Scientific and Research Projects


    SFB/Transregio 167 „Entwicklung, Funktion und Potential von myeloiden Zellen im zentralen Nervensystem (NeuroMac)“ Teilprojekt Z01 „Genomics and bioinformatics core“
      Description of the project:
      - no english description available -

      Folgt

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Backofen R
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2017
      End of project: 2020
      Project Management:
      Albert-Ludwigs-University Freiburg
      Backofen R
    DFG-Projekt: Die Populationsgenetik des CRISPR-Cas-Systems in Bakterien
      Description of the project:
      - no english description available -

      Das CRISPR-Cas-System (Clustered Regularly Interspaced Short Palindromic Repeats) ist ein weit-verbreitetes prokaryotischen, adaptives Verteidigungssystem gegen Phagen (Viren). Nach der Virusinfektion einer bakteriellen Zelle kann die Viren-DNA durch Cas-Proteine zerschnitten und in das CRISPR-Array von Spacer-Sequenzen eingebaut werden. Nachfolgende Infektionen mit demselben Virus werden nun verhindert, da fremde DNA, die mit dem Spacer übereinstimmt, das Ziel von Proteinen wird, die die erkannte DNA zerschneiden. Besitzt ein Bakterium nicht die richtige Spacer/Cas-Kombination und wird durch ein Virus angegriffen, so kann sich der Virus ausbreiten und das Bakterium umbringen.In unserem Projekt kombinbieren wir bioinformatische Expertise mit probabilistischer Modellierung, um quantitative, verlässliche Modelle zum Verständnis der Evolution des CRISPR-Arrays in nah verwandten Linien zu erhalten. Für unsere Arbeit ist die bioinformatische Analysis, inklusive Assemblierung und Klassifizierung (mittels Cas-Proteinen) von vorhandenen metagenomischen Data aus Meerwasser und dem menschlichen Darm fundamental. Die Modellierung von CRISPR-Evolution ist entweder neutral, wo neue Spacer-Sequenzen in das CRISPR-Array entweder zufällig oder zu Beginn des Arrays eintreten. Realistischere Szenarien basieren auf der Co-Evolution von Bakterien und Viren. Wir erweitern (die Analyse von) existierenden evolutionären Modellen durch einen Neutralitätstest und durch die Inferenz von horizontalem Gentransfer innerhalb des CRISPR-Cas-Systems.

      Additional information: http://www.bioinf.uni-freiburg.de
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2017
      End of project: 2019
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG SPP Probabilistic Structures in Evolution
    DFG-Projekt: Vorhersage von RNA-RNA Interaktionen durch kinetische Modellierung
      Description of the project:
      - no english description available -

      Folgt

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Backofen R
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2017
      End of project: 2019
      Project Management:
      Albert-Ludwigs-University Freiburg
      Backofen R
    DFG Projekt eCLASH: Definition des Interactomes kleiner RNA
      Description of the project:
      Amongst the first classes of non-coding RNAs to be described, microRNAs (miRNAs) represent a broad, tissue-specific post-transcriptional regulatory system active in virtually every cell-type. MiRNAs directly target mRNAs for post-transcriptional repression and are vital to organism complexity, development, and function. Aberrant miRNA expression has been causally implicated in disease states as disparate as cancer, metabolic disease, and neurodegeneration. The single greatest contemporary challenge for understanding miRNA biology is our inability to definitively predict or determine mRNA targeting, with current predictive methods providing ~20% accuracy in target prediction. Here, we build upon technological advances in the field and present data for a prototype technology, ‘eCLASH’, capable of unbiased direct determination of essentially all miRNA-mRNA target interaction events. In this project, we propose development and validation of the technology to the point of generating a universally applicable protocol usable in fresh or frozen (biobanked) primary tissues and cell-types. Since we are working with a high-throughput technology, an important part of the project is to establish a robust bioinformatics pipeline able to tackle the highly complex datasets in a biologist friendly platform. Finally, we aim to harness the technology to generate a powerful new community resource, mapping all miRNA-mRNA interaction events in at least 25 key tissues of the mouse. Critically, within the context of this mouse ‘interactome atlas’, we will directly map the full depth miRNA interaction profiles of control and metabolically diseased (Db/Db) mice and thus provide proof-of-concept for the utility of eCLASH in understanding disease associated miRNA-dependent gene regulation.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2016
      End of project: 2019
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
      Keywords:
        eCLASH
    Centre for Biological Signalling Studies SELEX for synthetic biology and nanoscale applications
      Description of the project:
      SELEX for synthetic biology and nanoscale applications Emerging new techniques such as super-resolution microscopy, hold the promise of detecting nanostructures of cell surface receptor, thus serving as invaluable tools for deciphering the receptor signaling mechanism. However, these methods are often limited by the availability of labeling tools and the general low labeling efficiency. Remarkably, aptamers, single-stranded DNA or RNA oligonucleotides selected in vitro for the desired targets, have been shown to surpass the normal antibody in reaching a higher labeling density for super-resolution microscopy. Although aptamers can be easily selected against virtually any target through an in vitro selection process known as SELEX (systematic evolution of ligands by exponential enrichment), the traditional random cloning and sequencing approaches only enable sampling of a small portion of the enriched sequences. For the determination of a small number of high affinity binders, it is often needed to perform the SELEX with more than 20 rounds, which is expensive and time consuming. Even worse, SELEX is a black box in this setting to be opened only at the last round. This creates many problems such as low reproducibility (different runs will produce different aptamers, sharing no similarity), PCR artifacts or background binding. In addition, the current technology usually does not allow inferring more general sequential or structural properties of high-affinity binding RNA aptamers. This hinders their applicability for synthetic biology applications, where an aptamer is integrated in a longer transcript to combine several functions. The rational design of these molecules would require such properties to be checked. To solve these problems, we propose to 1) combine the in vitro SELEX power with next generation sequencing (NGS) and advanced bioinformatics analysis to detect short binding motifs and their sequential and structural properties, and 2) to improve the SELEX protocol by partially including the iCLIP protocol, which is used to detect binding sites of RNA-binding proteins. The later will allow us to experimentally determine likely binding regions, a so far unsolved problem in SELEX. In addition, the project requires a constant interplay between lab work and bioinformatics, where selected motifs are tested in the lab, giving rise to additional information about functional motifs that will be used to improve the bioinformatics analysis.

