Skip to main content
SpringerLink
Log in

Web Resources for Gene List Analysis in Biomedicine

  • Chapter
Web-Based Applications in Healthcare and Biomedicine

Part of the book series: Annals of Information Systems ((AOIS,volume 7))

Abstract

This chapter mainly focuses on the technological and information resources presently available through the web to functionally evaluate lists of genes. It first presents the current biotechnologynanotechnology and molecular biology scenario of the massive production of promising heterogeneous experimental data that need to be evaluated to light new insights on the cellular biomolecular processes and contribute to advances in health care and biomedicine. Then, it describes the technologies to manage, share and computationally use the valuable information and knowledge available in the biomedical and biomolecular domain, and presents the main bio-terminologies and bio-ontologies used to annotate genes and gene products in order to describe their known structural, functional and phenotypic features. Then, it illustrates the main computational analysis techniques that can be used to extract relevant information out of gene and protein annotation profiles, focusing on annotation enrichment analysis and functional similarity metrics. Finally, the chapter presents the resources available online to access existing biomolecular controlled annotations and extract new biomedical knowledge through their analysis, focusing on two representative and well-known web tools. The concise perspective of the field and the selected resources presented help interested readers in quickly understanding the main principles of knowledge representation and analysis in biomedicine and their high relevance for modern biomedical research and e-health.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Stevens R, Goble CA, Bechhofer S. Ontology-based knowledge representation for bioinformatics. Brief Bioinform 2000;1(4):398–416.

    Article  CAS  PubMed  Google Scholar 

  2. Hill DP, Blake JA, Richardson JE, Ringwald M. Extension and integration of the Gene Ontology (GO): Combining GO vocabularies with external vocabularies. Genome Res 2002;12(12):1982–1991.

    Article  CAS  PubMed  Google Scholar 

  3. Hennig S, Groth D, Lehrach H. Automated Gene Ontology annotation for anonymous sequence data. Nucleic Acids Res 2003;31(13):3712–3715.

    Article  CAS  PubMed  Google Scholar 

  4. Bodenreider O, Stevens R. Bio-ontologies: Current trends and future directions. Brief Bioinform 2006;7(3):256–274.

    Article  CAS  PubMed  Google Scholar 

  5. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M. From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Res 2006;34(Database issue):D354–D357.

    Article  CAS  PubMed  Google Scholar 

  6. Finn RD, Mistry J, Schuster-Bockler B, Griffiths-Jones S, Hollich V, Lassmann T, Moxon S, Marshall M, Khanna A, Durbin R, Eddy SR, Sonnhammer EL, Bateman A. Pfam: Clans, web tools and services. Nucleic Acids Res 2006;34(Database issue):D247–D251.

    Article  CAS  PubMed  Google Scholar 

  7. McKusick VA. Mendelian Inheritance in Man and its online version, OMIM Am J Hum Genet 2007;80(4):588–604.

    Article  CAS  Google Scholar 

  8. Hamosh A, Scott AF, Amberger JS, Bocchini CA, McKusick VA. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 2005;33(Database issue):D514–D517.

    Article  CAS  PubMed  Google Scholar 

  9. Kelso J, Visagie J, Theiler G, Christoffels A, Bardien S, Smedley D, Otgaar D, Greyling G, Jongeneel CV, McCarthy MI, Hide T, Hide W. eVOC: A controlled vocabulary for unifying gene expression data. Genome Res 2003;13(6A):1222–1230.

    Article  CAS  PubMed  Google Scholar 

  10. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology: Tool for the unification of biology. The gene ontology consortium. Nat Genet 2000;25(1):25–29.

    Article  CAS  PubMed  Google Scholar 

  11. Rubin DL, Lewis SE, Mungall CJ, Misra S, Westerfield M, Ashburner M, Sim I, Chute CG, Solbrig H, Storey MA, Smith B, Day-Richter J, Noy NF, Musen MA. National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge. OMICS 2006;10(2):185–198.

    Article  CAS  PubMed  Google Scholar 

  12. Rivals I, Personnaz L, Taing L, Potier MC. Enrichment or depletion of a GO category within a class of genes: Which test? Bioinformatics 2007;23(4):401–407.

    Article  CAS  PubMed  Google Scholar 

  13. Shaffer JP. Multiple hypothesis testing. Ann Rev Psych 1995;46:561–584.

    Article  Google Scholar 

  14. Holm S. A simple sequentially rejective Bonferroni test procedure. Scand Stat 1979;6:65–70.

    Google Scholar 

  15. Westfall PH, Young SS. Resampling-based multiple testing. New York: Wiley, 1993.

    Google Scholar 

  16. Benjamini Y, Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995;57:289–300.

    Google Scholar 

  17. Grossmann S, Bauer S, Robinson PN, Vingron M. Improved detection of overrepresentation of Gene Ontology annotations with parent-child analysis. Bioinformatics 2007;23(22):3024–3031.

    Article  CAS  PubMed  Google Scholar 

  18. Alexa A, Rahnenfuhrer J, Lengauer T. Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 2006;22(13):1600–1607.

    Article  CAS  PubMed  Google Scholar 

  19. Günther CC, Langaas M, Lydersen S. Statistical hypothesis testing of association between two lists of genes. Tech Report Preprint Statistics, 1/2006, Department of Mathematical Sciences, NTNU. http://www.math.ntnu.no/preprint/statistics/2006/. Accessed 27 March 2009.

  20. Resnik P. Using information content to evaluate semantic similarity in a taxonomy. In: Proceedings of the 14th international joint conference on Artificial Intelligence, IJCAI 95, Montreal, Québec, Canada, 1995:448–453.

