Probabilistic Protein Homology Modeling
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Probabilistic Protein Homology Modeling
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Author : Armin Jonathan Olaf Meier
language : en
Publisher:
Release Date : 2014
Probabilistic Protein Homology Modeling written by Armin Jonathan Olaf Meier and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Probabilistic Protein Homology Modeling
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Author :
language : en
Publisher:
Release Date : 2014
Probabilistic Protein Homology Modeling written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Probabilistic Protein Homology Modeling
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Author : Armin Jonathan Olaf Meier
language : en
Publisher:
Release Date : 2014
Probabilistic Protein Homology Modeling written by Armin Jonathan Olaf Meier and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
A Probabilistic Approach For Protein Structure Prediction And Protein Homology Identification
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Author : Lihua Yu
language : en
Publisher:
Release Date : 1999
A Probabilistic Approach For Protein Structure Prediction And Protein Homology Identification written by Lihua Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Amino acid sequence categories.
Invitation To Protein Sequence Analysis Through Probability And Information
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Author : Daniel J. Graham
language : en
Publisher: CRC Press
Release Date : 2019-02-06
Invitation To Protein Sequence Analysis Through Probability And Information written by Daniel J. Graham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-06 with Science categories.
This book explores the remarkable information correspondences and probability structures of proteins. Correspondences are pervasive in biochemistry and bioinformatics: proteins share homologies, folding patterns, and mechanisms. Probability structures are just as paramount: folded state graphics reflect Angstrom-scale maps of electron density. The author explores protein sequences (primary structures), both individually and in sets (systems) with the help of probability and information tools. This perspective will enhance the reader’s knowledge of how an important class of molecules is designed and put to task in natural systems, and how we can approach class members in hands-on ways.
Biological Sequence Analysis
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Author : Richard Durbin
language : en
Publisher:
Release Date : 1998
Biological Sequence Analysis written by Richard Durbin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Amino acid sequence categories.
Presents up-to-date computer methods for analysing DNA, RNA and protein sequences.
Protein Structure Prediction
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Author : Mohammed Zaki
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-12
Protein Structure Prediction written by Mohammed Zaki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-12 with Science categories.
This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure. This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.
Modeling Of Proteins And Protein Protein Interactions With Probabilistic Graphical Models
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Author : Bornika Ghosh
language : en
Publisher:
Release Date : 2011
Modeling Of Proteins And Protein Protein Interactions With Probabilistic Graphical Models written by Bornika Ghosh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Graphical modeling (Statistics) categories.
Probabilistic Modeling In Bioinformatics And Medical Informatics
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Author : Dirk Husmeier
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-06
Probabilistic Modeling In Bioinformatics And Medical Informatics written by Dirk Husmeier and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-06 with Computers categories.
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.
Probabilistic Graphical Models For Protein Structure Prediction
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Author : Debswapna Bhattacharya
language : en
Publisher:
Release Date : 2016
Probabilistic Graphical Models For Protein Structure Prediction written by Debswapna Bhattacharya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Computationally predicting the folded and functional three-dimensional structure of a protein molecule from its amino acid sequence with high degree of accuracy is critically important in structural bioinformatics and has huge implications in understanding and curing numerous diseases caused by protein misfolding, including CJD and type II diabetes, as well as neurodegenerative diseases like Alzheimer's, Parkinson's, Huntington's, and amyotrophic lateral sclerosis. Existing computational approaches for protein structure prediction faces two key challenges: (1) difficulty in efficiently navigating the enormous conformational space accessible to proteins and (2) difficulty in accurately capturing energetics of the complex interactions of thousand of atoms in a protein molecule in silico. This dissertation attempts to address these challenges by (1) developing novel probabilistic graphical models and experimentally motivated probabilistic sampling techniques to fully capture and efficiently explore proteins' conformational space in various granularities and (2) integrating knowledge-based information into existing energy functions in order to improve their ability to discriminate correctly folded protein structures from decoys. We show that our methods outperform many traditional and state-of-the-art protein structure prediction approaches in terms of accuracy, speed and robustness. All of these methods are freely available to the scientific community.