01758nlm0 22005051i 450 9900092637804033219783642108174000926378FED01000926378(Aleph)000926378FED0100092637820100926d2009----km-y0itay50------baengDEdrnn-008mamaaIntelligent Robotics and ApplicationsRisorsa elettronicaSecond International Conference, ICIRA 2009, Singapore, December 16-18, 2009. Proceedingsedited by Ming Xie, Youlun Xiong, Caihua Xiong, Honghai Liu, Zhencheng HuBerlin ; HeidelbergSpringer2009Lecture Notes in Computer Science0302-97435928Documento elettronicoTestoFormato html, pdfHu,ZhenchengLiu,HonghaiXie,MingXiong,CaihuaXiong,YoulunITUNINAREICATUNIMARCFull text per gli utenti Federico IIhttp://dx.doi.org/10.1007/978-3-642-10817-4EB990009263780403321Artificial intelligenceArtificial Intelligence (incl. Robotics)Computer Imaging, Vision, Pattern Recognition and GraphicsComputer scienceComputer ScienceComputer simulationComputer visionControl, Robotics, MechatronicsOptical pattern recognitionPattern RecognitionRehabilitationRehabilitation MedicineSimulation and ModelingIntelligent Robotics and Applications773722UNINA02344oam 2200493I 450 991016285740332120251107230832.01-4822-5862-51-315-37226-61-4822-5860-910.1201/9781315372266(CKB)3710000001021899(MiAaPQ)EBC4778632(OCoLC)967412430(EXLCZ)99371000000102189920180706h20172017 uy 0engurcnu||||||||rdacontentrdamediardacarrierStatistical modeling and machine learning for molecular biology /Alan Moses, University of Toronto, Canada1st ed.Boca Raton :CRC Press,[2017]©20171 online resourceChapman & Hall/CRC mathematical and computational biology series1-138-40721-6 1-4822-5859-5 section 1. Overview -- section 2. Clustering -- section 3. Regression -- section 4. Classification.Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.Chapman and Hall/CRC mathematical & computational biology series.Molecular biologyStatistical methodsMolecular biologyData processingMolecular biologyStatistical methods.Molecular biologyData processing.572.8Moses Alan M.1855674FlBoTFGFlBoTFGBOOK9910162857403321Statistical modeling and machine learning for molecular biology4453978UNINA