New Approaches of Protein Function Prediction from Protein Interaction Networks

New Approaches of Protein Function Prediction from Protein Interaction Networks
Author: Jingyu Hou
Publsiher: Academic Press
Total Pages: 124
Release: 2017-01-13
ISBN 10: 0128099445
ISBN 13: 9780128099445
Language: EN, FR, DE, ES & NL

New Approaches of Protein Function Prediction from Protein Interaction Networks Book Review:

New Approaches of Protein Function Prediction from Protein Interaction Networks contains the critical aspects of PPI network based protein function prediction, including semantically assessing the reliability of PPI data, measuring the functional similarity between proteins, dynamically selecting prediction domains, predicting functions, and establishing corresponding prediction frameworks. Functional annotation of proteins is vital to biological and clinical research and other applications due to the important roles proteins play in various biological processes. Although the functions of some proteins have been annotated via biological experiments, there are still many proteins whose functions are yet to be annotated due to the limitations of existing methods and the high cost of experiments. To overcome experimental limitations, this book helps users understand the computational approaches that have been rapidly developed for protein function prediction. Provides innovative approaches and new developments targeting key issues in protein function prediction Presents heuristic ideas for further research in this challenging area

Prediction of Protein Structures Functions and Interactions

Prediction of Protein Structures  Functions  and Interactions
Author: Janusz M. Bujnicki
Publsiher: John Wiley & Sons
Total Pages: 302
Release: 2008-12-23
ISBN 10: 9780470741900
ISBN 13: 0470741902
Language: EN, FR, DE, ES & NL

Prediction of Protein Structures Functions and Interactions Book Review:

The growing flood of new experimental data generated by genome sequencing has provided an impetus for the development of automated methods for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction of Protein Structures, Functions and Interactions presents a comprehensive overview of methods for prediction of protein structure or function, with the emphasis on their availability and possibilities for their combined use. Methods of modeling of individual proteins, prediction of their interactions, and docking of complexes are put in the context of predicting gene ontology (biological process, molecular function, and cellular component) and discussed in the light of their contribution to the emerging field of systems biology. Topics covered include: first steps of protein sequence analysis and structure prediction automated prediction of protein function from sequence template-based prediction of three-dimensional protein structures: fold-recognition and comparative modelling template-free prediction of three-dimensional protein structures quality assessment of protein models prediction of molecular interactions: from small ligands to large protein complexes macromolecular docking integrating prediction of structure, function, and interactions Prediction of Protein Structures, Functions and Interactions focuses on the methods that have performed well in CASPs, and which are constantly developed and maintained, and are freely available to academic researchers either as web servers or programs for local installation. It is an essential guide to the newest, best methods for prediction of protein structure and functions, for researchers and advanced students working in structural bioinformatics, protein chemistry, structural biology and drug discovery.

Introduction to Protein Structure Prediction

Introduction to Protein Structure Prediction
Author: Huzefa Rangwala,George Karypis
Publsiher: John Wiley & Sons
Total Pages: 520
Release: 2011-03-16
ISBN 10: 9781118099469
ISBN 13: 111809946X
Language: EN, FR, DE, ES & NL

Introduction to Protein Structure Prediction Book Review:

A look at the methods and algorithms used to predict proteinstructure A thorough knowledge of the function and structure of proteinsis critical for the advancement of biology and the life sciences aswell as the development of better drugs, higher-yield crops, andeven synthetic bio-fuels. To that end, this reference sheds lighton the methods used for protein structure prediction and revealsthe key applications of modeled structures. This indispensable bookcovers the applications of modeled protein structures and unravelsthe relationship between pure sequence information andthree-dimensional structure, which continues to be one of thegreatest challenges in molecular biology. With this resource, readers will find an all-encompassingexamination of the problems, methods, tools, servers, databases,and applications of protein structure prediction and they willacquire unique insight into the future applications of the modeledprotein structures. The book begins with a thorough introduction tothe protein structure prediction problem and is divided into fourthemes: a background on structure prediction, the prediction ofstructural elements, tertiary structure prediction, and functionalinsights. Within those four sections, the following topics arecovered: Databases and resources that are commonly used for proteinstructure prediction The structure prediction flagship assessment (CASP) and theprotein structure initiative (PSI) Definitions of recurring substructures and the computationalapproaches used for solving sequence problems Difficulties with contact map prediction and how sophisticatedmachine learning methods can solve those problems Structure prediction methods that rely on homology modeling,threading, and fragment assembly Hybrid methods that achieve high-resolution proteinstructures Parts of the protein structure that may be conserved and usedto interact with other biomolecules How the loop prediction problem can be used for refinement ofthe modeled structures The computational model that detects the differences betweenprotein structure and its modeled mutant Whether working in the field of bioinformatics or molecularbiology research or taking courses in protein modeling, readerswill find the content in this book invaluable.

