Computational Intelligence Techniques for Comparative Genomics Dedicated to Prof. Allam Appa Rao on the Occasion of His 65th Birthday / edited by Naresh Babu Muppalaneni, Vinit Kumar Gunjan.
Contributor(s): Muppalaneni, Naresh Babu., editor literario | Gunjan, Vinit Kumar., editor literario
Material type:
E-bookSeries: (SpringerBriefs in Forensic and Medical Bioinformatics,, 2196-8845); (Engineering (Springer-11647)).Publisher: Singapore : Springer International Publishing, 2015Description: 1 recurso en línea (XVIII, 137 páginas 61 ilustraciones, 41 ilustraciones a color.).ISBN: 9789812873385.Subject: Inteligencia artificial
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | Q342 .C667 2015 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.12112429 |
Diversified Insulin Associated Beta-behavioral & Endogenously Triggered Exposed Symptoms (Diabetes) Model of Diabetes in India -- Automatic Teaching Learning Based Optimization: A Novel Clustering Method For Gene Functional Enrichments -- A Comparative Study of Methodologies of Protein Secondary Structure -- A sparse modeled ROI for GLAM construction in image classification problems - A case study of Breast Cancer -- A Survey on Identification of Protein Complexes in Protein-Protein Interaction Data: Methods and Evaluation -- Modeling Artificial Life: A cellular Automata Approach -- Identification of Deleterious Snps in TACR1 Gene Using Genetic algorithm -- Identification of AIDS Disease Severity Using Genetic Algorithm -- A Novel Clustering Approach Using Hadoop Distributed Environment -- Framework for Evaluation of Programming Language Examinations -- An Efficient Data Integration Framework in Cloud using Map Reduce.
This Brief highlights Informatics and related techniques to Computer Science Professionals, Engineers, Medical Doctors, Bioinformatics researchers and other interdisciplinary researchers. Chapters include the Bioinformatics of Diabetes and several computational algorithms and statistical analysis approach to effectively study the disorders and possible causes along with medical applications.
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