Presentation is loading. Please wait.

Presentation is loading. Please wait.

Reactome a pathways knowledgebase Imre Vastrik EMBL-European Bioinformatics Institute 6/10/2005.

Similar presentations


Presentation on theme: "Reactome a pathways knowledgebase Imre Vastrik EMBL-European Bioinformatics Institute 6/10/2005."— Presentation transcript:

1 Reactome a pathways knowledgebase Imre Vastrik EMBL-European Bioinformatics Institute 6/10/2005

2 The Plan Why? How? What does it look like/what can you do with it?

3 From data to knowledge Decrease in computational access

4 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....

5

6 Decrease in computational access …and exhaustion

7

8

9 Why? How? What does it look like/what can you do with it?

10 History of Reactome Started as Genome Knowledgebase in spring 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.

11 plasma membrane [GO: ] Cytosol [GO: ] extracellular region [GO: ] Reactome data model Insulin Insulin receptor Insulin Insulin receptor PP Insulin IRS Insulin Insulin receptor PP ATP x12 ADP x12

12 Reactome data model UniProt:P01308 UniProt:P06213 PMID: PMID: PMID: PMID: PMID: ChEBI:2359ChEBI:2342 IRS-1IRS-2 DOK1 UniProt :Q9Y4H2UniProt :Q99704UniProt :P35568 plasma membrane [GO: ] Insulin Insulin receptor Insulin Insulin receptor Insulin Insulin receptor PP PP Insulin IRS ATP x12 ADP x12 Cytosol [GO: ] extracellular region [GO: ] transmembrane receptor protein tyrosine kinase activity [GO: ]

13 plasma membrane [GO: ] Reactome data model Insulin Insulin receptor Insulin Insulin receptor Insulin Insulin receptor PP PP Insulin IRS IRS-1IRS-2 DOK1 UniProt :Q9Y4H2UniProt :Q99704UniProt :P35568 UniProt:P01308 UniProt:P06213 ATP x12 ADP x12 ChEBI:2359ChEBI:2342 transmembrane receptor protein tyrosine kinase activity [GO: ] PMID: PMID: PMID: PMID: PMID: Cytosol [GO: ] extracellular region [GO: ] Insulin signalling

14 Ambiguity of connection maps… AB C D ++ + Do you need A & B or just A | B to get active C?

15 …is avoided by using states and reactions A C C’ C’’ B D D’ A C C’’ B D D’ A & BA | B

16 About mice and men… humanmouserathuman PMID:5555PMID:4444PMID:8976PMID:3924

17 … and how not to mix them human PMID:5555PMID:4444 mouse rat Direct evidence Indirect evidence PMID:8976 PMID:3924

18 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

19 Reviewer (external) Curator (staff) Expert (external)

20 Release cycle Repository Release DB Extract finished & reviewed topics Computationally project pathways to other organisms Add cross-references (Ensembl, Entrez Gene, MIM, KEGG,…)

21 Reactome in numbers (release 15, 26/9/2005) Human: Reactions1524 Pathways659 Proteins1095 “Small molecules”379 Complexes982 Literature references1408 Interactions19471

22 Why? How? What does it look like/what can you do with it?

23 HSA MMU ANA BSU ECO SSO MJA PFA DDI ATH ANI SPO SCE CEL DME TNI Homo sapiens Schizosaccharomyces pombe Mus musculus Tetraodon nigroviridis Drosophila melanogaster Caenorhabditis elegans Saccharomyces cerevisiae Aspergillus nidulans Arabidopsis thaliana Dictyostelium discoideum Plasmodium falciparum Methanococcus jannaschii Sulpholobus solfataricus Escherichia coli Bacillus subtilis Anabaena

24 Human Species 1 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

25 HSA MMU ANA BSU ECO SSO MJA PFA DDI ATH ANI SPO SCE CEL DME TNI Finding lineage-specific deletions ?++ ? ? + ?

26 Lineage-specific deletion rates

27 Absent in cerevisiae and pombe, but present in aspergillus Lipid metabolism Xenobiotic metabolism Metabolism of amino acids Nucleotide metabolism (transport)

28 Lineage Deletion rates Trp Catabolism Head or Tail DNA Repair Redundant Paths Insulin Signalling Pathway modules

29 Presence of “small molecules”

30 Tissue expression Data from Human Novartis Affy scan more correlated

31 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

32 Cold Spring Harbor LaboratoryEuropean Bioinformatics InstituteGene Ontology Consortium Lincoln Stein Peter D'Eustachio Lisa Matthews Gopal Gopinath Marc Gillespie Guanming Wu Elizabeth Nickerson Marcela Tello-Ruiz Geeta Joshi-Tope Ewan Birney Imre Vastrik Esther Schmidt Bijay Jassal Bernard de Bono David Croft Suzanna Lewis Groups & People NHGRI Grant # R01 HG EU STREP EMI-CD EBI Industry program www:http://www.reactome.org


Download ppt "Reactome a pathways knowledgebase Imre Vastrik EMBL-European Bioinformatics Institute 6/10/2005."

Similar presentations


Ads by Google