Yearb Med Inform 2009; 18(01): 117-120
DOI: 10.1055/s-0038-1638650
Original Article
Georg Thieme Verlag KG Stuttgart

Accelerating Knowledge Discovery through Community Data Sharing and Integration

Y.L. Yip
1   University of Geneva, Dept. of Structural Biology and Bioinformatics, Geneva, Switzerland
,
Section Editor for the IMIA Yearbook Section on Bioinformatics, Swiss-Prot group, Swiss Institute of Bioinformatics, Geneva, Switzerland › Institutsangaben
Weitere Informationen

Correspondence to

Dr. Yum Lina Yip
Swiss-Prot group
Swiss Institute of Bioinformatics
1 Rue Michel-Servet
CH-1211 Geneva
Switzerland
Telefon: +41 22 379 5049   
Fax: +41 22 379 5858   

Publikationsverlauf

Publikationsdatum:
07. März 2018 (online)

 

Summary

Objectives To summarize current excellent research in the field of bioinformatics.

Method Synopsis of the articles selected for the IMIA Yearbook 2009.

Results The selection process for this yearbook’s section on Bioinformatics results in six excellent articles highlighting several important trends First, it can be noted that Semantic Web technology continues to play an important role in heterogeneous data integration. Novel applications also put more emphasis on its ability to make logical inferences leading to new insights and discoveries.

Second, translational research, due to its complex nature, increasingly relies on collective intelligence made available through the adoption of community-defined protocols or software architectures for secure data annotation, sharing and analysis. Advances in systems biology, bio-ontologies and text-ming can also be noted.

Conclusions Current biomedical research gradually evolves towards an environment characterized by intensive collaboration and more sophisticated knowledge processing activities. Enabling technologies, either Semantic Web or other solutions, are expected to play an increasingly important role in generating new knowledge in the foreseeable future.