      Additional information: http://www.bioss.uni-freiburg.de
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.11.2015
      End of project: 31.10.2017
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • Exzellenzinitiative DFG
      Keywords:
        BIOSS 2
    BWST_NCRNA_008 Determinanten der Interaktion nicht-kodierender RNAs mit regulatorischen Zielmolekülen
      Description of the project:
      - no english description available -

      Determinanten der Interaktion nicht-kodierender RNAs mit regulatorischen Zielmolekülen Tausende verschiedener nicht-kodierender RNAs wurden in Modellorganismen aller großen phylogenetischen Taxa identifiziert. Wirkmechanismen und exakte Funktionen sind häufig jedoch nicht bekannt, obwohl die Charakterisierung ausgewählter Moleküle die regulatorische Funktion nicht-kodierender RNAs klar etablieren konnte. Hier möchten wir grundlegende Parameter der Interaktion nicht-kodierender RNAs mit ihren Zielmolekülen untersuchen. In einem interdisziplinären Ansatz, der informatische Methoden mit experimentellen Analysen kombiniert, werden wir eine globale Methodik entwickeln, um die Kinetik von RNA Sense:Antisense Interaktionen zu modellieren. Solche Interaktionen beruhen zum Teil auf direkten RNA:RNA Wechselwirkungen, ein anderer Teil ist unter der Kontrolle von Proteinfaktoren, hier werden wir den Effekt von RNA-Helikasen untersuchen. Die Modellierungsergebnisse werden durch die experimentelle Untersuchung von Sense- Antisense Interaktionen in einem in vitro Fluoreszenzassay systematisch getestet. Die Analyse des CrhR RNA Helikase-gebundenen Transkriptoms in Synechocystis 6803 erfolgt durch Immunpräzipitation des CrhR Proteins und anschließender Hochdurchsatz- Sequenzanalyse. Für die exakte Bestimmung von RNA-Helikase-Bindemotiven werden wir eine UV-Quervernetzungs-Technik einsetzen. Im Ergebnis erwarten wir eine erheblich verbesserte Genom-weite Vorhersage des Interaktoms nicht-kodierender RNAs mit ihren Zielmolekülen. Die Resultate sind von grundlegendem Interesse u.a. für das Verständnis der Steuerung der Genexpression, der Zelldifferenzierung und Stress-Adaptation.

      Additional information: http://www.bioinf.uni-freiburg.de
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.09.2015
      End of project: 31.08.2018
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • Baden-Württemberg Stiftung gGmbH
    DFG-Projekt:Extending the theory of Algebraic Dynamic Programming for applications in bioinformatics
      Description of the project:
      Dynamic programming techniques are the basis of many algorithms used in bioinformatics, as for example the alignment methods used in comparative genomics or algorithms for RNA structure prediction. New insights lead to a continuous improvement of those algorithms and the development of many specialized variants. As a consequence, there is a growing demand to implement efficient prototypes of these algorithms quickly. This is in particular hard since for specialized problems the recursive structure of the corresponding dynamic programming algorithm becomes more and more complex. Algebraic Dynamic Programming (ADP) has been proven to be a suitable framework for the rapid development and efficient implementation of dynamic programming algorithms in bioinformatics. In this project we want to extend the theory of ADP to make it applicable to a larger class of problems, make it more efficient and more convenient to use. In particular, we want to formulate the problems of RNA pseudoknot alignment and RNA-RNA interactioin in ADP. Furthermore, we investigate how various optimization techniques that have been applied to dynamic programming algorithms recently, can be integrated in the ADP framework. This does not only lead to more efficient implementations, but also to a more precise and fundamental understanding of the optimizations and the circumstances under which they can be applied. Finally, we want to extend ADP with better support for probabilistic models which is essential for many applications.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.08.2015
      End of project: 31.07.2018
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    BMBF Verbundprojekt Deutsches Netzwerk für Bioinformatik-Infrastruktur (de.NBI)
      Description of the project:
      - no english description available -

      Das Deutsche Netzwerk für Bioinformatik-Infrastruktur (de.NBI) besteht aus spezialisierten Service-Einheiten mit herausragender Expertise in vielen Teildisziplinen der Lebenswissenschaften und lokalen Knoten für qualitativ hochwertige Datenbanken. Diese Einheiten sichern die Entwicklung bioinformatischer Ansätze und Technologien durch die Bündelung ihres Know-Hows und ihrer technischen Ausstattung. Die zentrale Leitlinie dieses Netzwerks ist die Bereitstellung und die kontinuierliche Weiterentwicklung bioinformatischer Dienstleitungen und Software-Lösungen für die Grundlagen- und die angewandte Forschung. Daneben sollen Standards für die Datenspeicherung und die Datenanalyse, das Datenmanagement und den Datenaustausch etabliert werden. Das Netzwerk wird durch eine Koordinationseinheit komplettiert, die Strategien für die langfristige und nachhaltige Etablierung der angebotenen Serviceleistungen und Datenressourcen entwickelt. In jüngster Zeit unterlagen die modernen Lebenswissenschaften einer äußerst schnellen Entwicklung, die vornehmlich durch technische Verbesserungen im analytischen Bereich, eine Miniaturisierung und Parallelisierung und den Einsatz von Hochdurchsatz-Technologien für biologische Proben angetrieben wurde. Dadurch wird in den Lebenswissenschaften ein enormer Umfang an experimentellen Daten generiert. Prominenteste Beispiele für diese weiterhin andauernde Entwicklung sind die Omics-Technologien, die durch die Analyse der verschiedenen Ebenen der Informationsspeicherung und Stoffwechselprozesse Einblicke in biologische Systeme in bisher unbekannter Tiefe ermöglichen. Die zunehmende Anwendung dieser neuen Technologien und die Auswertung der erhobenen Daten haben bereits viele Wissenschaftsbereiche revolutioniert und eröffnen neue Perspektiven für die Grundlagen- und die angewandte Forschung in den Lebenswissenschaften. Die Auswirkungen dieser Entwicklung sind nicht nur in der Wissenschaft, sondern auch in der Gesellschaft bemerkbar. Beispielsweise wird durch das Humane Mikrobiom-Projekt ein systematischer Katalog der taxonomischen Diversität der menschlichen Mikroflora generiert. Das Forschungsvorhaben ermöglicht zudem auch Einblicke in die verschiedenen Rollen der Mikroflora für die menschliche Gesundheit oder die Entwicklung von Krankheiten. Ein anderes Beispiel, das die Wissenschaft revolutioniert hat, ist die UniProt Knowledgebase, in der Informationen über Proteine als die wesentlichen Effektormoleküle der Zellen gesammelt sind. Auch das europäische Flaggschiffprojekt „Human Brain Project“ kombiniert Omics- und bioinformatische Methoden zur Aufklärung der Funktionsmechanismen im Gehirn und zum Verständnis von Gehirnerkrankungen. Der Fortschritt in den Lebenswissenschaften und die Generierung riesiger Mengen experimenteller Daten ist dabei auch von einer andauernden Entwicklung in der Bioinformatik begleitet, die Archivierung, Prozessierung, Visualisierung, und Integration dieser Daten betreffend. Es ist offensichtlich, dass die Verfügbarkeit gut angepasster bioinfomatischer Tools, entsprechender Hardware sowie manuell gepflegter, hochqualitativer Datenbanken eine grundlegende Voraussetzung für die Verarbeitung und Auswertung großer Datenmengen in den Lebenswissenschaften ist. Da der Umfang und die Komplexität der erzeugten Daten kontinuierlich weiter anwächst, wird auch eine permanente Weiterentwicklung der Bioinformatik benötigt, die sowohl den Ausbau der technischen Infrastruktur, wie Rechner- und Speicherkapazitäten, als auch die Entwicklung neuer spezialisierter Werkzeuge und Softwarelösungen umfasst. Das Deutsche Netzwerk für Bioinformatik-Infrastruktur greift diese Herausforderung in vielen Bereichen der Lebenswissenschaften auf, mit dem Ziel, ein Repertoire an spezialisierten Bioinformatik-Tools und qualitativ hochwertigen Datenbanken sowie notwendige Rechner- und Speicherkapazitäten bereitzustellen, auszubauen und stetig weiter zu verbessern. Das Leitmotiv für das Deutsche Netzwerk für Bioinformatik-Infrastruktur folgt damit wesentlichen Empfehlungen des deutschen Bioökonomierats, die in der Publikation „Anforderungen an eine Bioinformatik-Infrastruktur in Deutschland zur Durchführung von bioökonomierelevanter Forschung“ dargelegt sind. Das neue Konzept für ein Deutsches Netzwerk für Bioinformatik- Infrastruktur umfasst sechs vernetzte Leistungszentren, einen Datenbank-Knoten und einen Datenmanagement-Knoten, die gemäß ihrer jeweiligen Expertise spezifische Bioinformatik-Dienstleistungen vorhalten und kontinuierlich weiterentwickeln. Die ausgewählten Service-Einheiten bestehen aus mindestens zwei Projektpartnern aus verschiedenen Institutionen an verschiedenen Orten innerhalb Deutschlands, um eine thematisch optimale Abdeckung der Ressourcen und wissenschaftlichen Serviceleistungen zu gewährleisten. Zudem ergänzen sich die Service-Einheiten im Hinblick auf die thematische Ausrichtung und bioinformatische Expertise, damit zukünftigen Nutzern aus Wissenschaft und Industrie ein breites Angebot an Dienstleistungen angeboten werden kann. Die Infrastruktur des Netzwerks wird von einer Koordinations- und Managementstruktur unterstützt, die den wissenschaftlichen Austausch innerhalb der deutschen Bioinformatik-Community fördern und die vorhandenen Ressourcen optimal für Serviceleistungen in der Grundlagen- und der angewandten Forschung einsetzen soll. Das zentralisierte Management sichert zudem die Zugänglichkeit und Verfügbarkeit aller Infrastruktur-Elemente und Bioinformatik-Dienstleistungen für potentielle Nutzer und verfügt über Instrumente der internen Qualitätskontrolle und Qualitätssicherung.

