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Soft computing for biological systems

Purohit, Hemant J.

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Soft computing for biological systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Soft computing for biological systems/ edited by Hemant J. Purohit, Vipin Chandra Kalia, Ravi Prabhakar More.
other author:	Purohit, Hemant J.
Published:	Singapore :Springer Singapore : : 2018.,
Description:	xii, 300 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1. Diagnostic prediction based on gene expression profiles and artificial neural networks -- 2. Soft-Computing Approaches to Extract Biologically Significant Gene Network Modules -- 3. A Hybridization of Artificial Bee Colony with Swarming Approach of Bacterial Foraging Optimization for Multiple Sequence Alignment -- 4. Construction Gene Networks Using Gene Expression Profiles -- 5. Bioinformatics tools for shotgun metagenomic data analysis -- 6. Prediction of protein-protein interactions using machine learning techniques -- 7. Protein structure prediction using machine learning approaches -- 8. Drug-transporters as Therapeutic targets: Computational Models, Challenge and Opportunity -- 9. Module-Based Knowledge Discovery for Multiple-Cytosine-Variant Methylation Profile -- 10. Outlook of various soft computing data pre-processing techniques to study the pest population dynamics in Integrated Pest Management -- 11. Genomics for Oral Cancer Biomarker research -- 12. Soft-computing methods and tools for Bacteria DNA Barcoding data analysis -- 13. Fish DNA Barcoding: A comprehensive survey of the Bioinformatics tools and databases.
Contained By:	Springer eBooks
Subject:	Computational biology. -
Online resource:	http://dx.doi.org/10.1007/978-981-10-7455-4
ISBN:	9789811074554

Soft computing for biological systems
Soft computing for biological systems[electronic resource] /edited by Hemant J. Purohit, Vipin Chandra Kalia, Ravi Prabhakar More. - Singapore :Springer Singapore :2018. - xii, 300 p. :ill. (some col.), digital ;24 cm.

1. Diagnostic prediction based on gene expression profiles and artificial neural networks -- 2. Soft-Computing Approaches to Extract Biologically Significant Gene Network Modules -- 3. A Hybridization of Artificial Bee Colony with Swarming Approach of Bacterial Foraging Optimization for Multiple Sequence Alignment -- 4. Construction Gene Networks Using Gene Expression Profiles -- 5. Bioinformatics tools for shotgun metagenomic data analysis -- 6. Prediction of protein-protein interactions using machine learning techniques -- 7. Protein structure prediction using machine learning approaches -- 8. Drug-transporters as Therapeutic targets: Computational Models, Challenge and Opportunity -- 9. Module-Based Knowledge Discovery for Multiple-Cytosine-Variant Methylation Profile -- 10. Outlook of various soft computing data pre-processing techniques to study the pest population dynamics in Integrated Pest Management -- 11. Genomics for Oral Cancer Biomarker research -- 12. Soft-computing methods and tools for Bacteria DNA Barcoding data analysis -- 13. Fish DNA Barcoding: A comprehensive survey of the Bioinformatics tools and databases.

This book explains how the biological systems and their functions are driven by genetic information stored in the DNA, and their expression driven by different factors. The soft computing approach recognizes the different patterns in DNA sequence and try to assign the biological relevance with available information.The book also focuses on using the soft-computing approach to predict protein-protein interactions, gene expression and networks. The insights from these studies can be used in metagenomic data analysis and predicting artificial neural networks.

ISBN: 9789811074554

Standard No.: 10.1007/978-981-10-7455-4doiSubjects--Topical Terms:

590653
Computational biology.

LC Class. No.: QH324.2

Dewey Class. No.: 570.285

Soft computing for biological systems
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245 0 0 $a Soft computing for biological systems $h [electronic resource] / $c edited by Hemant J. Purohit, Vipin Chandra Kalia, Ravi Prabhakar More.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2018.
300 $a xii, 300 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 1. Diagnostic prediction based on gene expression profiles and artificial neural networks -- 2. Soft-Computing Approaches to Extract Biologically Significant Gene Network Modules -- 3. A Hybridization of Artificial Bee Colony with Swarming Approach of Bacterial Foraging Optimization for Multiple Sequence Alignment -- 4. Construction Gene Networks Using Gene Expression Profiles -- 5. Bioinformatics tools for shotgun metagenomic data analysis -- 6. Prediction of protein-protein interactions using machine learning techniques -- 7. Protein structure prediction using machine learning approaches -- 8. Drug-transporters as Therapeutic targets: Computational Models, Challenge and Opportunity -- 9. Module-Based Knowledge Discovery for Multiple-Cytosine-Variant Methylation Profile -- 10. Outlook of various soft computing data pre-processing techniques to study the pest population dynamics in Integrated Pest Management -- 11. Genomics for Oral Cancer Biomarker research -- 12. Soft-computing methods and tools for Bacteria DNA Barcoding data analysis -- 13. Fish DNA Barcoding: A comprehensive survey of the Bioinformatics tools and databases.
520 $a This book explains how the biological systems and their functions are driven by genetic information stored in the DNA, and their expression driven by different factors. The soft computing approach recognizes the different patterns in DNA sequence and try to assign the biological relevance with available information.The book also focuses on using the soft-computing approach to predict protein-protein interactions, gene expression and networks. The insights from these studies can be used in metagenomic data analysis and predicting artificial neural networks.
650 0 $a Computational biology. $3 590653
650 0 $a Systems biology. $3 905904
650 0 $a Soft computing. $3 563033
650 1 4 $a Life Sciences. $3 890838
650 2 4 $a Bioinformatics. $3 553671
650 2 4 $a Gene Expression. $3 600530
650 2 4 $a Biomedical Engineering/Biotechnology. $3 2162071
650 2 4 $a Computational Biology/Bioinformatics. $3 898313
650 2 4 $a Gene Function. $3 1067308
700 1 $a Purohit, Hemant J. $3 3274703
700 1 $a Kalia, Vipin Chandra. $3 2132839
700 1 $a More, Ravi Prabhakar. $3 3301506
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-7455-4
950 $a Biomedical and Life Sciences (Springer-11642)