Demo Presentation Wageningen Text Mining Workshop 2007

with AIDA Marco Roos , Scott Marshall, Sophia Katrenko, Edgar Meij, Willem van Hage, Pieter Adriaans AIDA demonstration Wageningen, 23/11/2007 Adaptation of Talk for Taverna/OMII-UK workshop, Hinxton, October 2007

About e-Science An e-science approach to mining biomedical literature

and beer… And how we relate it to beer…

Virtual Laboratory e-Science project

Wet laboratory analogy Data Data handling & Data integration Metadata Data analysis Data storage Expert knowledge

General framework of AID for VL-e Middleware for sharing resources Knowledge-based resource management

General framework of AID for VL-e Middleware for sharing resources Model based resource management TM TM TM TM TM TM

Theme An e-Science approach to mining biomedical literature

and beer… And how we relate it to beer…

10/06/09 BioAID Which diseases may be associated with my protein of interest?

Biomedical knowledge repository 10/06/09 BioAID PubMed statistics http://www.ncbi.nlm.nih.gov/entrez >17 million citations >400,000 added/year ~70,000 searches/month … Does not compute Does not fit

Bioinformatics A bioinformatician

Bioinformatics A typical bioinformatician

Bioinformatics A biologist behind a computer who (just) learned perl

/* * determines ridges in htm expression table */ #include "ridge.h" int selecthtm(PGconn *conn, char *htmtablename, char *chromname, PGresult *htmtable) { char querystring[256]; sprintf("SELECT * FROM %s WHERE chrom = %s ORDER BY genstart", htmtablename, chromname); htmtable = PQexec(conn, querystring); return(validquery(htmtable, querystring)); } int is_ridge(PGresult *htmtable, int row, double exprthreshold, int mincount) /* determines if mincount genes in a row are (part of) a ridge */ /* pre: htmtable is valid and sorted on genStart (ascending) /* post: { if (mincount<=0) return TRUE; if (row>=PQntuples(htmtable)) return FALSE; if(PQgetvalue(htmtable, 0, PQfnumber(htmtable, "movmed39expr")) < exprthreshold) { return FALSE; } return(is_ridge(htmtable, ++row, exprthreshold, --mincount)); } int main() { PGconn *conn; /* holds database connection */ char querystring[256]; /* query string */ PGresult *result; int i; conn = PQconnectdb("dbname=htm port=6400 user=mroos password=geheim"); if (PQstatus(conn)==CONNECTION_BAD) { fprintf(stderr, "connection to database failed. "); fprintf(stderr, "%s", PQerrorMessage(conn)); exit(1); } else printf("Connection ok "); sprintf(querystring, "SELECT * FROM chromosomes"); printf("%s ", querystring); result = PQexec(conn, querystring); if (validquery(result, querystring)) { printresults(result); } else { PQclear(result); PQfinish(conn); return FALSE; } PQclear(result); PQfinish(conn); return TRUE; } int printresults(PGresult *tuples) { int i; for (i=0; i< PQntuples(tuples) && i < 10; i++) { printf("%d, ", i); printf("%s ", PQgetvalue(tuples,i,0)); } return TRUE; } int validquery(PGresult *result, char *querystring) { printf(" in validquery "); if (PQresultStatus(result) != PGRES_TUPLES_OK) { printf("Query %s failed. ", querystring); fprintf(stderr, "Query %s failed. ", querystring); return FALSE; } return TRUE; }

Theme No , that is not an e-Science approach to mining biomedical literature

Not e-science So 2000 (quoting Lennart Post)

Not e-science So 1980

Theme An e-Science approach to mining biomedical literature

An e-science approach

e-Science

Collaboration

Combining expertise

Sharing

Technology

e -Scientists Edgar Meij Information retrieval expert

e -Scientists Sophia Katrenko Machine learning (information extraction) expert

e -Scientists Willem van Hage Semantic web expert (and bass guitar player)

The AIDA toolbox for knowledge extraction and knowledge management in a virtual laboratory for e -Science

e -bioscience An e-bioscientist

Components of the AIDA toolbox used for Life Science knowledge extraction

Bio AID Disease Discovery workflow 10/06/09 BioAID AIDA AIDA OMIM service (Japan) AIDA ‘ Taverna shim’ Taverna ‘shim’

An e-science approach

e-Science

Collaboration

Combining expertise

Sharing

Technology

Sharing

with AIDA Live Demonstration Marco Roos , Scott Marshall, Sophia Katrenko, Edgar Meij, Willem van Hage, Pieter Adriaans AIDA demonstration Tavena/OMII-UK, Hinxton, October 2007

10/06/09 BioAID Which diseases may be associated with my protein of interest?

