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Soft Computing for Biological Systems de Hemant J. Purohit

Soft Computing for Biological Systems

Editat de Hemant J. Purohit, Vipin Chandra Kalia, Ravi Prabhakar More
en Limba Engleză Hardback – 14 mar 2018

Această primă ediție a lucrării Soft Computing for Biological Systems aduce în prim-plan o abordare integrată a bioinformaticii, propunând utilizarea tehnicilor de calcul relaxat (soft computing) pentru a descifra complexitatea informației genetice stocate în ADN. Spre deosebire de literatura clasică de biologie moleculară, volumul coordonat de Hemant J. Purohit, Vipin Chandra Kalia și Ravi Prabhakar More se concentrează pe capacitatea algoritmilor de a gestiona ambiguitatea și incertitudinea datelor biologice reale. Ne-a atras atenția modul în care autorii reușesc să facă tranziția de la teoria pură la aplicații clinice și ecologice concrete.

Structura cărții este riguros organizată în 12 capitole, debutând cu utilizarea rețelelor neuronale artificiale în predicția diagnostică bazată pe profiluri de expresie genică. Progresia conținutului acoperă teme esențiale precum alinierea secvențelor multiple prin hibridizarea algoritmilor de tip „Artificial Bee Colony” și analiza datelor metagenomice, oferind o perspectivă tehnică asupra instrumentelor de bioinformatics actuale. Această lucrare reprezintă o evoluție naturală față de volumele anterioare ale editorilor, cum este Mining of Microbial Wealth and MetaGenomics, trecând de la explorarea diversității ecosistemelor la modelarea predictivă a funcțiilor biologice.

Soft Computing for Biological Systems poate fi considerată o alternativă modernă la Analysis of Biological Data: A Soft Computing Approach de Sanghamitra Bandyopadhyay pentru cursurile de biologie computațională, oferind avantajul unor secțiuni dedicate noilor tehnici de preprocesare a datelor pentru managementul dăunătorilor și cercetarea biomarkerilor în oncologie. Reținem, de asemenea, capitolul dedicat transportorilor de medicamente ca ținte terapeutice, un domeniu în care modelele computaționale prezentate aici deschid noi oportunități pentru designul farmaceutic.

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Specificații

ISBN-13: 9789811074547
ISBN-10: 9811074542
Pagini: 310
Ilustrații: XII, 300 p. 43 illus., 31 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.65 kg
Ediția:1st ed. 2018
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

De ce să citești această carte

Recomandăm această carte cercetătorilor și studenților de la masterat sau doctorat în bioinformatică și biologie moleculară. Cititorul câștigă o înțelegere profundă a modului în care machine learning și algoritmii evolutivi pot fi aplicați pentru a prezice structura proteinelor și interacțiunile genice. Este un instrument esențial pentru cei care doresc să utilizeze tehnici avansate de procesare a datelor în analiza metagenomică și diagnosticarea asistată de inteligență artificială.

Despre autor

Editorii volumului sunt personalități recunoscute în domeniul biotehnologiei și bioinformaticii. Hemant J. Purohit și Vipin Chandra Kalia au colaborat anterior la lucrări de referință precum Optimization and Applicability of Bioprocesses, unde au explorat integrarea strategiilor verzi de inginerie. Expertiza lor combinată acoperă un spectru larg, de la microbiologie industrială și metagenomică până la dezvoltarea de modele computaționale pentru sisteme biologice complexe. Activitatea lor academică se concentrează pe utilizarea resurselor microbiene și optimizarea proceselor biologice prin intermediul tehnologiei informației.

Descriere scurtă

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.

Cuprins

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.

