Information-theoretic algorithms in bioinformatics and bio-/medical-imaging: A review

Author

Neelakanta, Perambur ; Chatterjee, Sharmistha ; Pappusetty, Deepti ; Pavlovic, Mirjana ; Pandya, Abhijit

Author_Institution

Dept. of Comput. & Electr. Eng. & Comput. Sci., Florida Atlantic Univ., Boca Raton, FL, USA

fYear

2011

fDate

3-5 June 2011

Firstpage

183

Lastpage

188

Abstract

Information-theoretic notion of entropy (in Shannon sense) is a versatile avenue in analyzing bioinformatic details as well as in mining data pertinent to molecular biology. Also, the informatics of bio- and medical-imaging can be comprehended via entropy considerations. Presented in this paper is a comprehensive review on salient methods, newer techniques and open-questions on unexplored efforts vis-à-vis the entropy principles cast on bioinformatic computations and bio-/medical-image informatics. Supplementing energetics algorithms are indicated.

Keywords

bioinformatics; data mining; medical image processing; bioinformatics; biomedical imaging; data mining; entropy principles; information theoretic algorithm; information theoretic notion; molecular biology; Bioinformatics; Biomedical imaging; DNA; Entropy; Genomics; Proteins; Information-theoretics; bio-/medical-imaging; bioinformatics; energetics; entropy; microbiology;

fLanguage

English

Publisher

ieee

Conference_Titel

Recent Trends in Information Technology (ICRTIT), 2011 International Conference on

Conference_Location

Chennai, Tamil Nadu

Print_ISBN

978-1-4577-0588-5

Type

conf

DOI

10.1109/ICRTIT.2011.5972249

Filename

5972249