Gene Expression Data Analysis - A Statistical and Machine Learning Perspective (Hardcover)

An introduction to the Central Dogma of molecular biology and information flow in biological systems. A systematic overview of the methods for generating gene expression data. Background knowledge on statistical modeling and machine learning techniques. Detailed methodology of analyzing gene expression data with an example case study. Clustering methods for finding co-expression patterns from microarray, bulkRNA and scRNA data. A large number of practical tools, systems and repositories that are useful for computational biologists to create, analyze and validate biologically relevant gene expression patterns. Suitable for multi-disciplinary researchers and practitioners in computer science and biological sciences.

General

Imprint:	Crc Press
Country of origin:	United Kingdom
Release date:	November 2021
First published:	2022
Authors:	Pankaj Barah • Dhruba Kumar Bhattacharyya • Jugal Kumar Kalita
Dimensions:	234 x 156mm (L x W)
Format:	Hardcover
Pages:	360
ISBN-13:	978-0-367-33889-3
Categories:	Books > Science & Mathematics > Biology, life sciences > General Books > Computing & IT > General theory of computing > General Books > Professional & Technical > Biochemical engineering > Biotechnology > General Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Books > Computing & IT > Applications of computing > Databases > General
LSN:	0-367-33889-0
Barcode:	9780367338893

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