Clustering and scoring molecular interactions relying on community standards
•Download as PPT, PDF•
0 likes•30 views
This document summarizes standards and services for clustering and scoring molecular interactions. It describes how PSICQUIC allows querying multiple interaction databases using a single query and returns standardized PSI-MI results. It also describes how the MI cluster service clusters interactions to remove redundancy while preserving source information. Finally, it describes how PSISCORE calculates annotation-based confidence scores for interactions from different sources based on supporting evidence.
Recommended
More Related Content
Similar to Clustering and scoring molecular interactions relying on community standards
Similar to Clustering and scoring molecular interactions relying on community standards (20)
More from Rafael C. Jimenez
More from Rafael C. Jimenez (20)
Recently uploaded
Recently uploaded (20)
Clustering and scoring molecular interactions relying on community standards
- 1. EBI is an Outstation of the European Molecular Biology Laboratory. Clustering and scoring molecular interactions relying on community standards Rafael C. Jimenez rafael@ebi.ac.uk
- 2. • Collaboration among multiple repositories in one field • Adoption of standards • Coordination on data deposition Nucleotide Sequences INSDC EMBL DDBJ NCBI Mass spectrometry ProteomeXchange PRIDE PeptideAtlas GPMDB Tranche … Interactions IMEx IntAct BIND DIP MINT … Sharing infrastructures Better accessibility More data coverage Less redundancy
- 3. Master headline23.08.183 PSI-MI standards Data format Data distribution Data description Minimum data PSICQUIC MIMIxPSI-MI CV Data scoring PSISCORE PSI-MI XML PSI-MITAB PSI-MI
- 4. 23.08.184 PSICQUIC Query Interactions PSICQUIC Registry PSI-MIMIQL Input Output PSICQUIC Service A PSICQUIC Service B PSICQUIC Service C User View Web Service System Data Provenance PSICQUIC PMID: 21716279
- 5. Master headline23.08.185 PSICQUIC Registry • 16 PSICQUIC services • 16,335,145 interactions
- 7. Master headline23.08.187 MI cluster • Clusters binary interactions providing non redundant information • It looks at all the interactor accessions • Primary identifiers, aliases and cross-references • Rely on standards (PSI-MI format and PSI-MI CV) • Results back in PSI-MI format • Also mapping information between the data provider and the original data. • Used by … PSICQUIC view, IntAct, EnCore, Reactome and the EBI search • Freely available: • Java API (Maven dependency) http://code.google.com/p/enfin-core/wiki/wp1_encore_tools_micluster
- 9. MI score • Designed to calculate annotation evidence • Based on common and minimum experimental information • Number of publications • experimental detection methods (CV) • interaction types (CV) • Formula based on curation experience • Default parameters are configurable • Rely on standards (PSI-MI format, PSI-MI CV, MIMIx) • Scores between 0-1 • One method to score interactions from different resources • Used by … the EBI search, EnCore and UniProt • Freely available: • Java API (Maven dependency) & PSISCORE web service http://code.google.com/p/enfin-core/wiki/wp1_encore_tools_micluster
- 10. Example Master headline23.08.1810 PSICQUIC Services Binary interaction evidences Publications Interaction Type Detection Method MI score String 4 1 - experimental interaction detection predictive text mining interologs mapping inferred by curator 0.06 IntAct 2 1 direct interaction cross-linking study 0.44 iRefIndex 17 9 physical association confirmational text mining coimmunoprecipitation surface plasmon resonance interologs mapping 0.54 DIP InnateDB IntAct MINT Reactome 14 10 direct interaction physical association pull down anti tag coimmunoprecipitation coimmunoprecipitation surface plasmon resonance two hybrid cross-linking study inferred by curator 0.94 APID DIP InnateDB IntAct MINT Reactome Reactome-FIs STRING iRefIndex 43 16 direct interaction association physical association confirmational text mining anti tag coimmunoprecipitation coimmunoprecipitation surface plasmon resonance two hybrid experimental knowledge based pull down experimental interaction detection predictive text mining interologs mapping cross-linking study inferred by curator 0.97 Scoring clusters P37173 interacts with P01137 TGFR2_HUMAN TGFB1_HUMAN
- 11. Master headline23.08.1811 PSICQUIC & PSISCORE 0.90 0.380.25 —0.63 0.45 0.71 0.40 0.11 PSICQUIC PSISCORE Query Interactions PSI-MI 0.90 0.380.25 —0.63 0.45 0.71 0.40 0.11 PSICQUIC Registry Confidence Scores PSI-MIMIQL PSISCORE Registry client Input Input Output Output PSICQUIC Service A PSICQUIC Service B PSISCORE Service D PSISCORE Service E PSICQUIC Service C User View Web Service System
- 12. PSISCORE client
- 13. Master headline23.08.1813 Thank you! Questions? AcknowledgementsProteomicsServicesTeam Work supported by the Enfin grant (EU contract number LSHG-CT-2005-518254) Hagen BlankenburgHenning Hermjakob Sandra Orchard Marine Smousseau Samuel Kerrien Bruno Aranda