LEADER 04172nam  22006135  450 
001 9910298425303321
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010   $a981-10-7455-0
024 7 $a10.1007/978-981-10-7455-4
035   $a(CKB)4100000002485538
035   $a(MiAaPQ)EBC5307254
035   $a(DE-He213)978-981-10-7455-4
035   $a(PPN)22463674X
035   $a(EXLCZ)994100000002485538
100   $a20180219d2018      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $2rdacontent
182   $2rdamedia
183   $2rdacarrier
200 10$aSoft Computing for Biological Systems /$fedited by Hemant J. Purohit, Vipin Chandra Kalia, Ravi Prabhakar More
205   $a1st ed. 2018.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2018.
215   $a1 online resource (301 pages) $cillustrations
311   $a981-10-7454-2 
320   $aIncludes bibliographical references at the end of each chapters and index.
327   $a1. 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.
330   $aThis 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.
606   $aBioinformatics
606   $aGene expression
606   $aBiomedical engineering
606   $aMedical genetics
606   $aBioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15001
606   $aGene Expression$3https://scigraph.springernature.com/ontologies/product-market-codes/B12010
606   $aBiomedical Engineering/Biotechnology$3https://scigraph.springernature.com/ontologies/product-market-codes/B24000
606   $aComputational Biology/Bioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23050
606   $aGene Function$3https://scigraph.springernature.com/ontologies/product-market-codes/B12030
615  0$aBioinformatics.
615  0$aGene expression.
615  0$aBiomedical engineering.
615  0$aMedical genetics.
615 14$aBioinformatics.
615 24$aGene Expression.
615 24$aBiomedical Engineering/Biotechnology.
615 24$aComputational Biology/Bioinformatics.
615 24$aGene Function.
676   $a570.285
702   $aPurohit$b Hemant J$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aKalia$b Vipin Chandra$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aMore$b Ravi Prabhakar$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910298425303321
996   $aSoft Computing for Biological Systems$92503041
997   $aUNINA