Identification of hub proteins from sequence

Identification of hub proteins from sequence is a challenge in molecular biology. Therefore, it is of interest to predict protein hubs in networks. We describe the prediction of protein “hub” using physiochemical, thermodynamic and conformational properties of amino acid residues in sequence. We hav...

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Detalles Bibliográficos
Autores principales: Latha, Aswathi Balakrishnan, Nair, Achuthsankar Sukumaran, Sivasankaran, Athmaja, Dhar, Pawan Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2011
Materias:
Hypothesis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3218517/
https://www.ncbi.nlm.nih.gov/pubmed/22102772
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author Latha, Aswathi Balakrishnan
Nair, Achuthsankar Sukumaran
Sivasankaran, Athmaja
Dhar, Pawan Kumar
author_facet Latha, Aswathi Balakrishnan
Nair, Achuthsankar Sukumaran
Sivasankaran, Athmaja
Dhar, Pawan Kumar
author_sort Latha, Aswathi Balakrishnan
collection PubMed
description Identification of hub proteins from sequence is a challenge in molecular biology. Therefore, it is of interest to predict protein hubs in networks. We describe the prediction of protein “hub” using physiochemical, thermodynamic and conformational properties of amino acid residues in sequence. We have used twenty sequence based features to identify hub behaviour. Linear discriminant analysis and normalised Bayesian approach were utilized for identifying hub proteins solely using these sequence features in E. coli/H. sapiens datasets with accuracies of 99.5/98.6, 87.8/89.6 and 90.1/92.6, respectively.
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spelling pubmed-32185172011-11-18 Identification of hub proteins from sequence Latha, Aswathi Balakrishnan Nair, Achuthsankar Sukumaran Sivasankaran, Athmaja Dhar, Pawan Kumar Bioinformation Hypothesis Identification of hub proteins from sequence is a challenge in molecular biology. Therefore, it is of interest to predict protein hubs in networks. We describe the prediction of protein “hub” using physiochemical, thermodynamic and conformational properties of amino acid residues in sequence. We have used twenty sequence based features to identify hub behaviour. Linear discriminant analysis and normalised Bayesian approach were utilized for identifying hub proteins solely using these sequence features in E. coli/H. sapiens datasets with accuracies of 99.5/98.6, 87.8/89.6 and 90.1/92.6, respectively. Biomedical Informatics 2011-10-14 /pmc/articles/PMC3218517/ /pubmed/22102772 Text en © 2011 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Hypothesis
Latha, Aswathi Balakrishnan
Nair, Achuthsankar Sukumaran
Sivasankaran, Athmaja
Dhar, Pawan Kumar
Identification of hub proteins from sequence
title Identification of hub proteins from sequence
title_full Identification of hub proteins from sequence
title_fullStr Identification of hub proteins from sequence
title_full_unstemmed Identification of hub proteins from sequence
title_short Identification of hub proteins from sequence
title_sort identification of hub proteins from sequence
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3218517/
https://www.ncbi.nlm.nih.gov/pubmed/22102772
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AT nairachuthsankarsukumaran identificationofhubproteinsfromsequence
AT sivasankaranathmaja identificationofhubproteinsfromsequence
AT dharpawankumar identificationofhubproteinsfromsequence

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