      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.03.2015
      End of project: 28.02.2018
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    DFG Forschergruppe Untersuchung der prokaryotischen Immunsysteme I-B und I-D in archaea
      Description of the project:
      Bioinformatic analyses of CRISPR elements Most archaea and many bacteria have a defence system against a variety of invadinggenetic elements called CRISPR-Cas systems, which is based on RNA. This project aims at a better understanding of the CRISPR-Cas system by using highly advanced bioinformatics approaches. First, we will develop a fully automated annotation pipeline for CRISPR-Cas systems. There is a severe deficit in convenient annotation applications for CRISPR-Cas systems. In addition to our automated characterization ofCRISPR evolution (CRISPRmap), we intend to develop a web-server toolbox for a comprehensive automatic in silico characterization of many other important aspects ofCRISPR-Cas systems, including the prediction of the CRISPR orientation, the leader sequence and the first automated annotation of CRISPR-Cas subtypes.Second, we want to identify CRISPR targets (i.e. protospacers) and characterize associated protospacer-adjacent motif, PAM, important for both adaptation and interference. Our goal is to first collect a set of protospacers from viral genomes and metagenomics data. Subsequently, we will identify and analyze patterns of associated PAMs. Characterized PAM motifs and their properties will be validated the groups of Schmitz-Streit and Randau. Third, we want to detect requirements of a CRISPR array that lead to efficient cleavage in a cell. These requirements do not only help to expand our knowledge of the diverse CRISPR processing mechanisms, but also aid in the design of artificial arrays for experiments. With experiments performed by the Hess and Marchfelder groups, we will measure the effect of detailed sequence and structure constraints on processing efficiency. Finally, we want to, in collaboration with Jörg Vogel/Nadja Heidrich and Emmanuelle Charpentier, characterize further type II systems that require a non-coding RNA(tracrRNA). These systems are especially interesting since they are widely used for genome editing.

      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2015
      End of project: 2017
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG FOR 1680
    DFG-Projekt: ATP – Automatisierte intra-annuelle Jahrringanalyse für Dendroökologische Forschung
      Description of the project:
      - no english description available -

      Jahrringe archivieren datierbare Umweltinformationen über die Wachstumsbedingungen der Bäume zum Zeitpunkt ihrer Bildung. Die Dendrochronologie baut auf dem Prinzip des Cross-Datings auf, d.h. auf der Identifikation und Synchronisierung zeitspezifischer Muster zwischen mehreren Jahrringsequenzen. Zusammen mit den Ergebnissen der statistischen Analyse von Jahrringdaten liefert die Kenntnis der Zusammenhänge zwischen Umweltfaktoren und dem Baumwachstum die Grundlage für die Rekonstruktion vergangener Umweltbedingungen. Damit tragen jahrringbasierte Untersuchungen u.a. zur Klimarekonstruktion, zur archäologischen Forschung sowie zur Aufklärung vielfältiger ökologischer Forschungsfragestellungen bei. In diesem interdisziplinären Forschungsvorhaben zielen wir darauf ab, Methoden der Mustererkennung für die Analyse intra-annueller Jahrringdichteprofile für dendrochronologische und -ökologische Forschungsfragestellungen verfügbar zu machen und anzuwenden. In dem Vorhaben wird die Expertise der Dendroökologischen Arbeitsgruppe (Prof. Spiecker et al.) im Bereich der jahrringbasierten Umweltforschung mit dem Expertenwissen der Bioinformatikgruppe (Prof. Backofen et al.) im Bereich der Entwicklung von Alignment- und Clustermethoden für Anwendungen in der Bioinformatik zielgerichtet miteinander verknüpft. Unsere Forschungsaktivitäten sind darauf ausgerichtet verbesserte Methoden zu entwickeln um (1) die Umweltsignale bei der Aggregation intra-annueller Dichteprofile zu verstärken, (2) für intra-annuelle Jahrringpositionen hochaufgelöste zeitliche Annotationen zu generieren, und (3) auf dieser Grundlage intra-annuelle Jahrringsequenzen zu datieren und Chronologien aufzubauen. Zu diesem Zweck wollen wir den von uns bereits entwickelten MICA-Ansatz (Multiple Interval-based Curve Alignment), der aufbauend auf etablierten Sequenzalignment-Techniken signalverstärkte Konsensusprofile erzeugt, erweitern und verbessern. Die Anwendung auf die vorhandenen umfangreichen Daten zu intra-annuellen Jahrringdichteprofilen zielt darauf ab, räumliche Konsensusprofil-Chronologien für verschiedene Baumarten zu entwickeln. Darüberhinaus sollen die vorhandenen Punktdendrometerdaten unter Anwendung des MICA-Ansatzes zur Erzeugung zeitlich annotierter Konsensusprofil-Chronologien verwendet werden. Beide Typen von Chronologien werden für die Entwicklung neuer Datierungstechniken verwendet. Auf diese Weise wird eine höhere Informationsdichte für die Datierung nutzbar gemacht, als bei der ausschließlichen Verwendung der Jahrringbreite. Deshalb wird es mit diesen neuen Methoden möglich sein, kürzere Sequenzen zu datieren und eine höhere Datierungsgenauigkeit zu erreichen als bei den konventionellen Methoden. Schließlich wollen wir testen, ob Holzproben deren Herkunft nicht bekannt ist über diese Verfahren einem bestimmten Standort oder Standorttyp zugeordnet werden können. Alle entwickelten Methoden werden ausführlich dokumentiert und der Öffentlichkeit zugänglich gemacht.

