Machine Learning in Bioinformatics

Jyotsna Talreja Wassan, Haiying / HY Wang, Huiru Zheng

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Machine Learning (ML) is an adaptive process of interpreting information from real-world data sets, by making use of computers that learn from experiences. Bioinformatics is emerging as an interdisciplinary science of interpreting biological data using such adaptive computational procedures. This article provides an overview on the ML tools and techniques, which are useful in bioinformatics and computational biology.
Original languageEnglish
Title of host publicationEncyclopedia of Bioinformatics and Computational Biology
EditorsShoba Ranganathan, Michael Gribskov, Kenta Nakai, Christian Schönbach
PublisherElsevier
Pages300-308
Number of pages9
Volume1
ISBN (Electronic)9780128114148
ISBN (Print)9780128114322
DOIs
Publication statusPublished - 6 Sep 2018

Keywords

  • Classification
  • Clustering
  • Deep Learning
  • reinforcement learning
  • Semi-supervised learning
  • supervised learning
  • Unsupervised Learning

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  • Cite this

    Wassan, J. T., Wang, H. . HY., & Zheng, H. (2018). Machine Learning in Bioinformatics. In S. Ranganathan, M. Gribskov, K. Nakai, & C. Schönbach (Eds.), Encyclopedia of Bioinformatics and Computational Biology (Vol. 1, pp. 300-308). Elsevier. https://doi.org/10.1016/B978-0-12-809633-8.20331-2