A PAL’s life About a biologist in e-science Presentation for the OMII-UK Board, Southampton, May 16, 2008

My experience in e- bio science My experience in e- bio science Marco Roos Biologist and bioinformatician Post-doc e-(bio)science, University of Amsterdam PAL OMII-UK Member BioAssist steering group

Marco Roos

Biologist and bioinformatician

Post-doc e-(bio)science, University of Amsterdam

PAL OMII-UK

Member BioAssist steering group

to here

Biological motivation: F unction and architecture of DNA in the cell Escherichia coli Mouse fibroblast (skin) cells

Many components... 10/06/09 BioAID

Example: bioinformatics before e-science Human Transcriptome Map (HTM) (Versteeg et al. , Genome Research, 2003) Sage tag count (TU, Sage library) TU identifier position Transcriptional Unit (TU)

Before e-science HTM construction and RIDGE detection /* * determines ridges in htm expression table */ #include &quot;ridge.h&quot; int selecthtm(PGconn *conn, char *htmtablename, char *chromname, PGresult *htmtable) { char querystring[256]; sprintf(&quot;SELECT * FROM %s WHERE chrom = %s ORDER BY genstart&quot;, 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, &quot;movmed39expr&quot;)) < 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(&quot;dbname=htm port=6400 user=mroos password=geheim&quot;); if (PQstatus(conn)==CONNECTION_BAD) { fprintf(stderr, &quot;connection to database failed.
&quot;); fprintf(stderr, &quot;%s&quot;, PQerrorMessage(conn)); exit(1); } else printf(&quot;Connection ok
&quot;); sprintf(querystring, &quot;SELECT * FROM chromosomes&quot;); printf(&quot;%s
&quot;, 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(&quot;%d, &quot;, i); printf(&quot;%s
&quot;, PQgetvalue(tuples,i,0)); } return TRUE; } int validquery(PGresult *result, char *querystring) { printf(&quot; in validquery
&quot;); if (PQresultStatus(result) != PGRES_TUPLES_OK) { printf(&quot;Query %s failed.
&quot;, querystring); fprintf(stderr, &quot;Query %s failed.
&quot;, querystring); return FALSE; } return TRUE; } IT used Perl PostgresSQL C MS Excel + VBA SPSS No predefined development strategy No design phase Data Data Data Data Data Data

Bioinformatics A typical bioinformatician

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

The ‘spaghetti’ approach

Before e-science Conclusion State of the art in computing in life science is of the 1980s (gross simplification)

Conclusion

State of the art in computing in life science is of the 1980s

(gross simplification)

e-science e-science motivation Enhance the state of the art of computing in life science and bioinformatics

e-science motivation

Enhance the state of the art of computing in life science and bioinformatics

Example An e-science approach to text mining

Biological knowledge extraction 10/06/09 BioAID Biological question/model Computational experiment Extracted knowledge I want to do it my way Carole Goble’s me -scientist >17 million citations +400,000/yr

10/06/09 BioAID Which diseases may be associated with my protein of interest EZH2

Combining expertise Edgar Meij Information retrieval expert

Combining expertise Sophia Katrenko Machine learning expert

Combining expertise Willem van Hage Semantic web expert (and bass guitar player)

Combining expertise Towards a knowledge framework Computer scientist and bioinformatician Scott Marshall

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

Combining web services

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

“ Collaboration through web services” Biological Database expert Hideaki Sugawara

“ Collaboration through web services” e -bioscientist

A nice tool

A not so nice tool

10/06/09 BioAID

Sharing

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

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

Summary so far Application of myExperiment Application of Taverna Application of web services Reuse of components from a text mining tool Reuse of AIDA services in resource management tools (not shown) Application of semantic web (not shown)

Application of myExperiment

Application of Taverna

Application of web services

Reuse of components from a text mining tool

Reuse of AIDA services in resource management tools (not shown)

Application of semantic web (not shown)

Summary so far Workflow enhance insight and reproducibility Workflow as ‘computational experiment’ Feedback and development Workflow enhances application of expertise Components built by diverse experts Collaboration through web services Text mining experiment by non text mining expert

Workflow enhance insight and reproducibility

Workflow as ‘computational experiment’

Feedback and development

Workflow enhances application of expertise

Components built by diverse experts

Collaboration through web services

Text mining experiment by non text mining expert

e -Science is about people 10/06/09 BioAID Want this…

e -Science is about people 10/06/09 BioAID … need this

Outreach Successful as ‘schoolbook’ example of e-science approach VL-e mid-term review (‘e-science that works’) 3x NBIC Bioinformatics symposium Text mining workshop Web services/workflow tutorial ICT delta and eChallenges ISMB/ECCB2007 Vienna 2x OMII-UK workshops Attracts bioinformaticians to e-science Example: NBIC/BioAssist

Successful as ‘schoolbook’ example of e-science approach

VL-e mid-term review (‘e-science that works’)