      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2015
      End of project: 2017
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
    DFG-Projekt: Ein flexibles und effizientes System für RNA Sequenz-Struktur-Motive
      Description of the project:
      - no english description available -

      Nicht-kodierende RNAs (ncRNAs) sind an vielen regulatorischen Prozessen einer Zelle beteiligt. Eine große Anzahl von ncRNAs, von denen die meisten nicht annotiert sind, wird durch Transkriptomanalysen (next-generation-sequencing (NGS)) gefunden. Die funktionale Analyse von ncRNAs stützt sich maßgeblich auf Sequenz-Struktur Ähnlichkeiten. Wegen der hohen rechnerischen Komplexität werden jedoch Programme, die Sequenz-Struktur Ähnlichkeiten finden, zur Zeit nicht bei der Annotierung von neu gefunden ncRNAs verwendet. Gängige Computer-gestützte genomweite ncRNA Analysen benötigen oft enorme Rechenressourcen (zehn bis hundert Computer-Jahre). Unser Ziel ist es, ein effizientes System zur Analyse und Annotation von ncRNAs aufzubauen. Wir werden ein einfach zu bedienendes webbasiertes Interface bereitstellen, welches Biologen ermöglicht ncRNAs zu annotieren und diese in ihrem genomischen Kontext zu analysieren, indem personalisierte Tracks im Genom-Browser genutzt werden. Das kombinierte System wird Folgendes leisten: 1.) Suche nach annotierten ncRNAs oder ncRNA Transkripten in anderen NGS Daten sowie in ncRNA-Datenbanken, die strukturelle Ähnlichkeit mit einer neu entdeckten ncRNA haben. Wir werden sowohl strukturierte kleine ncRNAs als auch lange nicht-kodierende RNAs (lncRNA), bei denen noch keine global konservierte Struktur gefunden wurde, berücksichtigen. 2.) Clustern einer Menge von neuen nicht-kodierenden RNAs, um strukturelle Gruppen bestimmen zu können, was eine Voraussetzung für die funktionale Annotierung von neuen ncRNA Klassen darstellt. Dies beinhaltet insbesondere ein globales Clustern von kompletten Transkripten. Wir werden zusätzlich an dem Problem des lokalen Clusterns basierend auf lokalen Alignments arbeiten, um regulatorische Motive zu finden, die in längeren Transkripten eingebettet sind. Dieses Problem ist gegenwärtig nur schwer mit automatisierten Programmen zu lösen. Ein wichtiges Ziel ist die Verbesserung der Effizienz und der Qualität von unserem Sequenz-Struktur Alignment Programm unter Verwendung fortschrittlicher algorithmischer Techniken. Gegenwärtig sind die besten exakten algorithmischen Ansätze nicht effizient genug für das routinemäßige Scannen von hunderten (wenn nicht tausenden) ncRNAs, die typischerweise in Transkriptomdaten gefunden werden. Um unsere Programme in der Praxis anwendbar zu machen, und damit die Bedürfnisse unserer Kooperationspartner zu erfüllen, müssen wir schnelle und sensitive Filter entwerfen, um die Anzahl der teuren Sequenz-Struktur Vergleiche zu reduzieren. Bisherige Verfahren verwendeten sequenzbasiertes Filtern. Offensichtlich funktioniert dieses Filtern nur für ncRNAs mit hoher Sequenz-Ähnlichkeit. Es ist jedoch bekannt, dass konservierte ncRNAs eine sehr geringe Sequenz-Konservierung haben können. Demzufolge ist ein weiteres Ziel, schnelle Sequenz-Struktur basierte Filtermethoden zu entwickeln, die auf unserem effizienten Graph-Kernel Ansatz basieren.

      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2015
      End of project: 2017
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
    DFG-Projekt: Isolierung und funktionelle Charakterisierung von nicht-kodierenden RNAs in der FOXG1-abhängigen Vorderhirnentwicklung und im Rett-Syndrom
      Description of the project:
      Determination and functional characterisation of non-coding RNAs in FOXG1-dependent forebrain development and Rett-syndrome Rett-syndrome is an autism-spectrum disorder. Impaired neurodevelopment leads e.g. to progressive loss of cognitive capabilities, spastic paralysis, ataxia and epilepsy. 90% of Rett-syndrome cases are ascribed to mutations of MECP2, but FOXG1 haploinsufficiency results in similar phenotypes. Whether MECP2- and FOXG1-mediated Rett-syndrome share similarities on a molecular level has so far not been described in detail. Recent data suggest that expression of non-coding RNAs (ncRNA) is under control of MECP2 as well as FOXG1 and that they are implicated in the disease. Within this project we aim to perform a systematical analysis of molecular parallels between loss of MECP2 and FOXG1 in the forebrain of mice focussing on long ncRNAs (lncRNA). We will generate MECP2- and FOXG1-deficiency in FOXG1 expressing cells and elucidate transcriptomes in development and adulthood using high throughput sequencing. Further state-of-the-art interdisciplinary approaches within the fields of bioinformatics, molecular biology, and biochemistry will be used to predict and validate targets as well as molecular mechanisms on transcriptional and post-transcriptional level. With different approaches we will analyse the biogenesis of lncRNAs and their interaction with proteins, as well as with RNA and/or DNA. To reveal functional roles of specific lncRNA during neurodevelopment we will alter their expression and study the effects on proliferation, survival and neural specification of stem cells, as well as proper neuronal differentiation, as these processes are disturbed in Rett-syndrome. Using both Rett-syndrome mouse models we will elucidate whether and which specific lncRNA expression and mechanism is involved in the origin of this disease.

