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Hardcover. Zustand: new. Hardcover. This book provides an overview of basic and advanced computational techniques for analyzing and understanding protein, RNA, and DNA sequences. It covers effective computing techniques for DNA and protein classifications, evolutionary and sequence information analysis, evolutionary algorithms, and ensemble algorithms. Furthermore, the book reviews the role of machine learning techniques, artificial intelligence, ensemble learning, and sequence-based features in predicting post-translational modifications in proteins, DNA methylation, and mRNA methylation, along with their functional implications. The book also discusses the prediction of proteinprotein and proteinDNA interactions, protein structure, and function using computational methods. It also presents techniques for quantitative analysis of proteinDNA interactions and protein methylation and their involvement in gene regulation. Additionally, the use of nature-inspired algorithms to gain insights into gene regulatory mechanisms and metabolic pathways in human diseases is explored. This book acts as a useful reference for bioinformaticians and computational biologists working in the fields of molecular biology, genomics, and bioinformatics.Key Features:Reviews machine learning techniques for DNA sequence classification and protein structure predictionDiscusses genetic algorithms for analyzing multiple sequence alignments and predicting proteinprotein interaction sitesExplores computational methods for quantitative analysis of proteinDNA interactionsExamine the role of nature-inspired algorithms in understanding the gene regulation and metabolic pathwaysCovers evolutionary algorithms and sequence-based features in predicting post-translational modifications This book provides an overview of basic and advanced computational techniques for analysing and understanding protein, RNA, and DNA sequences. This book acts as useful reference for bioinformaticians and computational biologists working in the field of molecular biology, genomics, and bioinformatics. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Saiyed Umer is currently serving as an Assistant Professor in the Department of Computer Science and Engineering Aliah University, Kolkata, India. He was the Research Personnel at Indian Statistical Institute (ISI), Kolkata, India, from November 2.

Hardcover. Zustand: new. Hardcover. This book provides an overview of basic and advanced computational techniques for analyzing and understanding protein, RNA, and DNA sequences. It covers effective computing techniques for DNA and protein classifications, evolutionary and sequence information analysis, evolutionary algorithms, and ensemble algorithms. Furthermore, the book reviews the role of machine learning techniques, artificial intelligence, ensemble learning, and sequence-based features in predicting post-translational modifications in proteins, DNA methylation, and mRNA methylation, along with their functional implications. The book also discusses the prediction of proteinprotein and proteinDNA interactions, protein structure, and function using computational methods. It also presents techniques for quantitative analysis of proteinDNA interactions and protein methylation and their involvement in gene regulation. Additionally, the use of nature-inspired algorithms to gain insights into gene regulatory mechanisms and metabolic pathways in human diseases is explored. This book acts as a useful reference for bioinformaticians and computational biologists working in the fields of molecular biology, genomics, and bioinformatics.Key Features:Reviews machine learning techniques for DNA sequence classification and protein structure predictionDiscusses genetic algorithms for analyzing multiple sequence alignments and predicting proteinprotein interaction sitesExplores computational methods for quantitative analysis of proteinDNA interactionsExamine the role of nature-inspired algorithms in understanding the gene regulation and metabolic pathwaysCovers evolutionary algorithms and sequence-based features in predicting post-translational modifications This book provides an overview of basic and advanced computational techniques for analysing and understanding protein, RNA, and DNA sequences. This book acts as useful reference for bioinformaticians and computational biologists working in the field of molecular biology, genomics, and bioinformatics. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Zustand: new. Hardcover. This book provides an overview of basic and advanced computational techniques for analyzing and understanding protein, RNA, and DNA sequences. It covers effective computing techniques for DNA and protein classifications, evolutionary and sequence information analysis, evolutionary algorithms, and ensemble algorithms. Furthermore, the book reviews the role of machine learning techniques, artificial intelligence, ensemble learning, and sequence-based features in predicting post-translational modifications in proteins, DNA methylation, and mRNA methylation, along with their functional implications. The book also discusses the prediction of proteinprotein and proteinDNA interactions, protein structure, and function using computational methods. It also presents techniques for quantitative analysis of proteinDNA interactions and protein methylation and their involvement in gene regulation. Additionally, the use of nature-inspired algorithms to gain insights into gene regulatory mechanisms and metabolic pathways in human diseases is explored. This book acts as a useful reference for bioinformaticians and computational biologists working in the fields of molecular biology, genomics, and bioinformatics.Key Features:Reviews machine learning techniques for DNA sequence classification and protein structure predictionDiscusses genetic algorithms for analyzing multiple sequence alignments and predicting proteinprotein interaction sitesExplores computational methods for quantitative analysis of proteinDNA interactionsExamine the role of nature-inspired algorithms in understanding the gene regulation and metabolic pathwaysCovers evolutionary algorithms and sequence-based features in predicting post-translational modifications This book provides an overview of basic and advanced computational techniques for analysing and understanding protein, RNA, and DNA sequences. This book acts as useful reference for bioinformaticians and computational biologists working in the field of molecular biology, genomics, and bioinformatics. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides an overview of basic and advanced computational techniques for analysing and understanding protein, RNA, and DNA sequences. This book acts as useful reference for bioinformaticians and computational biologists working in the field of molecular biology, genomics, and bioinformatics.