- Title
- Pattern recognition in bioinformatics : Girls lose out
- Creator
- Ahmad, Shandar; Chetty, Madhu; Schmidt, Bertil
- Date
- 2010
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/63174
- Identifier
- vital:5940
- Identifier
-
https://doi.org/10.1016/j.patrec.2010.06.001
- Identifier
- ISSN:0167-8655
- Abstract
- Editorial- With the advent of high speed computers, in-silico studies on biological patterns in recent years have been significantly impacted by the pattern recognition techniques. In this special issue, ‘Pattern Recognition in Bioinformatics’, we present various sophisticated algorithms for a wide range of pattern recognition problems from the world of complex biological systems, whether these are specific sequence signatures – motifs that stand out in discovering its partner – or substructures in an interaction network that determines an organisms’ response to external stimuli. The 12 high-quality articles included in this special issue are essentially based on significant extensions of the selected papers presented at the Third International Conference on Pattern Recognition in Bioinformatics (PRIB 2008) held in Melbourne, Australia. All these selected papers for special issue have again undergone a thorough review by at least three reviewers who are experts in the field. The fresh review process was followed to ensure that the papers met the high standards of scientific and technical merit of the Pattern Recognition Letters journal. The issue is broadly divided into three sections of four papers each, namely (1) Section 1: Interaction Networks and Feature-based Predictions (2) Section 2: Microarray and Transcription Data Analysis (3) Section 3: Sequence Analysis and Motif Discovery
- Relation
- Pattern Recognition Letter Vol. 31, no. 14 (2010), p. 2071-2072
- Rights
- Copyright Elsevier
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; 0906 Electrical and Electronic Engineering; 1702 Cognitive Science
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