      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2015
      End of project: 2017
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • SPP 1738, DFG
      Keywords:
        DFG SPP 1738
    DFG-Projekt: MiRNA and RNA-binding proteins as integral part of cell communication: context-based target prediction and validation
      Description of the project:
      - no english description available -

      Die regulierende Wirkung von miRNAs wird maßgeblich durch die Anwesenheit anderer miR- NAs und RNA-bindender Proteine beeinflusst. Quantitative Methoden zur Vorhersage der genauen Beziehungen zwischen miRNAs und RBPs nutzen jedoch typischerweise nur die Informationen in der Nähe der Zielregionen und weisen daher erhebliche Mängel auf. Aus diesen Gründen entwickeln wir Techniken, die 1. zum einen experimentelle Daten in Zusammenarbeit mit iterative rechnerischen Verfahren zur Verbesserung der amiRNA vermittelte ZielRNA-Spaltung und mRNA-RNA Bindeprotein Interaktion liefern, 2. in kohärenter Weise die verschiedenen experimentellen Daten wie mRNA, miRNA-mRNA oder RBP-mRNA-Wechselwirkungen integrieren und 3. mit einer "globalen" Perspektive die verschiedenen mRNA-Molekül Interaktionen betrachten. Auf diese Weise wird es möglich einen Einblick in die korrelierten Wirkung verschiedener Regulationsmechanismen (RBPs, miRNAs) auf die Genexpression zu erhalten und grundlegende Einsichten in das Design der Informationskodierung RNA-Moleküle zu gewinnen.

      contact person: Prof. Dr. Rolf Backofen
      Phone: +49 (0)761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2015
      End of project: 2017
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • SPP 1395, DFG
    BMBF-Verbundprojekt e:Bio ReelinSys – Systembiologie Reelin-assoziierter neuropsychiatrischer Erkrankungen
      Description of the project:
      - no english description available -

      Das Verbundprojekt ReelinSys ist ein interdisziplinäres Konsortium, in dem die Expertisen renommierter Systembiologen, neurobiologischer Grundlagenwissenschaftler, psychiatrischer Kliniker, Mikrosystemtechniker und Bioinformatiker gebündelt werden, um systembiologische Methoden auf ein aktuelles, kompetitives Forschungsthema auf dem Gebiet der Neuropsychiatrie anzuwenden. Mit diesem Ansatz wird das Ziel verfolgt, exemplarisch ein Rahmenkonzept aufzustellen, bei dem ein umfassendes molekulares und systembiologisches Verständnis des komplexen Reelin-Signalnetzwerks in eine zukünftige klinisch-diagnostische und pharmakologisch-therapeutische Anwendung auf neuropsychiatrische Krankheitsbilder translatiert wird. Für die erfolgreiche Rekonstruktion von regulatorischen Netzwerken hat sich herausgestellt, dass die Information aus Expressions-Daten mit Informationen über andere regulatorische Komponenten wie Protein-Protein oder Protein-RNA-Interaktionen kombiniert werden müssen. Dies ist insbesondere auch deshalb wichtig, um die Information aus Projektteil I (zelluläres Modell) mit integrieren zu können. Bezüglich Protein-Protein Interaktionen ist zu sagen, dass einer der Hauptkomponenten in der Reelin-Signalkaskade das Dab1-Protein ist, welches downstream Signalmoleküle über SH2/PTB Interaktionen rekrutiert. Eine weitere Schlüsselfigur ist Nova2, welches Reelin-Signalling durch alternatives Spleißen von Dab1 moduliert. Hierbei moduliert Nova2 das alternative Splicen durch eine Protein-RNA Interaktion, ist also ein Spleißfaktor.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2013
      End of project: 2015
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    BMBF-Verbundprojekt e:Bio RNAsys – Systembiologie der RNA
      Description of the project:
      Regulatory RNA:RNA interactions have recently emerged as an important level of regulation of gene expression above the primary control of transcription at the level of DNA. Even simple unicellular bacteria possess hundreds of regulatory non-coding RNAs that interact with cellular mRNAs to modulate central biological functions. However, the specifics of RNA-based regulation, why certain regulatory mechanisms employ RNA molecules rather than proteins as regulators, the dynamics and integration of RNA into the global regulatory network are less understood. Here we will identify the principles and specific advantages of RNA-based regulation, analyse and model why certain regulatory circuits are built on RNA rather than protein components, and unravel the systemic functions of regulatory RNA as integral components of regulatory networks. Our ultimate goal is to exploit these principles inbiotechnology and medicine.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2013
      End of project: 2015
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    SFB 992 Medizinische Epigenetik Projekt Z01 - Tiefensequenzierung/Bioinformatik
      Description of the project:
      A molecular understanding of disease mechanisms requires a global approach for studying chromatin states and gene regulation. We will provide our computational infrastructure and expertise in bioinformatics and deep sequencing data analysis to the CRC 992 members to enable the genome-scale study of differential gene expression and DNA methylation patterns in various cell types and organisms. A dedicated data management centre will be developed to facilitate access, visualisation and routine analysis of the sequencing data. We will also offer regular training with a special focus on the web services provided by our group. We will thereby help to improve the capacity for epigenetic research towards the development of potential epigenetic therapies.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.07.2012
      End of project: 30.06.2020
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    Ideenwettbewerb Biotechnologie und Medizintechnik Ein synthetischer Schaltmechanismus zur Kontrolle der Funktion und Lokalisation von Proteinen in tierischen und menschlichen Zellen
      Description of the project:
      - no english description available -

