Emerging Research in the Analysis and Modeling of Gene Regulatory Networks
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Emerging Research in the Analysis and Modeling of Gene Regulatory Networks

Ivan V. Ivanov, Xiaoning Qian, Ranadip Pal
Release Date: June, 2016|Copyright: © 2016 |Pages: 418
DOI: 10.4018/978-1-5225-0353-8
ISBN13: 9781522503538|ISBN10: 1522503536|EISBN13: 9781522503545
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Description & Coverage
Description:

While technological advancements have been critical in allowing researchers to obtain more and better quality data about cellular processes and signals, the design and practical application of computational models of genomic regulation continues to be a challenge.

Emerging Research in the Analysis and Modeling of Gene Regulatory Networks presents a compilation of recent and emerging research topics addressing the design and use of technology in the study and simulation of genomic regulation. Exploring both theoretical and practical topics, this publication is an essential reference source for students, professionals, and researchers working in the fields of genomics, molecular biology, bioinformatics, and drug development.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Bioinformatics
  • Cell Modeling
  • Drug Discovery
  • Multinomial Logistic Regression
  • Predictive Computational Modeling
  • Stochastic Simulation
  • Systems biology
Reviews & Statements

Contributors from borders between biological and computational sciences survey recent research and suggest future research into analyzing and modeling gene regulatory networks. Among their topics are relationships between models of genetic regulatory networks with emphasis on discrete state stochastic models, modeling stochastic gene regulatory networks using direct solutions of chemical master equations and rare event sampling, why multiple regulators are required for the transcription of each gene, and computational inferences of gene regulation from whole-transcriptome analysis of early embryos.

– ProtoView Reviews
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Editor/Author Biographies

Xiaoning Qian received the Ph.D. degree in Electrical Engineering from Yale University, New Haven, CT, in 2005. Currently, he is an assistant professor with the Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX. He is affiliated with the Center for Bioinformatics & Genomic Systems Engineering (CBGSE) and the Center for Translational Environmental Health Research (CTEHR) at Texas A\&M. His current research interests include computational network biology, genomic signal processing, and biomedical image analysis.

Ranadip Pal received the BTech degree in electronics and electrical communication engineering from the Indian Institute of Technology, Kharagpur, India, in 2002, and the MS and PhD degrees in electrical engineering from Texas A & M University, College Station, in 2004 and 2007, respectively. From August 2007, he has been with Texas Tech University where he is currently an associate professor at Electrical and Computer Engineering Department. His research areas are stochastic modeling and control, genomic signal processing, and computational biology. He received the Chancellor's Council Distinguished Research Award, 2016; Whitacre Research Award, 2014; President’s excellence in Teaching Award, 2012, and US NSF CAREER Award, 2010.

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