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Title: A topological approach for protein classification

Abstract

Here, protein function and dynamics are closely related to its sequence and structure. However, prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity between proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics.

Authors:
 [1];  [2];  [1];  [1];  [1];  [3]
+ Show Author Affiliations
  1. Michigan State Univ., East Lansing, MI (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. The Ohio State Univ., Columbus, OH (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1267039
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Molecular Based Mathematical Biology
Additional Journal Information:
Journal Volume: 3; Journal Issue: 1; Journal ID: ISSN 2299-3266
Publisher:
de Gruyter
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; persistent homology; machine learning; protein classification; topological fingerprint

Citation Formats

Cang, Zixuan, Mu, Lin, Wu, Kedi, Opron, Kristopher, Xia, Kelin, and Wei, Guo -Wei. A topological approach for protein classification. United States: N. p., 2015. Web. doi:10.1515/mlbmb-2015-0009.
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Cang, Zixuan, Mu, Lin, Wu, Kedi, Opron, Kristopher, Xia, Kelin, & Wei, Guo -Wei. A topological approach for protein classification. United States. doi:10.1515/mlbmb-2015-0009.
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Cang, Zixuan, Mu, Lin, Wu, Kedi, Opron, Kristopher, Xia, Kelin, and Wei, Guo -Wei. Wed . "A topological approach for protein classification". United States. doi:10.1515/mlbmb-2015-0009. https://www.osti.gov/servlets/purl/1267039.
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@article{osti_1267039,
title = {A topological approach for protein classification},
author = {Cang, Zixuan and Mu, Lin and Wu, Kedi and Opron, Kristopher and Xia, Kelin and Wei, Guo -Wei},
abstractNote = {Here, protein function and dynamics are closely related to its sequence and structure. However, prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity between proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics.},
doi = {10.1515/mlbmb-2015-0009},
journal = {Molecular Based Mathematical Biology},
number = 1,
volume = 3,
place = {United States},
year = {2015},
month = {11}
}
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DOI:  10.1515/mlbmb-2015-0009
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    Works referencing / citing this record:

    Non-empirical identification of trigger sites in heterogeneous processes using persistent homology
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    Non-empirical identification of trigger sites in heterogeneous processes using persistent homology
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    On the expectation of a persistence diagram by the persistence weighted kernel
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