    Google Scholar 

  21. Zhong J, Zhu H, Li Y, Yu Y. Lecture Notes In Computer Science; Vol. 2393, In: Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces, Springer, London, 2002:92–106.

    Google Scholar 

  22. Barutcuoglu Z, Schapire RE, Troyanskaya OG. Hierarchical multi-label prediction of gene function. Bioinformatics 2006;22(7):830–836.

    Article  CAS  PubMed  Google Scholar 

  23. Lin D. An information-theoretic definition of similarity. In: Proceedings of 15th international conference on machine learning, San Francisco, CA, USA, 2000:296–304.

    Google Scholar 

  24. Jiang JJ, Conrath DW. Semantic similarity based on corpus statistics and lexical taxonomy. In: Proceedings of international conference on research in Computational Linguistics, Taiwan, ROC, 1998:19–33.

    Google Scholar 

  25. Lord PW, Stevens RD, Brass A, Goble CA. Semantic similarity measures as tools for exploring the Gene Ontology. Pac Symp Biocomput 2003;8:601–612.

    Google Scholar 

  26. Speer N, Spieth C, Zell A. A memetic clustering algorithm for the functional partition of genes based on the Gene Ontology. In: Proceedings of the 2004 IEEE symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2004), La Jolla, CA, USA. San Diego, CA: IEEE Press, 2004:252–259.

    Google Scholar 

  27. Schlicker A, Domingues F, Rahnenführer J, Lengauer T. A new measure for functional similarity of gene products based on Gene Ontology. BMC Bioinf 2006;7(302):1–16.

    Google Scholar 

  28. Tao Y, Sam L, Li J, Friedman C, Lussier YA. Information theory applied to the sparse gene ontology annotation network to predict novel gene function. Bioinformatics 2007;23(13):529–538.

    Article  Google Scholar 

  29. Masseroli M, Pinciroli F. (2006) Using Gene Ontology and genomic controlled vocabularies to analyze high-throughput gene lists: Three tool comparison. Comput Biol Med 2006;36(7–8):731–747.

    Article  CAS  Google Scholar 

  30. Kasprzyk A, Keefe D, Smedley D, London D, Spooner W, Melsopp C, Hammond M, Rocca-Serra P, Cox T, Birney E. EnsMart: A generic system for fast and flexible access to biological data. Genome Res 2004;14(1):160–169.

    Article  CAS  PubMed  Google Scholar 

  31. Bussey KJ, Kane D, Sunshine M, Narasimhan S, Nishizuka S, Reinhold WC, Zeeberg B, Ajay W, Weinstein JN. MatchMiner: A tool for batch navigation among gene and gene product identifiers. Genome Biol 2003;4(4):R27, 1–7.

    Article  Google Scholar 

  32. Zhong S, Storch KF, Lipan O, Kao MC, Weitz CJ, Wong WH. GoSurfer: A graphical interactive tool for comparative analysis of large gene sets in Gene Ontology trade mark space. Appl Bioinf 2004;3(4):261–264.

    Article  CAS  Google Scholar 

  33. Doniger SW, Salomonis N, Dahlquist KD, Vranizan K, Lawlor SC, Conklin BR. MAPPFinder: Using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biol 2003;4(1):R7, 1–12.

    Article  Google Scholar 

  34. Cavalieri D, De Filippo C, Grosu P, Biggeri A. Making sense of whole genome expression data. Application of a universal DNA microarray to cyanobacterial diversity assessment. Minerva Biotecnol 2002;14:291–304.

    Google Scholar 

  35. Masseroli M, Martucci D, Pinciroli F. GFINDer: Genome Function INtegrated Discoverer through dynamic annotation, statistical analysis, and mining. Nucleic Acids Res 2004;32(Web Server issue):W293–W300.

    Article  CAS  PubMed  Google Scholar 

  36. Masseroli M, Galati O, Pinciroli F. GFINDer: Genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists. Nucleic Acids Res 2005;33(Web Server issue):W717–W723.

    Article  CAS  PubMed  Google Scholar 

  37. Masseroli M, Bellistri E, Franceschini A, Pinciroli F. Statistical analysis of genomic protein family and domain controlled annotations for functional investigation of classified gene lists. BMC Bioinf 2007;8(Suppl 1):S14, 1–10.

    Article  Google Scholar 

  38. Sherman BT, Huang DW, Tan Q, Guo Y, Bour S, Liu D, Stephens R, Baseler MW, Lane HC, Lempicki RA. DAVID Knowledgebase: A gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis. BMC Bioinf 8(426):1–11.

    Google Scholar 

  39. Huang DW, Sherman BT, Tan Q, Kir J, Liu D, Bryant D, Guo Y, Stephens R, Baseler MW, Lane HC, Lempicki RA. DAVID Bioinformatics Resources: Expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res 2007;35(Web Server issue):W169–W175.

    Article  Google Scholar 

  40. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nat Protoc 2009:4(1):44–57.

    Article  CAS  Google Scholar 

  41. Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. InterPro: The integrative protein signature database. Nucleic Acids Res 2009;37(Database issue):D211–D215.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milan, Italy

    Marco Masseroli & Marco Tagliasacchi

Authors
  1. Marco Masseroli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marco Tagliasacchi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marco Masseroli .

Editor information

Editors and Affiliations

  1. Department of Nursing, University of Peloponnese, 231 00, Sparta General Hospital Bldg., Sparta, Greece

    Athina Lazakidou

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Masseroli, M., Tagliasacchi, M. (2010). Web Resources for Gene List Analysis in Biomedicine. In: Lazakidou, A. (eds) Web-Based Applications in Healthcare and Biomedicine. Annals of Information Systems, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1274-9_8

Download citation

Publish with us

Policies and ethics

Search

Navigation