Introduction to machine learning and bioinformatics. (2008)

• Record Type: Book
• Further Information: Note: Sushmita Mitra [and three others].
• Other Names: Mitra, Sushmita, 1962-
• Contents: Introduction ; The Biology of a Living Organism ; Cells; DNA and Genes; Proteins; Metabolism; Biological Regulation Systems: When They Go Awry; Measurement Technologies; Probabilistic and Model-Based Learning ; Introduction: Probabilistic Learning; Basics of Probability; Random Variables and Probability Distributions; Basics of Information Theory; Basics of Stochastic Processes; Hidden Markov Models; Frequentist Statistical Inference; Some Computational Issues; Bayesian Inference; Exercises; Classification Techniques ; Introduction and Problem Formulation; The Framework; Classification Methods; Applications of Classification Techniques to Bioinformatics Problems; Exercises; Unsupervised Learning Techniques ; Introduction; Principal Components Analysis; Multidimensional Scaling; Other Dimension Reduction Techniques; Cluster Analysis Techniques; Exercises; Computational Intelligence in Bioinformatics ; Introduction; Fuzzy Sets; Artificial Neural Networks; Evolutionary Computing; Rough Sets; Hybridization; Application to Bioinformatics; Conclusion; Exercises; Connections ; Sequence Analysis; Analysis of High-Throughput Gene Expression Data; Network Inference; Exercises; Machine Learning in Structural Biology ; Introduction; Background; arp/warp; resolve; textal; acmi; Conclusion; Soft Computing in Biclustering ; Introduction; Biclustering; Multiobjective Biclustering; Fuzzy Possibilistic Biclustering; Experimental Results; Conclusions and Discussion; Bayesian Methods for Tumor Classification ; Introduction; Classification Based on Reproducing Kernel Hilbert Spaces ; Hierarchical Classification Model; Likelihoods of RKHS Models; The Bayesian Analysis; Prediction and Model Choice; Some Examples; Concluding Remarks; Modeling and Analysis of iTRAQ Data ; Introduction; Statistical Modeling of iTRAQ Data; Data Illustration; Discussion and Concluding Remarks; Mass Spectrometry Classification ; Introduction; Background on Proteomics; Classification Methods; Data and Implementation; Results and Discussion; Conclusions; Acknowledgment; Index ; References appear at the end of each chapter.
• Publisher Details: Place of publication not identified : Chapman and Hall/CRC
• Publication Date: 2008
• Extent: 1 online resource, illustrations
• Subjects: 572.80285; Bioinformatics; Machine learning
• Languages: English
• ISBNs: 9781420011784; 1420011782
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.