Current and Future Directions

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Presentation transcript:

Current and Future Directions State of CBIL Current and Future Directions

Computational Biology and Informatics Laboratory October, 2001

CBIL Research Gene Discovery Gene Regulation EST analysis Genomic sequence analysis Gene Regulation Microarray analysis Promoter/ regulatory region analysis Biological data representation Data integration Ontology

CBIL: Gene Discovery Gene Annotation (Kolchanov) Gene coding potential Gene function prediction AllGenes EPConDB (Kaestner, Permutt, Melton) StemCellDB/ StroCDB (Lemischka, Moore) Mouse chromosome 5 (Bucan) PlasmoDB (Roos, Kissinger) ParaDB (Roos) Posters

CBIL: Gene Regulation PaGE PROM_REC TESS Pancreatic development (Kaestner) TGF-B signaling (Bottinger) Fetal globin expression in adults (Fortina) Brain disease and injury (Eberwine, Meaney) Endothelial cell function (Davies)

CBIL: Biological Data Representation Genomic Unified Schema RNA Abundance Database Connecting to a brain atlas (Nissanov, Davidson) Microarray ontology (MGED)

CBIL Project Architecture Sequence & annotation Gene index (ESTs and mRNAs) Microarray expression data experimental annotation Relational DB (Oracle) with Perl object layer GUS RAD

GUS: Genomics Unified Schema free text Controlled vocabs. GO Species Tissue Dev. Stage Genes, gene models STSs, repeats, etc Cross-species analysis Genomic Sequence RAD RNA Abundance DB Characterize transcripts RH mapping Library analysis Cross-species analysis DOTS Transcribed Sequence Special Features Transcript Expression Arrays SAGE Conditions Ownership Protection Algorithm Evidence Similarity Versioning under development Domains Function Structure Cross-species analysis Protein Sequence Pathways Networks Representation Reconstruction

Clusters vs. Contig Assemblies UniGene Transcribed Sequences (DOTS) BLAST: Clusters of ESTs & mRNAs CAP4: Consensus Sequences -Alternative splicing -Paralogs

Assembled Transcripts About 3 million human EST and mRNA sequences used Combined into 797,028 assemblies Cluster into 150,006 “genes” Can identify a protein for 76,771 genes And predict a function for 24,127 genes About 2 million mouse EST and mRNA sequences used Combined into 355,770 assemblies Cluster into 74,024 “genes” Can identify a protein for 34,008 genes And predict a function for 15,403 genes

Crabtree et al. Genome Research 2001 Bridging Fingerprint Contigs and RH Maps on Mouse Chromosome 5 Crabtree et al. Genome Research 2001 Fingerprint Map Chr. 5 RH Map

Predicting Gene Ontology Functions

AllGenes

AllGenes Enhancements: Annotated Entries

AllGenes Enhancements: Genomic Data

http://plasmodb.org New site

Contig View OM Restriction Sites Microsatellites Self-BLAST NRDB-BLAST SAGE Tags EST/GSS FullPHAT GeneFinder GlimerM Annotation (chr2-TIGR)

RAD: RNA Abundance Database Experiment Platform Raw Data Processed Data Algorithm Metadata Compliant with the MGED standards

Microarray Gene Expression Database group (MGED) International effort on microarray data standards: Develop standards for storing and communicating microarray-based gene expression data defining the minimal information required to ensure reproducibility and verifiability of results and to facilitate data exchange (MIAME, MAGEML-MAGEDOM) collecting (and where needed creating) controlled vocabularies/ ontologies. developing standards for data comparison and normalization. The schema is compliant with the minimum annotations recommended by MGED. MIAME: Minimum Information About a Microarray Experiment (common set of concepts that need to be captured in a database to describe gene expression experiments adequately for interpretation, reproduction or critical assessment). MAML: MicroArray Mark-up Language (XML Document Type Definitions of the concepts). http://www.mged.org

EPConDB Pathway query

Microarray Analysis: PaGE

RAD GUS EST clustering and assembly Identify shared TF binding sites TESS (Transcription Element Search Software) PROM-REC (Promoter recognition) Genomic alignment and comparative Sequence analysis Identify shared TF binding sites

Promoter Analysis: PROM_REC

http:www.cbil.upenn.edu

CAP4 provided by Paracel Acknowledgements CBIL: Chris Stoeckert Vladimir Babenko Brian Brunk Jonathan Crabtree Sharon Diskin Greg Grant Yuri Kondrakhin Georgi Kostov Phil Le Li Li Junmin Liu Elisabetta Manduchi Joan Mazzarelli Shannon McWeeney Debbie Pinney Angel Pizarro Jonathan Schug PlasmoDB collaborators: David Roos Martin Fraunholz Jesse Kissinger Jules Milgram Ross Koppel, Monash U. Malarial Genome Sequencing Consortium (Sanger Centre, Stanford U., TIGR/NMRC) EPConDB collaborators: Klaus Kaestner Marie Scearce Doug Melton, Harvard Alan Permutt, Wash. U Comparative Sequence Analysis Collaborators: Maja Bucan Shaying Zhao Whitehead/MIT Center for Genome Research CAP4 provided by Paracel

CBIL: Future Directions Sequence/ Sequence annotation Gene expression experiment Proteomics, Metabolomics Pathways/ Networks