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  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 &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; }
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 ,[object Object],[object Object],[object Object],[object Object],[object Object]
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 ,[object Object],[object Object],[object Object],[object Object],[object Object]
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 ,[object Object]
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
10/06/09 BioAID
Proto-ontology  (Protégé Jambalaya plugin) 10/06/09 BioAID
Enriched ontology  (snapshot) 10/06/09 BioAID
Future ,[object Object]
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 ,[object Object],[object Object],[object Object],[object Object],‘ Generalise’ examples per concept List of concepts <Concept=name> entity </concept>, frequency, doc ID, … Annotated sentences Training Corpus (e.g. MEDLINE) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],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 ,[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Conclusions e-Science approach 10/06/09 BioAID Disclose!
[object Object],[object Object],[object Object],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 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],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

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Demo Presentation Wageningen Text Mining Workshop 2007

  • 1. 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
  • 2. About e-Science An e-science approach to mining biomedical literature
  • 3. and beer… And how we relate it to beer…
  • 5. Wet laboratory analogy Data Data handling & Data integration Metadata Data analysis Data storage Expert knowledge
  • 6. General framework of AID for VL-e Middleware for sharing resources Knowledge-based resource management
  • 7. General framework of AID for VL-e Middleware for sharing resources Model based resource management TM TM TM TM TM TM
  • 8. Theme An e-Science approach to mining biomedical literature
  • 9. and beer… And how we relate it to beer…
  • 10. 10/06/09 BioAID Which diseases may be associated with my protein of interest?
  • 11. 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
  • 13. Bioinformatics A typical bioinformatician
  • 14. Bioinformatics A biologist behind a computer who (just) learned perl
  • 15. /* * 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; }
  • 16. Theme No , that is not an e-Science approach to mining biomedical literature
  • 17. Not e-science So 2000 (quoting Lennart Post)
  • 19. Theme An e-Science approach to mining biomedical literature
  • 20.
  • 21. e -Scientists Edgar Meij Information retrieval expert
  • 22. e -Scientists Sophia Katrenko Machine learning (information extraction) expert
  • 23. e -Scientists Willem van Hage Semantic web expert (and bass guitar player)
  • 24. The AIDA toolbox for knowledge extraction and knowledge management in a virtual laboratory for e -Science
  • 25. e -bioscience An e-bioscientist
  • 26. Components of the AIDA toolbox used for Life Science knowledge extraction
  • 27. Bio AID Disease Discovery workflow 10/06/09 BioAID AIDA AIDA OMIM service (Japan) AIDA ‘ Taverna shim’ Taverna ‘shim’
  • 28.
  • 30. 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
  • 31. 10/06/09 BioAID Which diseases may be associated with my protein of interest?
  • 33. Components of the AIDA toolbox used for Life Science knowledge extraction
  • 36. Bio AID Disease discovery workflow
  • 37. Bio AID Disease discovery workflow 10/06/09 BioAID
  • 38. Bio AID Disease discovery workflow from 100 abstracts: 29 proteins associated with 1280 diseases 10/06/09 BioAID
  • 39.
  • 40. 10/06/09 BioAID Doesn’t EZH2 have synonyms?
  • 41. “ Collaboration through web services” Bio-text mining expert Martijn Schuemie
  • 42. “ Collaboration through web services” Synonym service
  • 43. 10/06/09 BioAID EZH2 is only a small part of a very complex system, for my research I need more than lists
  • 45. Workflow and semantics When running workflows Store how biological entities are related Combine results from different runs Recover ‘trails to evidence’
  • 46. Example scenario of semantic approach Need a unique identifyer myModel myExtended Model
  • 47. “ Collaboration through web services” 2 Bio-text mining expert Martijn Schuemie
  • 48. getUniprotID Used as unique ID for proteins
  • 51. Proto-ontology (Protégé Jambalaya plugin) 10/06/09 BioAID
  • 52. Enriched ontology (snapshot) 10/06/09 BioAID
  • 53.
  • 54.
  • 55. 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'
  • 56. Reuse and share knowledge MedLine Reuse and share biological knowledge TM
  • 57.
  • 58.
  • 59.
  • 61. Why should I adopt e-Science? I don’t believe in e -Science I believe in Me -Science
  • 62. 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/
  • 63.
  • 64. How does beer relate to BioAID? And how do we relate it to beer?
  • 66. 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

Notas do Editor

  1. We will demonstrate an e-science approach to mining knowledge from biomedical literature through the application of the ‘Adaptive Information Disclosure Application’ toolbox that we develop in the context of the Dutch Virtual Laboratory e-Science project.