      Das Thema dieses Vorhabens ist die Entwicklung und Charakterisierung eines neuartigen synthetisch biologischen Schaltmechanismus, mit dem die Funktion und Lokalisation von Proteinen in tierischen und menschlichen Zellen zeitaufgelöst gesteuert werden kann. Zur Realisierung dieser Idee soll ein neuartiger, synthetischer, biologischer Schalter entwickelt werden, der es erlaubt, durch Zugabe einer niedermolekularen Signalsubstanz ein beliebiges Zielprotein an ein zweites Protein zu fusionieren, wobei das zweite Protein die Funktion, Aktivität oder Lokalisation des Zielproteins kontrollieren kann. Die Ergebnisse der im Ideenwettbewerb "Biotechnologie und Medizintechnik" geförderten Machbarkeitsstudien wurden vom 16. bis 18. Januar 2012 im Haus der Wirtschaft in Stuttgart präsentiert. Aus den 42 vorgestellten Projektideen wurden zehn zur weiteren Förderung empfohlen. Über 150 Akteure aus Politik, Forschung, Wissenschaft und Wirtschaft nahmen an der Veranstaltung des Ministeriums für Wissenschaft, Forschung und Kunst Baden-Württemberg teil. Die Veranstaltung wurde vom Projektträger Jülich und der BIOPRO Baden-Württemberg unterstützt. Aus dem Bereich Synthetische Biologie wurde das Projekt "Ein synthetischer Schaltmechanismus zur Kontrolle der Funktion und Lokalisation von Proteinen in tierischen und menschlichen Zellen" von Prof. Dr. Rolf Backofen und Prof. Dr. Wilfried Weber ausgewählt.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2012
      End of project: 2015
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    DFG Forschergruppe Unravelling the prokaryotic immune system Bioinformatic analyses of CRISPR elements
      Description of the project:
      Prokaryotes acquire immunity against phages and viruses through a gene silencing pathway mediated by clusters of regularly interspaced short palindromic repeats, co-called CRISPR non-coding RNAs. The project aims to elucidate the mechanism underlying the processing of CRISPR-transcripts, targeting specificity of mature crRNA, and acquisition of new spacers using advanced bioinformatics tools. A complex of CRISPR-associated (CAS) proteins is known to process the CRISPR-transcripts and binds to a sequence/structure motif within the direct repeats. We use two approaches to predict the important secondary structure elements (1) We will analyse families of all known CRISPR repeats. (2) We will investigate the influence of the context sequence (flanking spacers) on the repeat structure and calculate structure quality measures for each occurrence. Mature crRNA targets either single-stranded RNA or double-stranded DNA. We will scan metagenomic data for novel proto-spacers, which are invading DNA/RNA that match a CRISPR-spacer and represent a putative target. With this set of proto-spacers, we will determine characteristic features of targeting single-stranded RNA, e.g. the interaction hybridization strength, accessibility of the target site, and various kinetic features. Based on experimental data for RNA-DNA interaction, we will also develop a novel classification approach for RNA-DAN interaction. Current data indicates an R-loop interaction, and we will combine sequence-based features of DNA-duplex stability with features from the predicted R-loop interaction.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2012
      End of project: 2014
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
    DFG-Projekt: MicroRNA as an integral part of cell communication: regularized target prediction and network preditction
      Description of the project:
      MicroRNAs, endogenously encoded small RNA molecules, play an integral part in transcriptional and post-transcriptional gene regulation. Recent discoveries indicate that miRNAs do not act independently but cooperatively act with other miRNAs and RNA binding proteins. However, current computational approaches do not not appropriately model these cooperative effects encrypted in the context of the miRNA binding sites. Furthermore, most machine learning approaches predict only interaction between miRNAs and their targets, but do not offer guidelines for mutagenesis based experimental verification. In order to assess contextual information a paradigm shift is needed. Therefore we propose (i) to build a miRNA target prediction pipeline that integrates explicit structural information on the interaction site context, (ii) to develop a combined computational and experimental strategies to assess by mutagenesis the importance of both individual positions and sequence/structural motifs in the context, and (iii) to use previous knowledge with expression data to generate tissue and disease specific interaction networks for evaluating the biological function of miRNA based regulation.

      Additional information: http://www.bioinf.uni-freiburg.de
      contact person: Prof. Dr. Rolf Backofen
      Phone: 0761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2012
      End of project: 2014
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Keywords:
        DFG SPP InKoMBio
    DFG-Projekt: Computational Detection of Bacterial ncRNAs and their Targets
      Description of the project:
      - no english description available -

      In this project, we want improve the functional prediction of sRNA by first improving the interaction prediction, and second, by considering additional regulatory elements. Concerning current approaches for the prediction of RNA-RNA interactions, there are several problems and limitations that will be dealt with in our project. First, we will improve the determination of transcript boundaries, since the folding quite strongly depends on the exact ends of the input sequence. Second, current interaction prediction tools suffer from a low specificity. We will therefore apply different techniques to improve the specificity such as the use of conservation information, the influence of other regulatory elements and the detection of further features influencing sRNA-mRNA interaction. Since kinetic effects can have a strong influence of RNA folding, we will explore this effect in detail for RNA-RNA interactions. Finally, the best models for interaction prediction are currently computationally too complex to be used on a regular basis. We will therefore improve the efficiency of these approaches.

      contact person: Prof. Dr. Rolf Backofen
      Phone: 0049 761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.06.2010
      End of project: 31.05.2013
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Keywords:
        DFG-Projekt
    DFG-Projekt: MicroRNA as an integral part of cell communication: regularized target prediction and network prediction
      Description of the project:
      MicroRNAs, gene encoded small RNA molecules, play an integral part in gene regulation by binding to target mRNAs and preventing their translation. The prediction of microRNA-mRNA binding sites and the resulting interaction network are essential to understand, and thus influence, regulation of a genetic information flow inside the living organism. Numerous algorithms have been proposed based on various heuristics; however the predictions often vary considerably. In this project we will extend a physical model for the binding of microRNAs to the corresponding target and establish an extended set of features influencing binding probabilities. We will be faced with the challenge of (i) too many features and (ii) few known interactions on which to train any prediction algorithm. This problem will be solved by using (i) information-theoretical criteria for feature reduction, (ii) regularization, (iii) application of the Infomax approach to guarantee minimal loss of information after dimension reduction, and (iv) experimental validation of theoretical predictions using a novel test system. This strategy will allow (i) statistical analysis of the predicted microRNA-mRNA hypergraph, (ii) characterization of network motives and hierachies, (iii) identification of missing links and (iv) removal of false interactions.

      contact person: Prof. Dr. Rolf Backofen
      Phone: 0049 761 203 7461
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2010
      End of project: 2011
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Keywords:
        DFG
    DFG-Projekt: A Flexible and Efficient System for the Detection of RNA Sequence/Structure Motifs
      Description of the project:
      In this project, we concentrate on algorithmic approaches for the comparison of RNAs. The comparison of RNAs requires to consider both the sequence and structure of the RNAs. We want to overcome the limitations of existing approaches in both expressivity and efficiency. We will investigate three directions: 1. We will study different means for improving the quality of RNA alignment algorithms. Thus, we will study different types of local RNA alignment algorithms (both sequence locality and a more recent new notion called structure locality), since RNA motifs are of local nature. Furthermore, we will consider an important class of structures (pseudoknots) usually not handled by RNA alignment tools. 2. Current RNA alignment algorithms are too time costly. We propose to study how different optimization techniques successfully applied to sequence alignment can be used in RNA alignment. 3. We will also perform tasks required for the success in practical applications. Thus, we plan to develop new filtering techniques for fast search of RNA motifs in genome databases, which is a necessary prerequisite to promote research on functional RNAs. We wsill investigate approaches for improving progressive multiple RNA alignment, and will train parameters on benchmark sets. This will also allow us to investigate the properties of the introduced scoring. Since any development will be incorporated into our widely used multiple alignment system LocARNA, this will produce one of the most advanced system for defining and searching various types of RNA motifs.

      contact person: Mathias Möhl
      Email: mmohl@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2009
      End of project: 2012
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
      Keywords:
        DFG-Projekt
    Centre for Biological Signalling Studies bioss from Analysis to Synthesis Area D1 Pathway assembler
      Description of the project:
      The BIOSS initiative will generate high-throughput data using novel technology that will be harnessed by BIOSS researchers via high quality experiments. High-throughput experiments require bioinformatics analysis afterwards, for the interpretation of the vast amounts of data that are produced – rigorous analysis, incorporating and respecting biological detail, is an absolute must. High-quality experiments in contrast require bioinformatics both for planning the experiment due to the combinatorial behavior of possible interactions (see Figure 1), as well as for analysis of the results after the experiment. Thus, bioinformatics has an important role to play in BIOSS in general, and project D1 – the BIOSS pathway assembler – in particular. The proposed Bioinformatics contributions to the BIOSS Pathway Assembler are: Prediction of the important players in signalling cascades. In-silico evaluation of signalling models. Design of key experiments, design of mutants/new fusion proteins The iterative refinement of models and experiments, since experiments lead to better models, which enable further well directed experiments. Analysis of the functional effects of the predicted and observed interactions. We will focus on ITAM-based signalling, and in particular on interactions between ITAM motifs and SH2 domains, with the SH2 domains of Syk and SHIP1 as our main example applications. Contrary to the earlier perception that negative regulators interact only with inhibitory motifs (ITIMs), it is now an emerging truth that reality is much more complex – for example, in spite of their very different functions, Syk and SHIP1 bind the same ITAM. Similarly, in addition to the established model of ITAMs and ITIMs “duelling” for the control of cellular activation within the immune system, it has been shown that ITAM-bearing receptors can also inhibit immune response (Hamerman and Lanier, 2006).