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  • References

  • 1 Yip YL. The promise of systems biology in clinical applications. Findings from theYearbook 2008 Section in Bioinformatics. Yearb Med Inform 2008; 102-4.
  • 2 Ruttenberg A, Clark T, Bug W, Samwald M, Bodenreider O, Chen H. et al. Advancing translational research with semantic web. BMC Bioinformatics 2007; 08: S2.
  • 3 Sioutos N, de Coronado S, Haber MW, Hartel FW, Shaiu WL, Wright LW. NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information. J Biomed Inform 2007; 40: 30-43.
  • 4 Baker CJO, Cheung KH. editors. Semantic Web: revolutionizing knowledge discovery in the life sciences. NewYork: Springer; 2007
  • 5 Deus HF, Stanislaus R, Veiga DF, Behrens C, Wistuba II, Minna JD. et al. A semantic web management model for integrative biomedical informatics. PLOS one 2008; 03 (08) e2946.
  • 6 Belleau F, Nolin MA, Tourigny N, Rigault P, Morissette J. Bio2RDF: Towards a mashup to build bioinformatics knowledge systems. J Biomed Inform 2008; 41: 706-16.
  • 7 Splendiani A. RDFScape: Semandtic Web meets Systems Biology. BMC Bioinformatics 2008; 09 (Suppl. 04) S6.
  • 8 Gudivada RC, Qu XA, Chen J, Jegga AG, Neumann EK, Aronow BJ. Identifying disease-causal genes using Semantic Web-based representation of integrated genomic and phenomic knowledge. J Biomed Inform 2008; 41: 717-29.
  • 9 Oster S, Langella S, Hastings S, Ervin D, Madduri R, Kurc T. et al. caGrid 1.0: a grid enterprise architecture for cancer research. AMIA Annual Symposium Proceedings 2007; 573-7.
  • 10 Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42 (02) 377-81 Epub 2008 Sep 30.
  • 11 Jenkinson AM, Albrecht M, Birney E, Blankenburg H, Down T, Finn RD. et al. Integrating biological data – the Distributed Annotation System. BMC Bioinformatics 2008; 09 (Suppl. 08) S3.
  • 12 Amin W, Parwani AV, Schmandt L, Mohanty SK, Farhat G, Pople AK. et al. National Mesothelioma Virtual Bank: A standard based biospecimen and clinical data resource to enhance translational research. BMC Cancer 2008; 08: 236.
  • 13 Sabb FW, Bearden CE, Glahn DC, Parker DS, Freimer N, Bilder RM. A collaborative knowledge base for cognitive phenomics. Mol Psychiatry 2008; 13: 350-60.
  • 14 Homer N, Szelinger S, Redman M, Duggan D, Tembe W, Muehling J. et al. Resolving individual contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotype microarrays. PLOS Genet 2008; 04 (08) e1000167.
  • 15 Voelkerding KV, Dames SA, Durtschi JD. Next generation sequencing: from basic research to diagnostics. Clin Chem 2009; 55 (04) 641-58.
  • 16 Kim PS, Lee PP, Levy D. Dynamics and potential impact of the immune response to chronic myelogenous leukemia. PLOS Comput Biol 2008; 04 (06) e1000095.
  • 17 Banaji M, Mallet A, Elwell CD, Nicholls P, Cooper CE. A model of brain circulation and metabolism: NIRS signal changes during physiological challenges. PLOS computational Biology 2008; 04 (11) e1000212.
  • 18 Viti F, Merelli I, Caprera A, Lazzari B, Stella A, Milanesi L. Ontology-based, tissue microarray oriented, image centered tissue bank. BMC Bioinformatics 2008; 09 (Suppl. 04) S4.
  • 19 Coulet A, Smäil-Tabbone M, Benlian P, Napoli A, Devignes MD. Ontology-guided data preparation for discovering genotype-phenotype relationships. BMC Bioinformatics 2008; 09 (Suppl. 04) S3.
  • 20 Robinson PN, Köhler S, Bauer S, Seelow D, Horn D, Mundlos S. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet 2008; 83 (05) 610-15.
  • 21 Theodosiou T, Angelis L, Vakali A. Non-linear correlation of content and metadata information extracted from biomedical information extracted from biomedical article datasets. J Biomed Inform 2008; 41: 202-16.
  • 22 Roberts A, Gaizaukas R, Hepple M, Guo Y. Mining clinical relationships from patient narratives. BMC Bioinformatics 2008; 09 (Suppl. 11) S3.
  • 23 Lang E. Bioinformatics and its Impact on Clinical Research Methods. Methods Inf Med 2006; 45: 104-6.
  • 24 Lang E. Integrating bioinformatics into clinical practice: progress and evaluation. Methods Inf Med 2007; 46: 106-8.

Correspondence to

Dr. Yum Lina Yip
Swiss-Prot group
Swiss Institute of Bioinformatics
1 Rue Michel-Servet
CH-1211 Geneva
Switzerland
Telefon: +41 22 379 5049   
Fax: +41 22 379 5858   

