Abstract
Ensemble learning is an intensively studied technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complex data structures. The aim of this article is two-fold. Firstly, it is to provide a review of the most widely used ensemble learning methods and their application in various bioinformatics problems, including the main topics of gene expression, mass spectrometry-based proteomics, gene-gene interaction identification from genome-wide association studies, and prediction of regulatory elements from DNA and protein sequences. Secondly, we try to identify and summarize future trends of ensemble methods in bioinformatics. Promising directions such as ensemble of support vector machines, meta-ensembles, and ensemble based feature selection are discussed.
Keywords: Ensemble learning, bioinformatics, microarray, mass spectrometry-based proteomics, gene-gene interaction, regulatory elements prediction, ensemble of support vector machines, meta ensemble, ensemble feature selection.
Current Bioinformatics
Title:A Review of Ensemble Methods in Bioinformatics
Volume: 5 Issue: 4
Author(s): Pengyi Yang, Yee Hwa Yang, Bing B. Zhou and Albert Y. Zomaya
Affiliation:
Keywords: Ensemble learning, bioinformatics, microarray, mass spectrometry-based proteomics, gene-gene interaction, regulatory elements prediction, ensemble of support vector machines, meta ensemble, ensemble feature selection.
Abstract: Ensemble learning is an intensively studied technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complex data structures. The aim of this article is two-fold. Firstly, it is to provide a review of the most widely used ensemble learning methods and their application in various bioinformatics problems, including the main topics of gene expression, mass spectrometry-based proteomics, gene-gene interaction identification from genome-wide association studies, and prediction of regulatory elements from DNA and protein sequences. Secondly, we try to identify and summarize future trends of ensemble methods in bioinformatics. Promising directions such as ensemble of support vector machines, meta-ensembles, and ensemble based feature selection are discussed.
Export Options
About this article
Cite this article as:
Yang Pengyi, Hwa Yang Yee, B. Zhou Bing and Y. Zomaya Albert, A Review of Ensemble Methods in Bioinformatics, Current Bioinformatics 2010; 5 (4) . https://dx.doi.org/10.2174/157489310794072508
DOI https://dx.doi.org/10.2174/157489310794072508 |
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
-
Recent Development in Fluorescent Probes for Copper Ion Detection
Current Topics in Medicinal Chemistry Recent Advances, Issues and Patents on Medical Nanorobots
Recent Patents on Engineering Aryl and Acyclic Unsaturated Derivatives of Thioguanine and 6- Mercaptopurine: Synthesis and Cytotoxic Activity
Letters in Drug Design & Discovery DNAM-1 (CD226): A Two-Sword Fencer for Innate and Adaptive Immunity
Current Medicinal Chemistry - Anti-Inflammatory & Anti-Allergy Agents Nuclear Factor-κB: A Holy Grail in Cancer Prevention and Therapy
Current Signal Transduction Therapy Nano-pharmaceutical Formulations for Targeted Drug Delivery against HER2 in Breast Cancer
Current Cancer Drug Targets Threes Company: Regulation of Cell Fate by Statins
Current Drug Targets - Cardiovascular & Hematological Disorders The Role of Neuronal Insulin/Insulin-Like Growth Factor-1 Signaling for the Pathogenesis of Alzheimer’s Disease: Possible Therapeutic Implications
CNS & Neurological Disorders - Drug Targets Oral and Intravenous Ibandronate in the Management of Postmenopausal Osteoporosis: A Comprehensive Review
Current Pharmaceutical Design Nuclear Magnetic Resonance Spectroscopy of Lipids in Cancer
Current Organic Chemistry Influence of the Bystander Effect on HSV-tk / GCV Gene Therapy. A Review.
Current Gene Therapy The Interaction Between FAK, MYCN, p53 and Mdm2 in Neuroblastoma
Anti-Cancer Agents in Medicinal Chemistry Interplay between Epigenetics & Cancer Metabolism
Current Pharmaceutical Design Genetic Approaches for Antigen-Selective Cell Therapy
Current Gene Therapy Ultrasound Contrast Imaging in Cancer –Technical Aspects and Prospects
Current Molecular Imaging (Discontinued) ONCOFID™-P a Hyaluronic Acid Paclitaxel Conjugate for the Treatment of Refractory Bladder Cancer and Peritoneal Carcinosis
Current Bioactive Compounds Current Status of Hormone Replacement Therapy in Post Menopausal Women
Current Drug Therapy Effects of CAP-regimen Chemotherapy on Blood Redox Status in Patients with Ovarian Cancer
Anti-Cancer Agents in Medicinal Chemistry Pharmacologic Activation of p53 by Small-Molecule MDM2 Antagonists
Current Pharmaceutical Design Anti-diabetic Drug Metformin: Challenges and Perspectives for Cancer Therapy
Current Cancer Drug Targets