      Additional information: http://www.bioss.uni-freiburg.de
      contact person: Kousik Kundu
      Email: kousik@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2008
      End of project: 2011
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
      Keywords:
        DFG-Projekt
    DFG-Projekt: Computational Detection of Bacterial ncRNAs and their Targets
      Description of the project:
      Small non-coding RNAs (ncRNAs) in bacteria provide another layer to regulate gene expression. The main problems in this context are the detection of ncRNAs and the determination of the mRNA targets. In this project, both problems are considered. Current approaches for the detection of mRNA targets are not sufficient to get reliable predictions. A system will be developed that uses additional features known to be important in bacteria to improve prediction reliability and to determine the mode of regulation. Machine learning will be used to detect these features and to estimate their significance. The interactions will be experimentally validated by the cooperating scientists. Secondly, we will search for unknown ncRNAs and will investigate their properties. Current approaches look for structurally conserved regions, which alone is not sufficient to detect ncRNAs. We will generate models of bacterial regulatory elements (like terminator signals or protein binding sites) that can be found in most of the bacterial ncRNAs, and integrate this additional knowledge in our existing comparative approach. We will use this system to detect new ncRNAs as well as common structural/functional features of known ncRNAs and their targets.

      contact person: Steffen Heyne
      Email: heyne@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.05.2007
      End of project: 31.05.2010
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG SPP 1258/1
      Keywords:
        DFG-Projekt
    Freiburg Initiative for Systems Biology – FRISYS WP2 miRNAs and WP3 Transcriptional networks
      Description of the project:
      Since January 2007 the Freiburg Initiative for Systems Biology is hosting one of the new FORSYS centres for Systems Biology. Several pro- and eukaryotic model organisms are targeted by the FRISYS research program. These organisms have been selected to cover phylogenetic key positions of the plant and animal realm like cyanobacteria, the moss Physcomitrelle patents, the angiosperm Arabidopsis thaliana, the invertebrate roundworm Caenorhabditis elegans and the vertebrate zebrafish (Danio rerio) and are complemented by work on mammalian cell and organ cultures. In this project, we work within the subprojects WP2 and WP3 on the impact of regulatory RNAs and study of the transcriptional regulatory networks which control growth and differentiation in these organisms.

      Additional information: http://www.frisys.biologie.uni-freiburg.de
      contact person: Andreas Richter
      Email: arichter@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.10.2006
      End of project: 31.12.2009
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • BMBF
      Keywords:
        BMBF-Projekt
    DFG SFB 604 INST 275/169-1 Alternative Splicing as a Modulator of Signal Transdruction
      Description of the project:
      Cells can change their splicing pattern in response to signals. Therefore, alternative splicing contributes to signal protein variability and information flow modulation, besides of posttranslational modification, differential gene expression and others. Alternative splice variants of FGFR2. All these thirteen transcripts are confirmed by Reference Sequences (S: signal peptide, IG1, 2, 3: immunoglobulin domains, T: transmembrane domains, Boxes: exons, black: coding, grey: non-coding, white: exon¬skipping, red: prolonged exon, blue: shortened exon; drawing not to scale) For this reason, we want to investigate the effect of alternative splicing on multifunctional signalling proteins, and determine regulatory mechanisms. We want to focus both on EST-based as well as on non-EST-based prediction methods for the identification of transcript variants, especially of those which are in the focus of the SFB. We will identify cis-acting elements, which are statistically linked to splicing events. These are, for instance, hexamer distribution patterns, conservation of exons and flanking introns in paralogs and orthologs, the score values of splice sites, as well as secondary structure elements in mRNA molecules. To find conserved secondary structure elements, we will employ and advance algorithms, currently under development. Modern learning techniques such as Bayesian networks, which we have used previously for the identification of transcription factor binding sites, will be applied for the prediction of transcript variants. The predicted splice forms will be validated by RT-PCR and sequencing. To gain more insight into the regulation of alternative splicing of signal proteins, we will cluster biologically related proteins to determine over- and underrepresented sequence or structure elements. In particular, we will focus on the functional effects of an alternative splicing phenomenon at NAGNAG acceptor sites, which was recently described by our group, on genes under investigation within the framework of the SFB. The general project aim is the extraction of splicing rules for classes of proteins, e.g. growth factor receptors, developmentally co-expressed genes or proteins with similar or equal splice pattern variations.

      Additional information: http://www.sfb604.uni-jena.de/Project_B10_(Platzer)-highlight-Project_B10.html
      contact person: Prof. Dr. Rolf Backofen
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 06.06.2005
      End of project: 01.08.2009
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
      Keywords:
        DFG-Projekt
    EU-Projekt: Emergent organisation in complex biomolecular systems, EMBIO - Specific Targeted Research Project, NEST – EC Contract No. 012835
      Description of the project:
      Complexity and self-organisation are critical yet poorly understood phenomena. This project aims to develop and apply mathematical and computational approaches that will identify principles governing the emergent organisation of self-organising biomolecular systems. Computational methods for characterising the dynamics of these intrinsically complex processes will be developed and applied to protein folding and molecular self-assembly. The methodologies will focus on the complexitiy of the system’s dynamics thus advancing fundamental knowledge concerning the role of complexity in biological systems. In this project, we studied properties of energy landscapes of proteins and RNAs. We investigated how to (efficiently) measure features of the landscape such as the number of local minima, the size distribution of the basins of attraction, the barrier tree, etc. A number of techniques for this purpose have already been developed for the special case of RNA secondary structure [46, 47]. Most of them depend crucially on the possibility to enumerate the near-ground state part of the energy landscape. The structure of the barrier tree itself can be used to extract characteristic quantifiers. A simple approach [48] will be extended to more sophisticated tree descriptors. We propose here to develop similar tools that can be applied to lattice models of protein folding. In [38,39,40], we have designed a global optimization technique for HP-kind lattice models on the cubic and face-centred cubic lattices based on constraint programming approaches. The HP-model is a simplified protein model introduced by Ken Dill. It distinguishes between polar (P) and hydrophobic (H) amino acids, and searches for a conformation with a maximal packing of the hydrophobic (H) amino-acids. Using the constraint-based approach, we can successfully fold sequences up to length 300, thus greatly improving on the results of competing groups. We want to use and extend this method to generate also the near-ground state part. One aim is to enlarge the sequence length which can be accessed using this method. But still we have to cope with an exponentially increasing number of conformations. For this purpose, we want to combine stochastic search methods with constraint-based approaches. This "constraint-based sampling" allows us a more directed (targeted) investigation of the landscape, thus improving both quality and efficiency of the sampling.

