Gene Expression Data Analysis: A Statistical and Machine Learning Perspective - Image 1

£54.24

Chapman and Hall/CRC Gene Expression Data Analysis: A Statistical and Machine Learning Perspective

Name: Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Brand: Chapman and Hall/CRC
Price: 54.24 GBP
Availability: InStock

Econometrics

Price History & Forecast

Last 23 days • 23 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 23 days • 1 price levels

Days at Price

Price Analysis

Most common price: £54 (23 days, 100.0%)

Price range: £54 - £54

Price levels: 1 different prices over 23 days

Description

Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: 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 multidisciplinary researchers and practitioners in computer science and biological sciences

Product Specifications

Brand: Chapman and Hall/CRC
Format: Paperback
ASIN: 1032055758
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 04 October 2024
Listed Since: 10 August 2024

Barcode

No barcode data available

Chapman and Hall/CRC Gene Expression Data Analysis: A Statistical and Machine Learning Perspective

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

CRC Press Gene Expression Data Analysis - Statistical Book

Advanced Analysis Of Gene Expression Microarray Data: 1 (Science, Engineering, And Biology Informatics)

Statistical Analysis of Gene Expression Microarray Data (Chapman & Hall/CRC Interdisciplinary Statistics)

Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R (Chapman & Hall/CRC Computational Biology Series)

Big Data in Omics and Imaging: Association Analysis (Chapman & Hall/CRC Computational Biology Series)

RNA-seq Data Analysis: A Practical Approach (Chapman & Hall/CRC Computational Biology Series)

Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities

Gene Expression Studies Using Affymetrix Microarrays (Chapman & Hall/CRC Computational Biology Series)

Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Microarray Image Analysis: An Algorithmic Approach (Chapman & Hall/CRC Computer Science & Data Analysis)

Big Data Analysis for Bioinformatics and Biomedical Discoveries (Chapman & Hall/CRC Computational Biology Series)

Next-Generation Sequencing Data Analysis

Statistical Modeling and Machine Learning for Molecular Biology (Chapman & Hall/CRC Computational Biology Series)

Introduction to Bioinformatics with R: A Practical Guide for Biologists (Chapman & Hall/CRC Computational Biology Series)

Computational Biology and Bioinformatics: Gene Regulation

Analyzing Gene Expression and DNA Methylation Data with R

Gene Expression Studies Using Affymetrix Microarrays (Chapman & Hall/CRC Computational Biology Series)

Computational Genetics: Advanced Data Analysis Programming with R and Bioconductor (Genesis Protocol: Next Generation Technology for Biological and Life Sciences)

Statistics and Data Analysis for Microarrays Using R and Bioconductor (Chapman & Hall/CRC Computational Biology Series)

Hands on Data Science for Biologists Using Python

Hands on Data Science for Biologists Using Python

Computational Biology and Bioinformatics: Gene Regulation

Introduction to Bioinformatics with R: A Practical Guide for Biologists (Chapman & Hall/CRC Computational Biology Series)