MARC Record from Library of Congress

LEADER: 03128nam a2200421 a 4500
001 2012933773
003 DLC
005 20120619153131.0
008 120221s2012 gw a b 001 0 eng c
010 $a 2012933773
016 7 $a101584022$2DNLM
016 7 $a015987263$2Uk
020 $a9783642272240 (alk. paper)
020 $a364227224X (alk. paper)
020 $a9783642272257 (e-ISBN)
020 $a3642272258 (e-ISBN)
035 $a(OCoLC)ocn795366045
040 $aNLM$beng$cNLM$dBTCTA$dUKMGB$dCDX$dOHX$dYDXCP$dBWX$dIXA$dDLC
042 $apcc
050 00 $aQH324.2$b.B389 2012
060 00 $a2012 D-765
060 10 $aQD 461
072 7 $aQH$2lcco
072 7 $aQA$2lcco
245 00 $aBayesian methods in structural bioinformatics /$cThomas Hamelryck, Kanti Mardia, Jesper Ferkinghoff-Borg, editors.
260 $aHeidelberg ;$aNew York :$bSpringer,$cc2012.
300 $axxii, 385 p. :$bill. ;$c24 cm.
490 1 $aStatistics for biology and health,$x1431-8776
504 $aIncludes bibliographical references (p. 343-376) and index.
505 00 $gPart 1.$tFoundations --$tAn Overview of Bayesian Inference and Graphical Models /$rThomas Hamelryck --$tMonte Carlo Methods for Inference in High-Dimensional Systems /$rJesper Ferkinghoff-Borg --$gPart 2.$tEnergy Functions for Protein Structure Prediction --$tOn the Physical Relevance and Statistical Interpretation of Knowledge-Based Potentials /$rMikael Borg, Thomas Hamelryck and Jesper Ferkinghoff-Borg --$tTowards a General Probabilistic Model of Protein Structure: The Reference Ratio Method /$rJes Frellsen, Kanti V. Mardia, Mikael Borg, Jesper Ferkinghoff-Borg and Thomas Hamelryck --$tInferring Knowledge Based Potentials Using Contrastive Divergence /$rAlexei A. Podtelezhnikov and David L. Wild --$gPart 3.$tDirectional statistics for biomolecular structure --$tStatistics of Bivariate von Mises Distributions /$rKanti V. Mardia and Jes Frellsen --$tStatistical Modelling and Simulation Using the Fisher-Bingham Distribution /$rJohn T. Kent --$gPart 4.$tShape Theory for Protein Structure Superposition --$tLikelihood and Empirical Bayes Superposition of Multiple Macromolecular Structures /$rDouglas L. Theobald --$tBayesian Hierarchical Alignment Methods /$rKanti V. Mardia and Vysaul B. Nyirongo --$gPart 5.$tGraphical models for structure prediction --$tProbabilistic Models of Local Biomolecular Structure and Their Applications /$rWouter Boomsma, Jes Frellsen and Thomas Hamelryck --$tPrediction of Low Energy Protein Side Chain Configurations Using Markov Random Fields /$rChen Yanover and Menachem Fromer --$gPart 6.$tInferring Structure from Experimental Data --$tInferential Structure Determination from NMR Data /$rMichael Habeck --$tBayesian Methods in SAXS and SANS Structure Determination /$rSteen Hansen.
650 0 $aStructural bioinformatics$xStatistical methods.
650 12 $aMolecular Structure.
650 22 $aBayes Theorem.
650 22 $aModels, Statistical.
700 1 $aHamelryck, Thomas.
700 1 $aMardia, K. V.
700 1 $aFerkinghoff-Borg, Jesper.
830 0 $aStatistics for biology and health.$x1431-8776