Homology Molecular Modeling

Homology Molecular Modeling
Author: Rafael Trindade Maia,Rômulo Maciel de Moraes Filho,Magnólia De Araújo Campos
Publsiher: BoD – Books on Demand
Total Pages: 146
Release: 2021-03-10
ISBN 10: 1839628057
ISBN 13: 9781839628054
Language: EN, FR, DE, ES & NL

Homology Molecular Modeling Book Review:

Homology modeling is an extremely useful and versatile technique that is gaining more and more space and demand in research in computational and theoretical biology. This book, “Homology Molecular Modeling - Perspectives and Applications”, brings together unpublished chapters on this technique. In this book, 7 chapters are intimately related to the theme of molecular modeling, carefully selected and edited for academic and scientific readers. It is an indispensable read for anyone interested in the areas of bioinformatics and computational biology. Divided into 4 sections, the reader will have a didactic and comprehensive view of the theme, with updated and relevant concepts on the subject. This book was organized from researchers to researchers with the aim of spreading the fascinating area of molecular modeling by homology.

Sequence based Protein Function Prediction

Sequence based Protein Function Prediction
Author: Brett Poulin
Publsiher: Unknown
Total Pages: 180
Release: 2004
ISBN 10: 1928374650XXX
ISBN 13: OCLC:62408348
Language: EN, FR, DE, ES & NL

Sequence based Protein Function Prediction Book Review:

Essential Bioinformatics

Essential Bioinformatics
Author: Jin Xiong
Publsiher: Cambridge University Press
Total Pages: 135
Release: 2006-03-13
ISBN 10: 113945062X
ISBN 13: 9781139450621
Language: EN, FR, DE, ES & NL

Essential Bioinformatics Book Review:

Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

Molecular Biology of the Cell

Molecular Biology of the Cell
Author: Bruce Alberts
Publsiher: Unknown
Total Pages: 135
Release: 2004
ISBN 10: 9780815332183
ISBN 13: 0815332181
Language: EN, FR, DE, ES & NL

Molecular Biology of the Cell Book Review:

Protein Bioinformatics

Protein Bioinformatics
Author: M. Michael Gromiha
Publsiher: Academic Press
Total Pages: 339
Release: 2011-04-21
ISBN 10: 0123884241
ISBN 13: 9780123884244
Language: EN, FR, DE, ES & NL

Protein Bioinformatics Book Review:

One of the most pressing tasks in biotechnology today is to unlock the function of each of the thousands of new genes identified every day. Scientists do this by analyzing and interpreting proteins, which are considered the task force of a gene. This single source reference covers all aspects of proteins, explaining fundamentals, synthesizing the latest literature, and demonstrating the most important bioinformatics tools available today for protein analysis, interpretation and prediction. Students and researchers of biotechnology, bioinformatics, proteomics, protein engineering, biophysics, computational biology, molecular modeling, and drug design will find this a ready reference for staying current and productive in this fast evolving interdisciplinary field. Explains all aspects of proteins including sequence and structure analysis, prediction of protein structures, protein folding, protein stability, and protein interactions Presents a cohesive and accessible overview of the field, using illustrations to explain key concepts and detailed exercises for students.

