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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 : 2017-01-13
  • ISBN : 9780128099445
  • Language : En, Es, Fr & De
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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

Protein Function Prediction


Protein Function Prediction
  • Author : Daisuke Kihara
  • Publisher : Humana Press
  • Release : 2017-05-20
  • ISBN : 1493970135
  • Language : En, Es, Fr & De
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This volume presents established bioinformatics tools and databases for function prediction of proteins. Reflecting the diversity of this active field in bioinformatics, the chapters in this book discuss a variety of tools and resources such as sequence-, structure-, systems-, and interaction-based function prediction methods, tools for functional analysis of metagenomics data, detecting moonlighting-proteins, sub-cellular localization prediction, and pathway and comparative genomics databases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step instructions of how to use software and web resources, use cases, and tips on troubleshooting and avoiding known pitfalls. Thorough and cutting-edge, Protein Function Prediction: Methods and Protocols is a valuable and practical guide for using bioinformatics tools for investigating protein function

Protein Function Prediction Methods and Protocols


Protein Function Prediction  Methods and Protocols
  • Author : Daisuke Kihara
  • Publisher : Methods in Molecular Biology
  • Release : 2019-05-12
  • ISBN : 1493983687
  • Language : En, Es, Fr & De
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Sequence based Protein Function Prediction


Sequence based Protein Function Prediction
  • Author : Brett Poulin
  • Publisher :
  • Release : 2004
  • ISBN : OCLC:62408348
  • Language : En, Es, Fr & De
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PROTEIN FUNCTION PREDICTION BA


PROTEIN FUNCTION PREDICTION BA
  • Author : Yatong An
  • Publisher : Open Dissertation Press
  • Release : 2017-01-26
  • ISBN : 1361011637
  • Language : En, Es, Fr & De
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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