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Computational Intelligence Methods for Bioinformatics and Biostatistics

Computational Intelligence Methods for Bioinformatics and Biostatistics

          
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About the Book

Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic.- Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Genomic Data: Two Examples from Rare Genetic Diseases and Infectious Diseases.- Bayesian Models for the Multi-sample Time-Course Microarray Experiments.- A Machine Learning Pipeline for Discriminant Pathways Identification.- Discovering Hidden Pathways in Bioinformatics.- Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models.- A Bioinformatics Procedure to Identify and Annotate Somatic Mutations in Whole-Exome Sequencing Data.- Feature Selection for the Prediction and Visualization of Brain Tumor Types Using Proton Magnetic Resonance Spectroscopy Data.- On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statins.- Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biomedical Knowledge Discovery.- Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins.- Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree.- DEEN: A Simple and Fast Algorithm for Network Community Detection.- Self-similarity in Physiological Time Series: New Perspectives from the Temporal Spectrum of Scale Exponents.- Support Vector Machines for Survival Regression.- Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Prediction.- A Faster Algorithm for Motif Finding in Sequences from ChIP-Seq Data.- Case/Control Prediction from Illumina Methylation Microarray's β and Two-Color Channels in the Presence of Batch Effects.- Supporting the Design, Communication and Management of Bioinformatic Protocols through the Leaf Tool.- Genomic Annotation Prediction Based on Integrated Information.- Solving Biclustering with a GRASP-Like Metaheuristic: Two Case-Studies on Gene Expression Analysis.


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Product Details
  • ISBN-13: 9783642356858
  • Publisher: Springer Verlag
  • Binding: Paperback
  • Height: 234 mm
  • No of Pages: 270
  • Series Title: Lecture Notes in Computer Science / Lecture Notes in Bioinformatics
  • Sub Title: 8th International Meeting, Cibb 2011, Gargnano del Garda, Italy, June 30 - July 2, 2011, Revised Selected Papers
  • Width: 156 mm
  • ISBN-10: 3642356850
  • Publisher Date: 22 Nov 2012
  • Depth: 19
  • Language: English
  • Returnable: Y
  • Spine Width: 15 mm
  • Weight: 409 gr


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