Protein Function Prediction for Omics Era

Protein Function Prediction for Omics Era
Author: Daisuke Kihara
Publsiher: Springer Science & Business Media
Total Pages: 310
Release: 2011-04-19
ISBN 10: 9400708815
ISBN 13: 9789400708815
Language: EN, FR, DE, ES & NL

Protein Function Prediction for Omics Era Book Review:

Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred

Prediction of Protein Function Using Text Features Extracted from the Biomedical Literature

Prediction of Protein Function Using Text Features Extracted from the Biomedical Literature
Author: Andrew Wong
Publsiher: Unknown
Total Pages: 166
Release: 2013
ISBN 10: 1928374650XXX
ISBN 13: OCLC:845228440
Language: EN, FR, DE, ES & NL

Prediction of Protein Function Using Text Features Extracted from the Biomedical Literature Book Review:

Proteins perform many important functions in the cell and are essential to the health of the cell and the organism. As such, there is much effort to understand the function of proteins. Due to the advances in sequencing technology, there are many sequences of proteins whose function is yet unknown. Therefore, computational systems are being developed and used to help predict protein function. Most computational systems represent proteins using features that are derived from protein sequence or protein structure to predict function. In contrast, there are very few systems that use the biomedical literature as a source of features. Earlier work demonstrated the utility of biomedical literature as a source of text features for predicting protein subcellular location. In this thesis we build on that earlier work, and examine the effectiveness of using text features to predict protein function. Using the molecular function and biological process terms from the Gene Ontology (GO) as our function classes, we trained two classifiers (k-Nearest Neighbour and Support Vector Machines) to predict protein function. The proteins were represented using text features that were extracted from biomedical abstracts based on statistical properties. For evaluation, the performance of our two classifiers was compared to that of two baseline classifiers: one that assigns function based solely on the prior distribution of protein function, and one that assigns function based on sequence similarity. The systems were trained and tested using 5-fold cross-validation over a dataset of more than 36,000 proteins. Overall, we show that text features extracted from biomedical literature can be used to predict protein function for any organism. Our results also show that our text-based classifier typically has comparable performance to the sequence-similarity baseline classifier. Based on our results and what previous work had shown, we believe that text features can be integrated with other types of features to provide more accurate predictions for protein function.

Applied Bioinformatics

Applied Bioinformatics
Author: Paul Maria Selzer,Richard Marhöfer,Andreas Rohwer
Publsiher: Springer Science & Business Media
Total Pages: 287
Release: 2008-01-18
ISBN 10: 3540728007
ISBN 13: 9783540728009
Language: EN, FR, DE, ES & NL

Applied Bioinformatics Book Review:

At last, here is a baseline book for anyone who is confused by cryptic computer programs, algorithms and formulae, but wants to learn about applied bioinformatics. Now, anyone who can operate a PC, standard software and the internet can also learn to understand the biological basis of bioinformatics, of the existence as well as the source and availability of bioinformatics software, and how to apply these tools and interpret results with confidence. This process is aided by chapters that introduce important aspects of bioinformatics, detailed bioinformatics exercises (including solutions), and to cap it all, a glossary of definitions and terminology relating to bioinformatics.

Protein Function Prediction Methods and Protocols

Protein Function Prediction  Methods and Protocols
Author: Daisuke Kihara
Publsiher: Methods in Molecular Biology
Total Pages: 252
Release: 2019-05-12
ISBN 10: 9781493983681
ISBN 13: 1493983687
Language: EN, FR, DE, ES & NL

Protein Function Prediction Methods and Protocols Book Review:

PROTEIN FUNCTION PREDICTION BA

PROTEIN FUNCTION PREDICTION BA
Author: Yatong An,{273a67}亚{275c28}
Publsiher: Open Dissertation Press
Total Pages: 80
Release: 2017-01-26
ISBN 10: 9781361011638
ISBN 13: 1361011637
Language: EN, FR, DE, ES & NL

PROTEIN FUNCTION PREDICTION BA Book Review:

