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Biological pattern discovery with R : machine learning approaches / Zheng Rong Yang.

By: Material type: TextPublication details: Singapore : World Scientific, 2021.Description: 1 online resource (464 p.)ISBN:
  • 9789811240126
  • 9811240124
Subject(s): Genre/Form: DDC classification:
  • 570.1/13 23
LOC classification:
  • QH324.2 .Y36 2021
Online resources:
Contents:
Introduction -- Responsive gene discovery -- Protease cleavage pattern discovery -- Genetic-epigenetic interplay discovery -- Spectral pattern discovery -- Gene expression pattern discovery -- Whole genome pattern discovery -- Optimised peptide pattern discovery -- Advanced subjects.
Summary: "This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worldwide. The chapters are organised to address individual biological pattern discovery problems. For each subject, the research methodologies and the machine learning algorithms which can be employed are introduced and compared. Importantly, each chapter was written with the aim to help the readers to transfer their knowledge in theory to practical implementation smoothly. Therefore, the R programming environment was used for each subject in the chapters. The author hopes that this book can inspire new or junior researchers' interest in biological pattern discovery using machine learning algorithms"-- Publisher's website.
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Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Electronic Books CUTN Central Library 570.1/13 (Browse shelf(Opens below)) Link to resource Available EB04937

Includes bibliographical references and index.

Introduction -- Responsive gene discovery -- Protease cleavage pattern discovery -- Genetic-epigenetic interplay discovery -- Spectral pattern discovery -- Gene expression pattern discovery -- Whole genome pattern discovery -- Optimised peptide pattern discovery -- Advanced subjects.

"This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worldwide. The chapters are organised to address individual biological pattern discovery problems. For each subject, the research methodologies and the machine learning algorithms which can be employed are introduced and compared. Importantly, each chapter was written with the aim to help the readers to transfer their knowledge in theory to practical implementation smoothly. Therefore, the R programming environment was used for each subject in the chapters. The author hopes that this book can inspire new or junior researchers' interest in biological pattern discovery using machine learning algorithms"-- Publisher's website.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

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