Literature DB >> 18348704

A protein map and its application.

Stephen S-T Yau1, Chenglong Yu, Rong He.   

Abstract

Graphical representation of gene sequences provides a simple way of viewing, sorting, and comparing various gene structures. Here we first report a two-dimensional graphical representation for protein sequences. With this method, we constructed the moment vectors for protein sequences, and mathematically proved that the correspondence between moment vectors and protein sequences is one-to-one. Therefore, each protein sequence can be represented as a point in a map, which we call protein map, and cluster analysis can be used for comparison between the points. Sixty-six proteins from five protein families were analyzed using this method. Our data showed that for proteins in the same family, their corresponding points in the map are close to each other. We also illustrate the efficiency of this approach by performing an extensive cluster analysis of the protein kinase C family. These results indicate that this protein map could be used to mathematically specify the similarity of two proteins and predict properties of an unknown protein based on its amino acid sequence.

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Year:  2008        PMID: 18348704     DOI: 10.1089/dna.2007.0676

Source DB:  PubMed          Journal:  DNA Cell Biol        ISSN: 1044-5498            Impact factor:   3.311


  20 in total

1.  Protein sequence analysis based on hydropathy profile of amino acids.

Authors:  Xiao-li Xie; Li-fei Zheng; Ying Yu; Li-ping Liang; Man-cai Guo; John Song; Zhi-fa Yuan
Journal:  J Zhejiang Univ Sci B       Date:  2012-02       Impact factor: 3.066

2.  An information-based network approach for protein classification.

Authors:  Xiaogeng Wan; Xin Zhao; Stephen S T Yau
Journal:  PLoS One       Date:  2017-03-28       Impact factor: 3.240

3.  Identifying anticancer peptides by using a generalized chaos game representation.

Authors:  Li Ge; Jiaguo Liu; Yusen Zhang; Matthias Dehmer
Journal:  J Math Biol       Date:  2018-10-05       Impact factor: 2.259

4.  A novel construction of genome space with biological geometry.

Authors:  Chenglong Yu; Qian Liang; Changchuan Yin; Rong L He; Stephen S-T Yau
Journal:  DNA Res       Date:  2010-04-01       Impact factor: 4.458

5.  A novel method of characterizing genetic sequences: genome space with biological distance and applications.

Authors:  Mo Deng; Chenglong Yu; Qian Liang; Rong L He; Stephen S-T Yau
Journal:  PLoS One       Date:  2011-03-02       Impact factor: 3.240

6.  FEGS: a novel feature extraction model for protein sequences and its applications.

Authors:  Zengchao Mu; Ting Yu; Xiaoping Liu; Hongyu Zheng; Leyi Wei; Juntao Liu
Journal:  BMC Bioinformatics       Date:  2021-06-03       Impact factor: 3.169

7.  Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences.

Authors:  Kun Tian; Xiaoqian Yang; Qin Kong; Changchuan Yin; Rong L He; Stephen S-T Yau
Journal:  PLoS One       Date:  2015-09-18       Impact factor: 3.240

8.  DFA7, a new method to distinguish between intron-containing and intronless genes.

Authors:  Chenglong Yu; Mo Deng; Lu Zheng; Rong Lucy He; Jie Yang; Stephen S-T Yau
Journal:  PLoS One       Date:  2014-07-18       Impact factor: 3.240

9.  Similarity/Dissimilarity analysis of protein sequences based on a new spectrum-like graphical representation.

Authors:  Yuhua Yao; Shoujiang Yan; Huimin Xu; Jianning Han; Xuying Nan; Ping-An He; Qi Dai
Journal:  Evol Bioinform Online       Date:  2014-06-12       Impact factor: 1.625

10.  Mathematical Characterization of Protein Sequences Using Patterns as Chemical Group Combinations of Amino Acids.

Authors:  Jayanta Kumar Das; Provas Das; Korak Kumar Ray; Pabitra Pal Choudhury; Siddhartha Sankar Jana
Journal:  PLoS One       Date:  2016-12-08       Impact factor: 3.240

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