Construction of gene regulatory networks using biclustering and Bayesian networks

Theoretical Biology & Medical Modelling
Fadhl M AlakwaaYasser M Kadah

Abstract

Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling. In this paper, we develop a biclustering function enrichment analysis toolbox (BicAT-plus) to study the effect of biclustering in reducing data dimensions. The network generated from our system was validated via available interaction databases and was compared with previous methods. The results revealed the performance of our proposed method. Because of the sparse nature of GRNs, the results of biclustering techniques differ significantly from those of previous methods.

References

Jul 3, 1999·Nature Genetics·S TavazoieG M Church
Dec 5, 2000·Molecular Biology of the Cell·A P GaschP Brown
Dec 7, 2000·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·N FriedmanDana Pe'er
Apr 13, 2001·Bioinformatics·K Y YeungW L Ruzzo
Jun 8, 2001·Bioinformatics·O TroyanskayaR B Altman
Feb 16, 2002·Bioinformatics·F Azuaje
Jul 23, 2002·Nature Genetics·Jan IhmelsNaama Barkai
Aug 10, 2002·Bioinformatics·Amos TanayRon Shamir
Jan 15, 2003·BMC Bioinformatics·Gary D Bader, Christopher W V Hogue
Aug 26, 2003·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Amir Ben-DorZohar Yakhini
Oct 10, 2003·Bioinformatics·Jean Philippe Vert, Minoru Kanehisa
Apr 28, 2005·Science's STKE : Signal Transduction Knowledge Environment·Dana Pe'er
Mar 18, 2006·Bioinformatics·Xue-Wen ChenXinkun Wang
Mar 23, 2006·Bioinformatics·Simon BarkowEckart Zitzler
Oct 20, 2006·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Sara C Madeira, Arlindo L Oliveira
Nov 9, 2006·Bioinformatics·Xiaowen Liu, Lusheng Wang
Dec 2, 2006·Bioinformatics·Iliana Avila-CampilloRichard Bonneau
Jun 26, 2007·Bioinformatics·K O ChengT H Lau
Nov 17, 2007·Bioinformatics·Yassen AssenovMario Albrecht
Feb 20, 2008·PLoS Pathogens·Matthew D DyerBruno W Sobral
Apr 8, 2009·Annals of the New York Academy of Sciences·Ronald C TaylorJason McDermott
Apr 8, 2009·Annals of the New York Academy of Sciences·Gustavo StolovitzkyAndrea Califano
May 30, 2009·Bioinformatics·Aurélie C LozanoSaharon Rosset

Citations

Nov 10, 2012·Theory in Biosciences = Theorie in Den Biowissenschaften·Hong Li
Jan 31, 2012·Briefings in Bioinformatics·Jinlian WangHabtom W Ressom
Sep 6, 2014·PloS One·Valeria BoAllan Tucker
Oct 9, 2014·TheScientificWorldJournal·Francisco Gómez-Vela, Norberto Díaz-Díaz
Mar 13, 2014·IEEE Journal of Biomedical and Health Informatics·K KalantzakiD I Fotiadis
May 4, 2015·Computational Biology and Chemistry·Francisco Gómez-VelaNorberto Díaz-Díaz
Jun 14, 2016·Computational and Structural Biotechnology Journal·Theodora KatsilaMinos-Timotheos Matsoukas
Sep 1, 2016·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Daniel N MohsenizadehEdward R Dougherty

Related Concepts

Bayesian Prediction
Receiver Operating Characteristic
Saccharomyces cerevisiae
Disease Clustering
Log-Linear Models
Online Mendelian Inheritance In Man
Gene Modules
DNA
Pharmaceutical Preparations
Genes

Trending Feeds

COVID-19

Coronaviruses encompass a large family of viruses that cause the common cold as well as more serious diseases, such as the ongoing outbreak of coronavirus disease 2019 (COVID-19; formally known as 2019-nCoV). Coronaviruses can spread from animals to humans; symptoms include fever, cough, shortness of breath, and breathing difficulties; in more severe cases, infection can lead to death. This feed covers recent research on COVID-19.

Synthetic Genetic Array Analysis

Synthetic genetic arrays allow the systematic examination of genetic interactions. Here is the latest research focusing on synthetic genetic arrays and their analyses.

Congenital Hyperinsulinism

Congenital hyperinsulinism is caused by genetic mutations resulting in excess insulin secretion from beta cells of the pancreas. Here is the latest research.

Neural Activity: Imaging

Imaging of neural activity in vivo has developed rapidly recently with the advancement of fluorescence microscopy, including new applications using miniaturized microscopes (miniscopes). This feed follows the progress in this growing field.

Chronic Fatigue Syndrome

Chronic fatigue syndrome is a disease characterized by unexplained disabling fatigue; the pathology of which is incompletely understood. Discover the latest research on chronic fatigue syndrome here.

Epigenetic Memory

Epigenetic memory refers to the heritable genetic changes that are not explained by the DNA sequence. Find the latest research on epigenetic memory here.

Cell Atlas of the Human Eye

Constructing a cell atlas of the human eye will require transcriptomic and histologic analysis over the lifespan. This understanding will aid in the study of development and disease. Find the latest research pertaining to the Cell Atlas of the Human Eye here.

Femoral Neoplasms

Femoral Neoplasms are bone tumors that arise in the femur. Discover the latest research on femoral neoplasms here.

STING Receptor Agonists

Stimulator of IFN genes (STING) are a group of transmembrane proteins that are involved in the induction of type I interferon that is important in the innate immune response. The stimulation of STING has been an active area of research in the treatment of cancer and infectious diseases. Here is the latest research on STING receptor agonists.