      Additional information: http://www-embio.ch.cam.ac.uk
      contact person: Martin Mann
      Email: mmann@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.03.2005
      End of project: 31.08.2008
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • EU
      Keywords:
        EU-Projekt
    EU-Projekt: Reasoning on the Web with Rules and Semantics –REWERSE, Network of Excellence – EC Contract No. 506779
      Description of the project:
      The objective of our working group is to create the core of a Bioinformatics Semantic Web populated by a number of sample data sources and applications representative of the use of the Web in Bioinformatics and to demonstrate novel, reasoning-based solutions dealing with the following problems: Rules for mediation and to formulate complex queries Consistent integration of Bioinformatics data Adaptive portals for molecular biologists Bioinformatics is an ideal field for testing Semantic Web technologies for three reasons: First, Web-based systems and Web databases have been applied very early in Bioinformatics, second the dramatic increase of data produced in the field calls for novel processing methods, third, the high heterogeneity of Bioinformatics data require semantic-based integration methods. Consider the following scenario: a biologist obtains a novel DNA sequences nothing is known about. He or she wants to run an alignment, but has specific requirements for the alignment. These requirements are captured as rules and constraints, which are taken into account by the online accessible semantic Web enabled sequence comparison service. The researcher found a number of significantly similar sequences in yeast for which there is gene expression data available. The scientist requests from the semantic Web enabled gene expression database and tool expression data for the relevant genes. He or she defines rules, which capture which expression profiles are interesting, e.g. all genes which are highly expressed at the beginning and end of the experiment are of interest. The genes are part of a larger process and the researcher is interested in their gene products. A query to SWISSPROT determines these. Do these proteins interact with each other? To answer this question a semantic Web service is queried, which computationally determines protein interactions. A user-defined rule formulating what constitutes a protein domain interaction, is applied on the fly to SCOP, the structural classification of proteins, and PDB, a large protein structure database. The rule-based sequence similarity tool mentioned above is used to determine whether the scientists proteins of interest are similar to any interacting proteins computed from SCOP and the PDB

      Additional information: http://rewerse.net
      contact person: Dr. Sebastian Will
      Email: will@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.04.2004
      End of project: 29.02.2008
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • EU
      Keywords:
        EU-Projekt
    Verbundprojekt JCB (FSU) Jenaer Centrum für Bioinformatik FSU/Kern, Projekt D.5 (Stochastische, constraint-basierte Ansätze zur Beschreibung von regulativen Sequenzen, Forschungsvorhaben 0312704K
      Description of the project:
      The identification of transcription factor binding sites in promoter sequences is an important problem, since it reveals information about the transcriptional regulation of genes. For analysing transcriptional regulation,computational approaches for predicting putative binding sites are applied. Commonly used stochastic models for binding sites are position-specific score matrices, which show weak predictive power. The objective of subproject D5 was the development of modelling approaches for description and recognition of regulatory DNA sequences in order to improve the prediction performance, especially by taking additional structural properties into account. In a first step, we have focused on single transcription factor binding sites (TFBS). Since it is obvious that the traditionally sequence-position-centered view on TFBS with independence assumptions between the motif positions is not characteristic enough, we abstracted from the these motif models for TFBS and represented them as sets of characteristic properties of which the majority can be derived from sequence information (sequence- dependent structure contribution, coarse base profiles in the neighbourhood of the site, matches to small consensus sequences). Bayesian networks have recently attracted considerable attention for data modelling and classification since they are a sophisticated stochastical framework to model features of various value ranges and their statistical dependencies. A subtask of learning these Bayesian networks from sets of known TFBS samples is the automatic selection of a highly predictive property subset, for which we applied adaptions of sequential search algorithms. Most recently we have released a web application, BioBayesNet, which facilitates the use of Bayesian networks to external scientists. It allows to calculate properties from uploaded sequences, to search for discriminating property subsets and to learn and use Bayesian networks. This application is suitable not only for TFBS but for any sequence analysis task. In a second phase of the project we did research in an integration of the TFBS models in a model for regulatory modules which consists of arrangements of TFBS on promoter sequences. The resulting model is based on Hidden Markov models which runs on sequences of feature value vectors and uses the TFBS Bayesian networks as state output distributions. Another important situation occurring in analysis of regulatory sequences is that you are given a set of unaligned sequences. In this case, the only information is that the sequences contain a common motif. This problem is called motif discovery, and a standard approach uses EM-based algorithms (MEME). Again we were interested to include additional structural information. For that purpose, we have developed an extension to MEME which guides the EM algorithm to promising motif start positions using structural features. These features determine an informative prior on possible start positions.

      Additional information: http://www.imb-jena.de/jcb
      contact person: Prof. Dr. Rolf Backofen
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 01.02.2003
      End of project: 31.12.2007
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • BMBF
      Keywords:
        BMBF-Projekt
    DFG-Projekt: Schwerpunktprogramm Selenproteine – Biochemische Grundlagen und klinische Bedeutung – SPP 1087 Projekt: Algorithmic determination of whether a protein’s cysteine residue can be replaced by selenocysteine by silent/similar pointwise mutagenesis in DANN/RNA
      Description of the project:
      The 21st amino-acid selenocysteine is encoded by UGA, a codon that usually terminates the translation of the mRNA by the ribosome. The cotranslational insertion of selenocysteine in bacterial selenoproteins requires a special mRNA element (called SECIS, Selenocysteine Insertion Sequence) after the UGA codon. A problem that remains of active research interest is the characterization of the SECIS-element. A conserved pattern can be described for the natural SECIS-elements in E.coli. For the Gram positive anaerobe E.acidaminophilum that has at least 6 selenoproteins of different functions, no conserved pattern has been found for the corresponding SECIS-elements so far. In this project, a unique approach to characterize SECIS-elements of E.acidaminophilum will be applied by throughly combining bioinformatics methods and corresponding biological experiments. Using a SELEX method, mRNA sequences will be generated that bind to SelB. These sequences will be combined into a consensus motif using bioinformatics methods. This motif can be used in a computer program that allows to assign for any mRNA sequence the probability of being a SECIS-element. To validate the motif found, high scoring RNA sequence will be tested for their capability of binding to SelB, using again SELEX methods.

      contact person: Prof. Dr. Rolf Backofen
      Email: backofen@informatik.uni-freiburg.de
      Runtime:
      Start of project: 2002
      End of project: 2005
      Project Management:
      Albert-Ludwigs-University Freiburg
      Prof. Dr. Rolf Backofen
      Financing:
      • DFG
      Keywords:
        DFG-Projekt