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Reactome a pathways knowledgebase. Imre Vastrik EMBL-European Bioinformatics Institute 6/10/2005. The Plan. Why? How? What does it look like/what can you do with it?. From data to knowledge. Decrease in computational access. Insulin binds the insulin receptor, causing it to
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Reactomea pathways knowledgebase Imre Vastrik EMBL-European Bioinformatics Institute 6/10/2005
The Plan • Why? • How? • What does it look like/what can you do with it?
From data to knowledge Decrease in computational access
Insulin binds the insulin receptor, causing it to dimerise. The dimerised form the autophosphorylates on 6 cytoplasmic tyrosines. This phosphorylated form recruits the IRS adaptor....
…and exhaustion Decrease in computational access
Why? • How? • What does it look like/what can you do with it?
History of Reactome • Started as Genome Knowledgebase in spring 2001. • Aim: capture the knowledge of biological experts in a form that could be searched and reasoned over electronically, and which could act as a connecting link between sequence records and primary biomedical literature. • Initially tried to capture and standardise the language used to describe molecular processes. • 2001/2002 realised that what we are trying to capture are reactions and pathways. • Rebranded as Reactome June 2004.
Insulin Insulin Insulin Insulin extracellular region [GO:0005576] plasma membrane [GO:0005886] Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Cytosol [GO:0005829] x12 x12 P P P P IRS ADP ATP Reactome data model
PMID:11737239 PMID:8276779 PMID:7781591 PMID:8276779 PMID:8039601 UniProt:P01308 transmembrane receptor protein tyrosine kinase activity [GO:0004714] Insulin Insulin Insulin Insulin extracellular region [GO:0005576] plasma membrane [GO:0005886] Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Insulin receptor Cytosol [GO:0005829] x12 x12 P P P P IRS ADP ATP IRS-1 IRS-2 DOK1 UniProt :P35568 UniProt :Q9Y4H2 UniProt :Q99704 UniProt:P06213 ChEBI:2359 ChEBI:2342 Reactome data model
Insulin receptor Insulin receptor Insulin receptor Insulin receptor x12 x12 ADP ATP Reactome data model PMID:11737239 PMID:8276779 PMID:7781591 PMID:8276779 PMID:8039601 UniProt:P01308 Insulin signalling transmembrane receptor protein tyrosine kinase activity [GO:0004714] Insulin Insulin Insulin Insulin extracellular region [GO:0005576] plasma membrane [GO:0005886] Insulin receptor Insulin receptor Insulin receptor Insulin receptor Cytosol [GO:0005829] P P P P IRS IRS-1 IRS-2 DOK1 UniProt :P35568 UniProt :Q9Y4H2 UniProt :Q99704 UniProt:P06213 ChEBI:2359 ChEBI:2342
Ambiguity of connection maps… A B + + C + D Do you need A & B or just A | B to get active C?
…is avoided by using states and reactions A & B A | B C C A A B C’ B D D C’’ C’’ D’ D’
About mice and men… PMID:5555 PMID:8976 PMID:3924 PMID:4444 human mouse rat human
… and how not to mix them PMID:5555 PMID:4444 Direct evidence Direct evidence human Indirect evidence PMID:8976 mouse Indirect evidence PMID:3924 rat
Two FAQs • What about tissue specific reactions? • We annotate to the union of all possible reactions: gene expression data gives the set of reactions feasible in a cell • What about fine dynamic balances? • We only capture qualitative information. The quantitative/model aspects has to be handled by ODEs/Kds and SBML like techniques. We can link to these resources, but they are out of scope for the moment
Expert (external) Curator (staff) Reviewer (external)
Release cycle Repository Extract finished & reviewed topics Computationally project pathways to other organisms Add cross-references (Ensembl, Entrez Gene, MIM, KEGG,…) Release DB www.reactome.org
Reactome in numbers(release 15, 26/9/2005) Human: • Reactions 1524 • Pathways 659 • Proteins 1095 • “Small molecules” 379 • Complexes 982 • Literature references 1408 • Interactions 19471
Why? • How? • What does it look like/what can you do with it?
Homo sapiens HSA Mus musculus MMU Tetraodon nigroviridis TNI Drosophila melanogaster DME Caenorhabditis elegans CEL Saccharomyces cerevisiae SCE Aspergillus nidulans ANI Schizosaccharomyces pombe SPO Arabidopsis thaliana ATH Dictyostelium discoideum DDI Plasmodium falciparum PFA Methanococcus jannaschii MJA Sulpholobus solfataricus SSO Escherichia coli ECO Bacillus subtilis BSU Anabaena ANA
Species 1 Human Species 2 Rules for orthology-based inference • 75% of a complex must have orthologs • Lineage specific paralogs are allowed • All small molecules presumed to exist if reactions exist • Otherwise every input, output, catalyst must be present
+ + + - ? + + - ? - - - - - - + ? + + + + - - ? - - - - - - - Finding lineage-specific deletions HSA MMU TNI DME CEL SCE ANI SPO ATH DDI PFA MJA SSO ECO BSU ANA
Absent in cerevisiae and pombe, but present in aspergillus Lipid metabolism Metabolism of amino acids Nucleotide metabolism (transport) Xenobiotic metabolism
Trp Catabolism Insulin Signalling DNA Repair Redundant Paths Head or Tail Pathway modules Lineage Deletion rates
Tissue expression more correlated Data from Human Novartis Affy scan
Reactome at a glance • Catalogue of all possible reactions (topology) in an organism - reactome • Authored by experts • Currently human orientated • Computational predictions to other species • Data & code freely available (www.reactome.org/download): • MySQL database, SBML, BioPAX + specialised datasets • Perl and Java APIs • Website mirror • Data entry tool
Groups & People www: http://www.reactome.org e-mail: help@reactome.org NHGRI Grant # R01 HG002639 EU STREP EMI-CD EBI Industry program