This dissertation, "Protein Function Prediction Based on Pocket-specific Noncontiguous Amino Acid Subsequences" by Yatong, An, {273a67}亚{275c28}, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Building a protein functional repertoire is important for many life sciences. Unfortunately, less than 1% of protein sequences have been annotated with reliable evidence. The use of computational methods to predict protein functions has become a common means to bridge this formidable gap. In this thesis, it is proposed to use pocket-specific noncontiguous amino acid subsequences for predicting protein functions. These subsequence patterns have a strong function classification capability and are also complementary to protein sequence alignment methods. On the basis of a benchmark of ∼1600 testing proteins from the Protein Data Bank (PDB), It is demonstrated that function prediction using pocket-specific noncontiguous amino acid subsequences can be much more accurate than using three-dimensional pocket structures. Because these noncontiguous amino acid subsequences are independent of protein or pocket structures, the method based on such subsequence patterns can be easily applied to proteins with unknown structures. Predictors achieve state-of-the-art performance on two benchmarks constructed using proteins from the PDB and SwissProt respectively. Then protein sequence alignment features are further integrated into our pocket-specific noncontiguous subsequence model. The maximum F-measure of the integrated predictor on the PDB-based benchmark is 0.844 for the molecular function (MF) ontology and 0.838 for the biological process (BP) ontology, representing respective performance improvements of 47.8% and 48.3% over best results achieved with existing methods. On the SwissProt-based benchmark, the maximum Fmeasure of the integrated predictor is 0.627 for MF and 0.468 for BP, representing respective performance improvements of 29.0% and 38.1% over best results achieved with existing methods. Subjects: Amino acid sequence Proteomics - Data processing

From Protein Structure to Function with Bioinformatics

From Protein Structure to Function with Bioinformatics
Author: Daniel John Rigden
Publsiher: Springer Science & Business Media
Total Pages: 328
Release: 2008-12-11
ISBN 10: 1402090587
ISBN 13: 9781402090585
Language: EN, FR, DE, ES & NL

From Protein Structure to Function with Bioinformatics Book Review:

Proteins lie at the heart of almost all biological processes and have an incredibly wide range of activities. Central to the function of all proteins is their ability to adopt, stably or sometimes transiently, structures that allow for interaction with other molecules. An understanding of the structure of a protein can therefore lead us to a much improved picture of its molecular function. This realisation has been a prime motivation of recent Structural Genomics projects, involving large-scale experimental determination of protein structures, often those of proteins about which little is known of function. These initiatives have, in turn, stimulated the massive development of novel methods for prediction of protein function from structure. Since model structures may also take advantage of new function prediction algorithms, the first part of the book deals with the various ways in which protein structures may be predicted or inferred, including specific treatment of membrane and intrinsically disordered proteins. A detailed consideration of current structure-based function prediction methodologies forms the second part of this book, which concludes with two chapters, focusing specifically on case studies, designed to illustrate the real-world application of these methods. With bang up-to-date texts from world experts, and abundant links to publicly available resources, this book will be invaluable to anyone who studies proteins and the endlessly fascinating relationship between their structure and function.

Protein Function Prediction by Integrating Sequence Structure and Binding Affinity Information

Protein Function Prediction by Integrating Sequence  Structure and Binding Affinity Information
Author: Huiying Zhao
Publsiher: Unknown
Total Pages: 354
Release: 2013
ISBN 10: 1928374650XXX
ISBN 13: OCLC:869742922
Language: EN, FR, DE, ES & NL

Protein Function Prediction by Integrating Sequence Structure and Binding Affinity Information Book Review:

Proteins are nano-machines that work inside every living organism. Functional disruption of one or several proteins is the cause for many diseases. However, the functions for most proteins are yet to be annotated because inexpensive sequencing techniques dramatically speed up discovery of new protein sequences (265 million and counting) and experimental examinations of every protein in all its possible functional categories are simply impractical. Thus, it is necessary to develop computational function-prediction tools that complement and guide experimental studies. In this study, we developed a series of predictors for highly accurate prediction of proteins with DNA-binding, RNA-binding and carbohydrate-binding capability. These predictors are a template-based technique that combines sequence and structural information with predicted binding affinity. Both sequence and structure-based approaches were developed. Results indicate the importance of binding affinity prediction for improving sensitivity and precision of function prediction. Application of these methods to the human genome and structure genome targets demonstrated its usefulness in annotating proteins of unknown functions and discovering moon-lighting proteins with DNA, RNA, or carbohydrate binding function. In addition, we also investigated disruption of protein functions by naturally occurring genetic variations due to insertions and deletions (INDELS). We found that protein structures are the most critical features in recognising disease-causing non-frame shifting INDELs. The predictors for function predictions are available at http://sparks-lab.org/spot, and the predictor for classification of non-frame shifting INDELs is available at http://sparks-lab.org/ddig.

