New Approaches of Protein Function Prediction from Protein Interaction Networks

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  • Author : Jingyu Hou
  • Publisher : Academic Press
  • Pages : 124 pages
  • ISBN : 0128099445
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>New Approaches of Protein Function Prediction from Protein Interaction Networks

Download or Read online New Approaches of Protein Function Prediction from Protein Interaction Networks full in PDF, ePub and kindle. this book written by Jingyu Hou and published by Academic Press which was released on 13 January 2017 with total page 124 pages. We cannot guarantee that New Approaches of Protein Function Prediction from Protein Interaction Networks book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

New Approaches of Protein Function Prediction from Protein Interaction Networks

New Approaches of Protein Function Prediction from Protein Interaction Networks
  • Author : Jingyu Hou
  • Publisher : Academic Press
  • Release : 13 January 2017
GET THIS BOOK New Approaches of Protein Function Prediction from Protein Interaction Networks

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

PROTEIN FUNCTION PREDICTION BA

PROTEIN FUNCTION PREDICTION BA
  • Author : Yatong An,{273a67}亚{275c28}
  • Publisher : Open Dissertation Press
  • Release : 26 January 2017
GET THIS BOOK PROTEIN FUNCTION PREDICTION BA

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

Genome Wide Prediction and Analysis of Protein Protein Functional Linkages in Bacteria

Genome Wide Prediction and Analysis of Protein Protein Functional Linkages in Bacteria
  • Author : Vijaykumar Yogesh Muley,Vishal Acharya
  • Publisher : Springer Science & Business Media
  • Release : 28 July 2012
GET THIS BOOK Genome Wide Prediction and Analysis of Protein Protein Functional Linkages in Bacteria

​​ ​Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.

From Protein Structure to Function with Bioinformatics

From Protein Structure to Function with Bioinformatics
  • Author : Daniel J. Rigden
  • Publisher : Springer
  • Release : 06 April 2017
GET THIS BOOK From Protein Structure to Function with Bioinformatics

This book is about protein structural bioinformatics and how it can help understand and predict protein function. It covers structure-based methods that can assign and explain protein function based on overall folds, characteristics of protein surfaces, occurrence of small 3D motifs, protein-protein interactions and on dynamic properties. Such methods help extract maximum value from new experimental structures, but can often be applied to protein models. The book also, therefore, provides comprehensive coverage of methods for predicting or inferring protein structure,

Function Prediction from Protein Sequence and Protein Structure Comparison

Function Prediction from Protein Sequence and Protein Structure Comparison
  • Author : Harley Coleman
  • Publisher : Createspace Independent Publishing Platform
  • Release : 30 January 2017
GET THIS BOOK Function Prediction from Protein Sequence and Protein Structure Comparison

Most commonly, protein function is inferred from the known functions of homologous proteins. For homologous proteins with easily recognizable sequence similarity, this type of prediction is based on the 'similar sequence-similar structure-similar function' paradigm. - Domains can be seen as 'units of evolution', and, therefore, both structural and functional similarity between proteins needs to be analyzed at the domain level. - Sequence comparison is most sensitive at the protein level and the detection of distantly related sequences is easier in

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
  • Publisher : Unknown
  • Release : 25 October 2021
GET THIS BOOK Protein Function Prediction by Integrating Sequence Structure and Binding Affinity Information

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

Protein Function Prediction for Omics Era

Protein Function Prediction for Omics Era
  • Author : Daisuke Kihara
  • Publisher : Springer Science & Business Media
  • Release : 19 April 2011
GET THIS BOOK Protein Function Prediction for Omics Era

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

Protein Function Prediction from Protein Interaction Network

Protein Function Prediction from Protein Interaction Network
  • Author : Sovan Saha,Piyali Chatterjee
  • Publisher : LAP Lambert Academic Publishing
  • Release : 25 October 2021
GET THIS BOOK Protein Function Prediction from Protein Interaction Network

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

Protein Function Prediction Using Decision Tree Technique

Protein Function Prediction Using Decision Tree Technique
  • Author : Venkata Rama Kumar Swamy Yedida
  • Publisher : Unknown
  • Release : 25 October 2021
GET THIS BOOK Protein Function Prediction Using Decision Tree Technique

The human genome project and numerous other genome projects have produced a large and ever increasing amount of sequence data. One of the main research challenges in the post-genomic era is to understand the relationship between the nucleotide sequences of genes and the functions of the proteins they encode. The objective of this thesis is to develop an automated protein function prediction system that is based on a set of homologous proteins and gene ontology categories. A novel measure based

Network based Information Integration for Protein Function Prediction

Network based Information Integration for Protein Function Prediction
  • Author : Xiaoyu Jiang
  • Publisher : Unknown
  • Release : 25 October 2021
GET THIS BOOK Network based Information Integration for Protein Function Prediction

Abstract: Protein function prediction is a fundamental problem in computational biology. For protein activities described by terms in databases such as the Gene Ontology (GO), this task is typically pursued as a binary classification problem. As a result of an astonishing increase in the available genome-wide protein information, integrating different protein datasets has become a significant opportunity and a major focus to infer functionality. This dissertation contains three novel approaches to integrate popular protein information to classify proteins into functional