Hidden Markov models and neural networks
Part 4. Bioinformatics
4.8. Modern Programming Paradigms in Biology
Published Online: 15 JAN 2005
Copyright © 2005 John Wiley & Sons, Ltd
Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics
How to Cite
Kremer, S. C. and Baldi, P. 2005. Hidden Markov models and neural networks. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.8:98.
- Published Online: 15 JAN 2005
In this contribution, we discuss the application of machine learning methods, particularly hidden Markov models and artificial neural networks, to bioinformatics tasks. We begin with a brief summary of the two paradigms as computational and learning systems and describe the nature of the problems to which these two approaches can be applied. Then, we give some examples of their application to bioinformatics, briefly discuss the strengths and weaknesses of these two approaches, and provide some avenues for further reading.
- hidden Markov models;
- neural networks;
- machine learning