Feature Representation and Learning Methods With Applications in Protein Secondary Structure

Feature Representation and Learning Methods With Applications in Protein Secondary Structure
Author: Zhibin Lv,Hong Wenjing,Xue Xu
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2021-10-25
ISBN 10: 2889715558
ISBN 13: 9782889715558
Language: EN, FR, DE, ES & NL

Feature Representation and Learning Methods With Applications in Protein Secondary Structure Book Review:

Protein Structure Prediction

Protein Structure Prediction
Author: Daisuke Kihara
Publsiher: Unknown
Total Pages: 358
Release: 2020
ISBN 10: 9781071607084
ISBN 13: 1071607081
Language: EN, FR, DE, ES & NL

Protein Structure Prediction Book Review:

Protein Function Prediction from Protein Interaction Network

Protein Function Prediction from Protein Interaction Network
Author: Sovan Saha,Piyali Chatterjee
Publsiher: LAP Lambert Academic Publishing
Total Pages: 148
Release: 2013
ISBN 10: 9783659402784
ISBN 13: 3659402788
Language: EN, FR, DE, ES & NL

Protein Function Prediction from Protein Interaction Network Book Review:

Proteins perform every function in a cell. With the advent of genome sequencing projects for different organisms, large amounts of DNA and protein sequence data is available, whereas their biological function is still unknown in the most of the cases. Predicting protein function is the most challenging problem in post-genomic era. Using sequence homology, phylogenetic profiles, gene expression data, and function of unknown protein can be predicted. Recently, the large interaction networks constructed from high throughput techniques like Yeast2Hybrid experiments are also used in prediction of protein function. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Based on the concept that a protein performs similar function like its neighbor in protein interaction network, a method is proposed to predict protein function using protein-protein interaction data.This analysis should enlighten the path for predicting unannotated protein function hence identifying diseases and inventing methods of it's cureness.

Bioinformatics Sequences Structures Phylogeny

Bioinformatics  Sequences  Structures  Phylogeny
Author: Asheesh Shanker
Publsiher: Springer
Total Pages: 402
Release: 2018-10-13
ISBN 10: 9811315620
ISBN 13: 9789811315626
Language: EN, FR, DE, ES & NL

Bioinformatics Sequences Structures Phylogeny Book Review:

This book provides a comprehensive overview of the concepts and approaches used for sequence, structure, and phylogenetic analysis. Starting with an introduction to the subject and intellectual property protection for bioinformatics, it guides readers through the latest sequencing technologies, sequence analysis, genomic variations, metagenomics, epigenomics, molecular evolution and phylogenetics, structural bioinformatics, protein folding, structure analysis and validation, drug discovery, reverse vaccinology, machine learning, application of R programming in biological data analysis, and the use of Linux in handling large data files.

Prediction of Protein Structure and the Principles of Protein Conformation

Prediction of Protein Structure and the Principles of Protein Conformation
Author: G.D. Fasman
Publsiher: Springer Science & Business Media
Total Pages: 798
Release: 2012-12-06
ISBN 10: 1461315719
ISBN 13: 9781461315711
Language: EN, FR, DE, ES & NL

Prediction of Protein Structure and the Principles of Protein Conformation Book Review:

The prediction of the conformation of proteins has developed from an intellectual exercise into a serious practical endeavor that has great promise to yield new stable enzymes, products of pharmacological significance, and catalysts of great potential. With the application of predic tion gaining momentum in various fields, such as enzymology and immunology, it was deemed time that a volume be published to make available a thorough evaluation of present methods, for researchers in this field to expound fully the virtues of various algorithms, to open the field to a wider audience, and to offer the scientific public an opportunity to examine carefully its successes and failures. In this manner the practitioners of the art could better evaluate the tools and the output so that their expectations and applications could be more realistic. The editor has assembled chapters by many of the main contributors to this area and simultaneously placed their programs at three national resources so that they are readily available to those who wish to apply them to their personal interests. These algorithms, written by their originators, when utilized on pes or larger computers, can instantaneously take a primary amino acid sequence and produce a two-or three-dimensional artistic image that gives satisfaction to one's esthetic sensibilities and food for thought concerning the structure and function of proteins. It is in this spirit that this volume was envisaged.