Notă biografică

Dr. Vipin Chandra Kalia is an Emeritus scientist and Ex-Chief Scientist at Microbial Biotechnology and Genomics, CSIR-Institute of Genomics and Integrative Biology, Delhi. He obtained his M.Sc. and Ph.D. degrees in Genetics from the Indian Agricultural Research Institute, New Delhi. He has been elected as: (1) Fellow of the Association of Microbiologists of India (FAMI), (2) Fellow of the National Academy of Sciences (FNASc), and (3) Fellow of National Academy of agricultural Sciences (FNAAS). His main areas of research are microbial biodiversity, genomics and evolution, bioenergy, biopolymers, antimicrobials, quorum sensing, and quorum quenching. He has published 101 papers in scientific journals such as (1) Nature Biotechnology, (2) Biotechnology Advances, (3) Trends in Biotechnology, (4) Critical Reviews in Microbiology, (5) Bioresource Technology, (6) International Journal of Hydrogen Energy, (7) PLoS ONE, (8) BMC Genomics, (9) Gene, and (10) Annual Review of Microbiology.His Google scholar citations are 4219 (as on 31st Aug 2017),  and he has an h index of 36 and an i10 index of 76. He has edited 3 books: Quorum sensing versus quorum quenching: A battle with no end in sight (2015, Springer India), Microbial Factories Vol 1 and 2 (2015). He is presently the editor in chief of the Indian Journal of Microbiology and Editor of (1) PLoS ONE, (2)Journal of Microbiology & Biotechnology (Korea), (3) Applied Biochemistry & Biotechnology (USA), (4) International Scholarly Research Notices (Energy), (5) Dataset Papers in Science (Microbiology), and (6) Journal of Molecular and Genetic Medicine. He is a life member of the following scientific societies: (1) Society of Biological Chemists of India (2) Society for Plant Biochemistry and Biotechnology, India; (3) Association of Microbiologists of India; (4) Indian Science Congress Association; (5) BioEnergy Society of India, and (6) the Biotech Research Society of India (BRSI). He is also a member of the American Society for Microbiology.

Dr Hemant J. Purohit is Chief Scientist, Head Environmental Biotechnology & Genomics Division. He completed his PhD from Nagpur University in 1986. He has been involved in Designing a strategy for capturing microbial diversity and exploration  by interfacing culturable and DNA fingerprinting tools; Developing genomics based monitoring tools for EIA and bio-remediation process; Study of stress dependent microbial response using dynamic gene expression and its application in bioprocess optimization; Developing better insights into microbial capacities for utilization of organics through genome sequence analysis etc. He has been project coordinator for a number of high value projects. He has 225 publications to his credit. His Google scholar citations is 4843 (as on August 2017), and he has an h-index of 38 and i10-index of 113. He has supervised 25 PhD students and more than 100 students for their projects / dissertations. He is a highly distinguished scientist. He is a recipient of a number of prestigious awards, including Fogarty International Exchange Program Fellowship (NINDS, NIH, Bethesda); Commonwealth Fellowship (Department of Biochemistry, Hull University, UK), Department of Biochemistry, University of Hull, UK; CSIR Research Fellowships (JRF and SRF) etc.

Dr. Ravi Prabhakar More is a Bioinformatician in the Accelerator program for Discovery in Brain disorders using Stem cells (ADBS) program at the prestigious TIFR-National Centre for Biological Sciences, Bangalore, India. His current research interest is the genetic analysis of individuals from mental illness families using the whole genome and exome sequence analysis. He completed his PhD in Bioinformatics from CSIR-National Environmental Engineering Research Institute (NEERI), Nagpur, India. He is the author of twelve research articles that have been published in well reputed peer-reviewed international journals. He has developed QR encrypted signature-based matK-QR Classifier software for plant species identification using matK gene sequences and published in BMC BioDataMining journal. For taxonomic classification of 16S rRNA sequences based on QR code encrypted signatures, he has developed a DNA BarID software tool, which is published in Journal of Computational Biology. He is the recipient of the award for outstanding project personnel in CSIR-NEERI, Nagpur India. He has analyzed metagenomes of CETP and Rumen Microbial Fibrolytic Enzymes in Indian Crossbred Cattle metagenome analysis, which was carried out to understand the taxonomic and metabolic potential using various tools and databases. On these work, four research articles are published in different journals viz. Bioresource Technology, AMB Express Journal. He was International Intern at NIBB Institute, Japan and developed combined supervised approach (Naïve Bayesian and homology) for detecting horizontal gene transfer (HGT) events in the microbial community. He did DNA Barcoding studies with respect to construction and analysis of phylogenetic trees of insect pests and published his work in well-reputed journals. He has attended a number of international conferences and published posters on different topics.

Caracteristici

Includes well-illustrated chapters for easy understanding of methodologies
Provides the most recent research in the area of soft-computing analysis
Discusses how the insights from various computational studies can be collated and ultimately exploited practically