Skip to main content
SpringerLink
Log in

Machine Learning in Computational Biology

  • Reference work entry
  • First Online:
Book cover Encyclopedia of Database Systems

  • 87 Accesses

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 4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 6,499.99
Price excludes VAT (USA)
  • Durable hardcover 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

Recommended Reading

  1. Andorf C, Dobbs D, Honavar V. Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach. BMC Bioinform. 2007;8(1):284.

    Article  Google Scholar 

  2. 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. Nat Gene. 2000;25(1):25–9.

    Article  Google Scholar 

  3. Baldi P, Brunak S. Bioinformatics: the machine learning approach. Cambridge, MA: MIT; 2001.

    MATH  Google Scholar 

  4. Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. Genbank. Nucleic Acids Res. 2007;35D(Database issue):21–D25.

    Article  Google Scholar 

  5. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The protein data bank. Nucleic Acids Res. 2000;28(1):235–42.

    Article  Google Scholar 

  6. Bishop CM. Pattern recognition and machine learning. Berlin: Springer; 2006.

    MATH  Google Scholar 

  7. Boutell MR, Luo J, Shen X, Brown CM. Learning multi-label scene classification. Pattern Recogn. 2004;37(9):1757–71.

    Article  Google Scholar 

  8. Bruggeman FJ, Westerhoff HV. The nature of systems biology. Trends Microbiol. 2007;15(1):15–50.

    Article  Google Scholar 

  9. Caragea C, Sinapov J, Dobbs D, and Honavar V. Assessing the performance of macromolecular sequence classifiers. In: Proceedings of the IEEE 7th International Symposium on Bioinformatics and Bioengineering; 2007. p. 320–6.

    Google Scholar 

  10. de Jong H. Modeling and simulation of genetic regulatory systems: a literature review. J Comput Biol. 2002;9(1):67–103.

    Article  Google Scholar 

  11. Diettrich TG. Ensemble methods in machine learning. Springer, Berlin. In: Proceedings of the 1st International Workshop on Multiple Classifier Systems; 2000. p. 1–15.

    Google Scholar 

  12. Diettrich TG. Machine learning for sequential data: a review. In: Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition; 2002. p. 15–30.

    Google Scholar 

  13. El-Manzalawy Y, Dobbs D, Honavar V. On evaluating MHC-II binding peptide prediction methods. PLoS One. 2008;3(9):e3268.

    Article  Google Scholar 

  14. El-Manzalawy Y., Dobbs D., Honavar V. Predicting linear B-cell epitopes using string kernels. J Mole Recogn. 2008; 21(4):243–255.

    Article  Google Scholar 

  15. Friedman N, Linial M, Nachman I, Pe’er D. Using bayesian networks to analyze expression data. J Comput Biol. 2000;7(3–4):601–20.

    Article  Google Scholar 

  16. Galperin MY. The molecular biology database collection: 2008 update. Nucleic Acids Res. 2008;36(Database issue):D2–4.

    Article  Google Scholar 

  17. Guyon I, Elisseeff A. An introduction to variable and feature selection. J Mach Learn Res. 2003;3(7–8):1157–82.

    MATH  Google Scholar 

  18. Hecker L, Alcon T, Honavar V, Greenlee H. Querying multiple large-scale gene expression datasets from the developing retina using a seed network to prioritize experimental targets. Bioinform Biol Insights. 2008;2:91–102.

    Article  Google Scholar 

  19. Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi A-L. The large-scale organization of metabolic networks. Nature. 1987;407(6804):651–4.

    Article  Google Scholar 

  20. Lahdesmaki H, Shmulevich I, Yli-Harja O. On learning gene regulatory networks under the boolean network model. Mach Learn. 2007;52(1–2):147–67.

    MATH  Google Scholar 

  21. Terribilini M, Lee J-H, Yan C, Jernigan RL, Honavar V, Dobbs D. Predicting RNA-binding sites from amino acid sequence. RNA J. 2006;12(8):1450–62.

    Article  Google Scholar 

  22. Yan C, Terribilini M, Wu F, Jernigan RL, Dobbs D, Honavar V. Predicting DNA-binding sites of proteins from amino acid sequence. BMC Bioinform. 2006;7:262.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science and Engineering, University of North Texas, Denton, TX, USA

    Cornelia Caragea

  2. Iowa State University, Ames, IA, USA

    Vasant Honavar

Authors
  1. Cornelia Caragea
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vasant Honavar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cornelia Caragea .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Robert H. Smith School of Business, University of Maryland, College Park, MD, USA

    Louiqa Raschid

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Caragea, C., Honavar, V. (2018). Machine Learning in Computational Biology. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_636

Download citation

Publish with us

Policies and ethics

Search

Navigation