Abstract
In the post-genome era, designing and conducting novel experiments have become increasingly common for modern researchers. However, the major challenge faced by researchers is surprisingly not the complexity in designing new experiments or obtaining the data generated from the experiments, but instead it is the huge amount of data to be processed and analyzed in the quest to produce meaningful information and knowledge. Gene regulatory network (GRN) inference from gene expression data is one of the common examples of such challenge. Over the years, GRN inference has witnessed a number of transitions, and an increasing amount of new computational and statistical-based methods have been applied to automate the procedure. One of the widely used approaches for GRN inference is the dynamic Bayesian network (DBN). In this review paper, we first discuss the evolution of molecular biology research from reductionism to holism. This is followed by a brief insight on various computational and statistical methods used in GRN inference before focusing on reviewing the current development and applications of DBN-based methods.
Keywords: Dynamic bayesian network, gene regulatory networks, network inference, time-series gene expression data.
Current Bioinformatics
Title:Current Development and Review of Dynamic Bayesian Network-Based Methods for Inferring Gene Regulatory Networks from Gene Expression Data
Volume: 9 Issue: 5
Author(s): Lian En Chai, Mohd Saberi Mohamad, Safaai Deris, Chuii Khim Chong, Yee Wen Choon and Sigeru Omatu
Affiliation:
Keywords: Dynamic bayesian network, gene regulatory networks, network inference, time-series gene expression data.
Abstract: In the post-genome era, designing and conducting novel experiments have become increasingly common for modern researchers. However, the major challenge faced by researchers is surprisingly not the complexity in designing new experiments or obtaining the data generated from the experiments, but instead it is the huge amount of data to be processed and analyzed in the quest to produce meaningful information and knowledge. Gene regulatory network (GRN) inference from gene expression data is one of the common examples of such challenge. Over the years, GRN inference has witnessed a number of transitions, and an increasing amount of new computational and statistical-based methods have been applied to automate the procedure. One of the widely used approaches for GRN inference is the dynamic Bayesian network (DBN). In this review paper, we first discuss the evolution of molecular biology research from reductionism to holism. This is followed by a brief insight on various computational and statistical methods used in GRN inference before focusing on reviewing the current development and applications of DBN-based methods.
Export Options
About this article
Cite this article as:
Chai En Lian, Mohamad Saberi Mohd, Deris Safaai, Chong Khim Chuii, Choon Wen Yee and Omatu Sigeru, Current Development and Review of Dynamic Bayesian Network-Based Methods for Inferring Gene Regulatory Networks from Gene Expression Data, Current Bioinformatics 2014; 9 (5) . https://dx.doi.org/10.2174/1574893609666140421210333
DOI https://dx.doi.org/10.2174/1574893609666140421210333 |
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
-
BRCA Unclassified Variants: How Can They be Classified?
Current Women`s Health Reviews Targeting Gene Therapy for Prostate Cancer
Current Pharmaceutical Design Recent Progress in the Development of Fluorometric Chemosensors to Detect Enzymatic Activity
Current Medicinal Chemistry Micro/Nanoparticle Design and Fabrication for Pharmaceutical Drug Preparation and Delivery Applications
Current Drug Therapy Synthesis and Anticancer Properties of Novel Truncated Carbocyclic Nucleoside Analogues
Anti-Cancer Agents in Medicinal Chemistry Light Directed Gene Transfer by Photochemical Internalisation
Current Gene Therapy Utilization of Tumor Markers in Adnexal Masses: A Review of Current Literature
Current Women`s Health Reviews Cellular Delivery In Vivo of siRNA-Based Therapeutics
Current Pharmaceutical Design Targeted Regulation of PI3K/Akt/mTOR/NF-κB Signaling by Indole Compounds and their Derivatives: Mechanistic Details and Biological Implications for Cancer Therapy
Anti-Cancer Agents in Medicinal Chemistry Herpesvirus / Retrovirus Chimeric Vectors
Current Gene Therapy Surgical Management of the Adnexal Mass
Current Women`s Health Reviews PI3K/AKT/mTOR Inhibitors In Ovarian Cancer
Current Medicinal Chemistry Influence of New Synthetic Xanthones on the Proliferation and Migration Potential of Cancer Cell Lines In Vitro
Anti-Cancer Agents in Medicinal Chemistry 1,8-Naphthyridine Derivatives: A Privileged Scaffold for Versatile Biological Activities
Mini-Reviews in Medicinal Chemistry Design, Synthesis, Molecular Docking and Biological Evaluation of 1-(benzo[d]thiazol-2-ylamino)(phenyl)methyl)naphthalen-2-ol Derivatives as Antiproliferative Agents
Letters in Organic Chemistry Application of MALDI-TOF Mass Spectrometry in Screening and Diagnostic Research
Current Pharmaceutical Design Proteomic and Metallomic Strategies for Understanding the Mode of Action of Anticancer Metallodrugs
Anti-Cancer Agents in Medicinal Chemistry Working Towards the Development of Vaccines for the Treatment and Prevention of Early Breast Cancer
Current Cancer Therapy Reviews Interactions of the Aryl Hydrocarbon Receptor with Inflammatory Mediators:Beyond CYP1A Regulation
Current Drug Metabolism Oxidative Stress in Tumor Angiogenesis - Therapeutic Targets
Current Pharmaceutical Design