Reverse Engineering of Regulatory Networks / edited by Sudip Mandal.

Format:

Book

Contributor:

Mandal, Sudip., Editor.

Series:

Methods in Molecular Biology, 1940-6029 ; 2719

Language:

English

Subjects (All):

Biomedical engineering.

Genetics.

Bioinformatics.

Biomedical Engineering and Bioengineering.

Local Subjects:

Biomedical Engineering and Bioengineering.

Genetics.

Bioinformatics.

Physical Description:

1 online resource (1 p.)

Edition:

1st ed. 2024.

Place of Publication:

New York, NY : Springer US : Imprint: Humana, 2024.

Summary:

This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Reverse Engineering of Regulatory Networks aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge. .

Contents:

Molecular Modeling Techniques and in-Silico Drug Discovery

Systems Biology Approach to Analyse Microarray Datasets for Identification of Disease-Causing Genes: Case Study of Oral Squamous cell Carcinoma

Fluorescence Spectroscopy: A Useful Method to Explore the Interactions of Small Molecule Ligands with DNA Structures

Inference of Dynamic Growth Regulatory Network in Cancer Using high-Throughput Transcriptomic Data

Implementation of Exome Sequencing to Identify Rare Genetic Diseases

Emerging Trends in Big Data Analysis in Computational Biology and Bioinformatics in Health Informatics: A Case Study on Epilepsy and Seizures

New Insights into Clinical Management for Sickle-Cell Disease: Uncovering the Significance Pathways Affected By the Involvement of Sickle Cell Disease

A Review on Computational Approach for S-system Based Modeling of Gene Regulatory Network

Big Data in Bioinformatics and Computational Biology: Basic Insights

Identification of Culprit Genes for Different Diseases by Analysing Microarray Data

Big Data Analysis in Computational Biology and Bioinformatics

Prediction and Analysis of Transcription Factor Binding Sites to Understand Gene Regulation: Practical Examples and Case Studies using R Programming

Hubs and Bottlenecks in Protein-Protein Interaction Networks

Next-Generation Sequencing to Study the DNA Interaction Nac Deep Learning for Predicting Gene Regulatory Networks: A Step-by-Step Protocol in R

Deep Learning for Predicting Gene Regulatory Networks: A Step-by-Step Protocol in R

Computational inference of Gene Regulatory Network using genome-wide ChIP-X data

Reverse Engineering in Biotechnology: The Role of Genetic Engineering in Synthetic Biology.

ISBN:

9781071634615

1071634615