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Title: | Statistical machine learning for computational biology |
Authors: | Devika Subramanian |
Issue Date: | 2007 |
Publisher: | Rice University |
Abstract: | The course is the second module of a three module course entitled "Bioinformatics: from sequence to structure". This course focuses on learning statistical models from biological data. Three problems are covered: gene finding, classification of gene expression data, and inferring regulatory networks from mRNA and proteomic data. The computational techniques covered include: HMMs, support vector machines, and structure learning with Bayesian networks. This course is made possible by a curriculum development grant from the NSF. |
link: | http://cnx.org/contents/041eb1d5-6512-489d-81b0-847a8928ab11@2.1/Statistical_machine_learning_f |
Keywords: | Mathematics and StatisticsScience and Technology;bayesian networks;classification of microarray data;computational gene finding;Hidden Markov models;learning regulatory networks from microarray and proteomic data;stasistical machine learning;support vector machines |
Theme: | 教科書-自然科學類 |
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