  • References

  • 1 Yip YL. The promise of systems biology in clinical applications. Findings from theYearbook 2008 Section in Bioinformatics. Yearb Med Inform 2008; 102-4.
  • 2 Ruttenberg A, Clark T, Bug W, Samwald M, Bodenreider O, Chen H. et al. Advancing translational research with semantic web. BMC Bioinformatics 2007; 08: S2.
  • 3 Sioutos N, de Coronado S, Haber MW, Hartel FW, Shaiu WL, Wright LW. NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information. J Biomed Inform 2007; 40: 30-43.
  • 4 Baker CJO, Cheung KH. editors. Semantic Web: revolutionizing knowledge discovery in the life sciences. NewYork: Springer; 2007
  • 5 Deus HF, Stanislaus R, Veiga DF, Behrens C, Wistuba II, Minna JD. et al. A semantic web management model for integrative biomedical informatics. PLOS one 2008; 03 (08) e2946.
  • 6 Belleau F, Nolin MA, Tourigny N, Rigault P, Morissette J. Bio2RDF: Towards a mashup to build bioinformatics knowledge systems. J Biomed Inform 2008; 41: 706-16.
  • 7 Splendiani A. RDFScape: Semandtic Web meets Systems Biology. BMC Bioinformatics 2008; 09 (Suppl. 04) S6.
  • 8 Gudivada RC, Qu XA, Chen J, Jegga AG, Neumann EK, Aronow BJ. Identifying disease-causal genes using Semantic Web-based representation of integrated genomic and phenomic knowledge. J Biomed Inform 2008; 41: 717-29.
  • 9 Oster S, Langella S, Hastings S, Ervin D, Madduri R, Kurc T. et al. caGrid 1.0: a grid enterprise architecture for cancer research. AMIA Annual Symposium Proceedings 2007; 573-7.
  • 10 Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42 (02) 377-81 Epub 2008 Sep 30.
  • 11 Jenkinson AM, Albrecht M, Birney E, Blankenburg H, Down T, Finn RD. et al. Integrating biological data – the Distributed Annotation System. BMC Bioinformatics 2008; 09 (Suppl. 08) S3.
  • 12 Amin W, Parwani AV, Schmandt L, Mohanty SK, Farhat G, Pople AK. et al. National Mesothelioma Virtual Bank: A standard based biospecimen and clinical data resource to enhance translational research. BMC Cancer 2008; 08: 236.
  • 13 Sabb FW, Bearden CE, Glahn DC, Parker DS, Freimer N, Bilder RM. A collaborative knowledge base for cognitive phenomics. Mol Psychiatry 2008; 13: 350-60.
  • 14 Homer N, Szelinger S, Redman M, Duggan D, Tembe W, Muehling J. et al. Resolving individual contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotype microarrays. PLOS Genet 2008; 04 (08) e1000167.
  • 15 Voelkerding KV, Dames SA, Durtschi JD. Next generation sequencing: from basic research to diagnostics. Clin Chem 2009; 55 (04) 641-58.
  • 16 Kim PS, Lee PP, Levy D. Dynamics and potential impact of the immune response to chronic myelogenous leukemia. PLOS Comput Biol 2008; 04 (06) e1000095.
  • 17 Banaji M, Mallet A, Elwell CD, Nicholls P, Cooper CE. A model of brain circulation and metabolism: NIRS signal changes during physiological challenges. PLOS computational Biology 2008; 04 (11) e1000212.
  • 18 Viti F, Merelli I, Caprera A, Lazzari B, Stella A, Milanesi L. Ontology-based, tissue microarray oriented, image centered tissue bank. BMC Bioinformatics 2008; 09 (Suppl. 04) S4.
  • 19 Coulet A, Smäil-Tabbone M, Benlian P, Napoli A, Devignes MD. Ontology-guided data preparation for discovering genotype-phenotype relationships. BMC Bioinformatics 2008; 09 (Suppl. 04) S3.
  • 20 Robinson PN, Köhler S, Bauer S, Seelow D, Horn D, Mundlos S. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet 2008; 83 (05) 610-15.
  • 21 Theodosiou T, Angelis L, Vakali A. Non-linear correlation of content and metadata information extracted from biomedical information extracted from biomedical article datasets. J Biomed Inform 2008; 41: 202-16.
  • 22 Roberts A, Gaizaukas R, Hepple M, Guo Y. Mining clinical relationships from patient narratives. BMC Bioinformatics 2008; 09 (Suppl. 11) S3.
  • 23 Lang E. Bioinformatics and its Impact on Clinical Research Methods. Methods Inf Med 2006; 45: 104-6.
  • 24 Lang E. Integrating bioinformatics into clinical practice: progress and evaluation. Methods Inf Med 2007; 46: 106-8.