Abstract
Past decades have seen the rapid development of microarray technologies making available large amounts of gene expression data. Hence, it has become increasingly important to have reliable methods to interpret this information in order to discover new biological knowledge. In this review paper we aim to describe the main existing evolutionary methods that analyze microarray gene expression data by means of biclustering techniques. Strategies will be classified according to the evaluation metric used to quantify the quality of the biclusters. In this context, the main evaluation measures, namely mean squared residue, virtual error and transposed virtual error, are first presented. Then, the main evolutionary algorithms, which find biclusters in gene expression data matrices using those metrics, are described and compared.
Keywords: Biclustering, evaluation metrics, evolutionary algorithms, gene expression data, microarray analysis, regulatory networks.
Current Bioinformatics
Title:On Evolutionary Algorithms for Biclustering of Gene Expression Data
Volume: 10 Issue: 3
Author(s): A. Carballido Jessica, A. Gallo Cristian, S. Dussaut Julieta and Ponzoni Ignacio
Affiliation:
Keywords: Biclustering, evaluation metrics, evolutionary algorithms, gene expression data, microarray analysis, regulatory networks.
Abstract: Past decades have seen the rapid development of microarray technologies making available large amounts of gene expression data. Hence, it has become increasingly important to have reliable methods to interpret this information in order to discover new biological knowledge. In this review paper we aim to describe the main existing evolutionary methods that analyze microarray gene expression data by means of biclustering techniques. Strategies will be classified according to the evaluation metric used to quantify the quality of the biclusters. In this context, the main evaluation measures, namely mean squared residue, virtual error and transposed virtual error, are first presented. Then, the main evolutionary algorithms, which find biclusters in gene expression data matrices using those metrics, are described and compared.
Export Options
About this article
Cite this article as:
Jessica Carballido A., Cristian Gallo A., Julieta Dussaut S. and Ignacio Ponzoni, On Evolutionary Algorithms for Biclustering of Gene Expression Data, Current Bioinformatics 2015; 10 (3) . https://dx.doi.org/10.2174/1574893609666140829204739
DOI https://dx.doi.org/10.2174/1574893609666140829204739 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Targeting Proteasomes with Naturally Occurring Compounds in Cancer Treatment
Current Cancer Drug Targets Direct Evidence on the Immune-Mediated Spontaneous Regression of Human Cancer: An Incentive for Pharmaceutical Companies to Develop a Novel Anti-Cancer Vaccine
Current Pharmaceutical Design Targeting Heat Shock Protein 90 for Malaria
Mini-Reviews in Medicinal Chemistry A Guide to Treatment of Sarcoidosis
Current Drug Therapy Preparation and Quality Control of <sup>111</sup>In-Plerixafor for Chemokine Receptor CXCR4
Recent Patents and Topics on Imaging (Discontinued) Diterpenoids- Potential Chemopreventive and Chemotherapeutic Agents in Leukemia
Current Pharmaceutical Biotechnology Liposome-Nanogel Structures for Future Pharmaceutical Applications: An Updated Review
Current Pharmaceutical Design Monoclonal Antibodies in Clinical Oncology
Anti-Cancer Agents in Medicinal Chemistry Jun Dimerization Protein 2 in Oxygen Restriction; Control of Senescence
Current Pharmaceutical Design Cancer Stem Cells in Prostate Cancer Chemoresistance
Current Cancer Drug Targets Human Growth Hormone Induced Cholestatic Hepatitis in a Growth Hormone Deficient Patient with Short Stature
Current Drug Safety Targeting BCR-ABL Oncoprotein for Leukemia Therapy: Current Biotechnology and Future Perspectives
Current Biotechnology Membrane Transporters as Determinants of the Pharmacology of Platinum Anticancer Drugs
Current Cancer Drug Targets Nitric Oxide in Cancer Therapeutics: Interaction with Cytotoxic Chemotherapy
Current Pharmaceutical Design A Descriptive Analysis of Post-Chemotherapy Development of Interstitial Lung Disease Using Spontaneous Reporting Data in Japan
Current Drug Safety Progress in the Preclinical Discovery and Clinical Development of Class I and Dual Class I/IV Phosphoinositide 3-Kinase (PI3K) Inhibitors
Current Medicinal Chemistry Honey as a Source of Dietary Antioxidants: Structures, Bioavailability and Evidence of Protective Effects Against Human Chronic Diseases
Current Medicinal Chemistry Oncogenic Fusion Tyrosine Kinases as Molecular Targets for Anti-Cancer Therapy
Anti-Cancer Agents in Medicinal Chemistry Targeting EGFR for Treatment of Glioblastoma: Molecular Basis to Overcome Resistance
Current Cancer Drug Targets A Novel Synthesis Method of Apogossypolone and its Antitumor Activity
Letters in Drug Design & Discovery