10/06/09 BioAID

Components of the AIDA toolbox used for Life Science knowledge extraction

10/06/09 BioAID

Sharing

Bio AID Disease discovery workflow

Bio AID Disease discovery workflow 10/06/09 BioAID

Bio AID Disease discovery workflow from 100 abstracts: 29 proteins associated with 1280 diseases 10/06/09 BioAID

Extending BioAID

Extending BioAID workflows

10/06/09 BioAID Doesn’t EZH2 have synonyms?

“ Collaboration through web services” Bio-text mining expert Martijn Schuemie

“ Collaboration through web services” Synonym service

10/06/09 BioAID EZH2 is only a small part of a very complex system, for my research I need more than lists

components... 10/06/09 BioAID

Workflow and semantics When running workflows Store how biological entities are related Combine results from different runs Recover ‘trails to evidence’

Example scenario of semantic approach Need a unique identifyer myModel myExtended Model

“ Collaboration through web services” 2 Bio-text mining expert Martijn Schuemie

getUniprotID Used as unique ID for proteins

10/06/09 BioAID

Proto-ontology (Protégé Jambalaya plugin) 10/06/09 BioAID

Enriched ontology (snapshot) 10/06/09 BioAID

Future

Future plans

Workflows for text mining ‘pipe line’ (BioAID) Named entity recognition Training document Manual annotation Annotated text that provides examples: N x …sentence<concept x > entity </concept x >sentence… Learn Learned model Readable patterns or black box of unreadable conditions: unreadable condition=true => <concept x > entity </concept x > Extract named entities and relations List of named entities

Requirements

Training documents and annotator(s) (or pre-annotated text)

List of concepts to annotate with (possibly from an ontology)

A corpus of interest

‘ Generalise’ examples per concept List of concepts <Concept=name> entity </concept>, frequency, doc ID, … Annotated sentences Training Corpus (e.g. MEDLINE)

Advantages

Concepts of choice

Quality of output under our control

Limitations

Output is limited by initial list of concepts

Substantial amount of manual work (annotation)

Semantic networks

Modelling support Epigenetics (paramutation) Courtesy of Maike Stam Cell division Escherichia coli Courtesy of Tanneke den Blauwen HIV < TF M M M M M M M RDRP RdDM Pol reinforcement repression M M M M M M M TF TF Pol RDRP B'

Reuse and share knowledge MedLine Reuse and share biological knowledge TM

Conclusions

Conclusions and discussion

e-science approach to text mining

myExperiment.org

‘ mySpace’ for computational scientists

Reach out to end-users

Workflow and web services

From ‘black box perl’ to ‘computational experiments’

Share & reuse workflows and knowledge

Grid infrastructure for power users

Conclusions e-Science approach 10/06/09 BioAID Disclose!

e -Science: sharing text mining services

The best service is good a special service is better

Share with users and other developers on text mining network on myExperiment.org

Conclusion e -Science and sharing 10/06/09 BioAID

Why adopt e-science?

Why should I adopt e-Science? I don’t believe in e -Science I believe in Me -Science

Why adopt e-science? For determined sinners: ‘ The seven deadly sins of bioinformatics’ by Carole Goble http://www.slideshare.net/dullhunk/the-seven-deadly-sins-of-bioinformatics/

Acknowledgements

AIDA developers team: Sophia Katrenko, Edgar Meij, Willem van Hage, Frans Verster, (Machiel Jansen), Scott Marshall.

Guus Schreiber, Maarten de Rijke, Pieter Adriaans

Jan Top, Nicole Koenderink, Food informatics, Wageningen University

Martijn Schuemie, Erasmus University Rotterdam

OMII-UK and myGrid team, especially Katy Wolstencroft, Stian Soiland, Stuart Owen, Andy Gibson, Alan Rector, Robert Stevens, Carole Goble

W3C Semantic Web Health Care and Life Sciences Interest Group

Hideaki Sugawara, Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics (http://xml.nig.ac.jp)

This work was supported by the Dutch Ministry of Economic Affairs via VL-e and BioRange (BSIK grants)

10/06/09 BioAID

How does beer relate to BioAID? And how do we relate it to beer?

10/06/09 BioAID

Thank you for your attention… Join the text mining network on myExperiment.org!!! AID information and resources http:// adaptivedisclosure.org W3C Semantic Web Health Care and Life Sciences Interest Group http://www.w3.org/2001/sw/hcls/ BioAID workflows available from http:// .org