3x NBIC

Bioinformatics symposium

Text mining workshop

Web services/workflow tutorial

ICT delta and eChallenges

ISMB/ECCB2007 Vienna

2x OMII-UK workshops

Attracts bioinformaticians to e-science

Example: NBIC/BioAssist

BioAssist National bioinformatics support programme Now based on e-science Taverna as target platform 5 (power)user communities (‘PAL’s pals’): Integrated analysis of functional genomics data Proteomics data management and analysis Metabolomics data management and analysis Biobanking High throughput sequencing System bioinformatics Grid and super computing support from SARA Collaboration with OMII-UK/myGrid for linking computing resources with Taverna for transparent processing of large datasets

National bioinformatics support programme

Now based on e-science

Taverna as target platform

5 (power)user communities (‘PAL’s pals’):

Integrated analysis of functional genomics data

Proteomics data management and analysis

Metabolomics data management and analysis

Biobanking

High throughput sequencing

System bioinformatics

Grid and super computing support from SARA

Collaboration with OMII-UK/myGrid for linking computing resources with Taverna for transparent processing of large datasets

BioAssist as test-bed community Life science/bioinformatics requirements Taverna Large data processing in Taverna Running workflows without Taverna help bioinformaticians help biologists Web service repository (e.g. BioCatalogue) Potential ‘companion’ tools for OMII-UK toolset MolGenis for local data vBrowser for browsing resources e.g. workflow results and data on grids Collaborative effort to address requirements Sharing code

Life science/bioinformatics requirements

Taverna

Large data processing in Taverna

Running workflows without Taverna help bioinformaticians help biologists

Web service repository (e.g. BioCatalogue)

Potential ‘companion’ tools for OMII-UK toolset

MolGenis for local data

vBrowser for browsing resources e.g. workflow results and data on grids

Collaborative effort to address requirements

Sharing code

PAL’s future Is this PAL satisfied? Not yet! Uptake by bioinformatics: going well Uptake by systems biology: progress Uptake by life science: early days

Is this PAL satisfied? Not yet!

Uptake by bioinformatics: going well

Uptake by systems biology: progress

Uptake by life science: early days

Full circle a biological question… 10/06/09 BioAID Could be running on a Grid or cluster

10/06/09 BioAID Thank you for sending me this e -Experiment from myExperiment.org!

Experiences and conclusions VL-e, AID and OMII-UK have helped me reach out to the bioinformatics and life science communities (Hopefully) I was helpful in getting the e-science of VL-e, AID, and OMII-UK across to the bioinformatics and life science community Collaborative spirit and win-win unfamiliar for me-scientists Dissemination requires a lot of time and energy

VL-e, AID and OMII-UK have helped me reach out to the bioinformatics and life science communities

(Hopefully) I was helpful in getting the e-science of VL-e, AID, and OMII-UK across to the bioinformatics and life science community

Collaborative spirit and win-win unfamiliar for me-scientists

Dissemination requires a lot of time and energy

Experiences and conclusions OMII-UK and its members prove the concept of e-science accomplish the hugely complicated task of being successful from core computer science to application science and back (imho the essence of e-science research) Why? (my view) Strong positive leadership Successful approach, acknowledging social aspects Large enough community OMII-UK role model for e-science & organisations adopting e-science e-science (user) community needs a role model for some time to come

OMII-UK and its members prove the concept of e-science

accomplish the hugely complicated task of being successful from core computer science to application science and back (imho the essence of e-science research)

Why? (my view)

Strong positive leadership

Successful approach, acknowledging social aspects

Large enough community

OMII-UK role model for e-science & organisations adopting e-science

e-science (user) community needs a role model for some time to come

Acknowledgements AID team: Sophia Katrenko, Edgar Meij, Willem van Hage ,…, Frans Verster, Machiel Jansen , Scott Marshall and Guus Schreiber, Maarten de Rijke, Pieter Adriaans Jan Top, Nicole Koenderink, Food informatics, Wageningen University Martijn Schuemie, Erasmus University Rotterdam Hideaki Sugawara, Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics (http://xml.nig.ac.jp) OMII-UK and the myGrid family, Katy Wolstencroft E-science support team for NBIC VL-e colleagues The Netherlands BioInformatics Centre (NBIC) W3C Semantic Web Health Care and Life Sciences Interest Group iCapture team in Canada My friends on myExperiment This work was supported by the Dutch Ministry of Economic Affairs via VL-e and BioRange (BSIK grants), and OMII-UK 10/06/09

AID team: Sophia Katrenko, Edgar Meij, Willem van Hage ,…, Frans Verster, Machiel Jansen , Scott Marshall and Guus Schreiber, Maarten de Rijke, Pieter Adriaans

Jan Top, Nicole Koenderink, Food informatics, Wageningen University

Martijn Schuemie, Erasmus University Rotterdam

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

OMII-UK and the myGrid family, Katy Wolstencroft

E-science support team for NBIC

VL-e colleagues

The Netherlands BioInformatics Centre (NBIC)

W3C Semantic Web Health Care and Life Sciences Interest Group

iCapture team in Canada

My friends on myExperiment

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

A hopefully mutually felt: warm and fuzzy feeling! Thank you for your attention

Why should I adopt e-Science? I do not believe in e -Science I only 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/