Guilt-by association approach to identify novel human aging-related genes using protein domains

Jasjit K. Banwait, Schuyler P. Dougherty, Ishwor Thapa, Dhundy Raj Bastola

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Elucidating the genetic reasons associated with aging and longevity could greatly help in designing strategies to extend years of healthy life in humans. Extensive studies have been carried out in model organisms to find the effect of genes on aging. Understandably, human aging is difficult to research due to the complexity of the processes involved in aging, along with the time and ethical constraints associated with the human life. In spite of these constraints, the Human Ageing Genomic Resources (HAGR) has compiled the GenAge database, a curated list of aging related genes in humans and model organisms using information from published literature. We hypothesized that biological feature-based data mining approaches can overcome the existing limitations associated with human aging research. In this study we develop a computational method to identify aging related human genes that may play a potential role in aging and life span related processes. We employed protein domain information and guilt-by association approach to predict potential aging related genes, which resulted into the identification of twenty-seven novel human aging related genes.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Editorslng. Matthieu Schapranow, Jiayu Zhou, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Satoru Miyano, Illhoi Yoo, Brian Pierce, Amarda Shehu, Vijay K. Gombar, Brian Chen, Vinay Pai, Jun Huan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages301-304
Number of pages4
ISBN (Electronic)9781467367981
DOIs
StatePublished - Dec 16 2015
EventIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States
Duration: Nov 9 2015Nov 12 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015

Other

OtherIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
CountryUnited States
CityWashington
Period11/9/1511/12/15

Fingerprint

Guilt
Genes
Aging of materials
Proteins
Data Mining
Protein Domains
Research
Computational methods
Databases
Data mining

Keywords

  • Protein domains
  • aging
  • bioinformatics
  • guilt-by association
  • network analysis

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Health Informatics
  • Biomedical Engineering

Cite this

Banwait, J. K., Dougherty, S. P., Thapa, I., & Bastola, D. R. (2015). Guilt-by association approach to identify novel human aging-related genes using protein domains. In L. M. Schapranow, J. Zhou, X. T. Hu, B. Ma, S. Rajasekaran, S. Miyano, I. Yoo, B. Pierce, A. Shehu, V. K. Gombar, B. Chen, V. Pai, ... J. Huan (Eds.), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 (pp. 301-304). [7359698] (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2015.7359698

Guilt-by association approach to identify novel human aging-related genes using protein domains. / Banwait, Jasjit K.; Dougherty, Schuyler P.; Thapa, Ishwor; Bastola, Dhundy Raj.

Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. ed. / lng. Matthieu Schapranow; Jiayu Zhou; Xiaohua Tony Hu; Bin Ma; Sanguthevar Rajasekaran; Satoru Miyano; Illhoi Yoo; Brian Pierce; Amarda Shehu; Vijay K. Gombar; Brian Chen; Vinay Pai; Jun Huan. Institute of Electrical and Electronics Engineers Inc., 2015. p. 301-304 7359698 (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Banwait, JK, Dougherty, SP, Thapa, I & Bastola, DR 2015, Guilt-by association approach to identify novel human aging-related genes using protein domains. in LM Schapranow, J Zhou, XT Hu, B Ma, S Rajasekaran, S Miyano, I Yoo, B Pierce, A Shehu, VK Gombar, B Chen, V Pai & J Huan (eds), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015., 7359698, Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, Institute of Electrical and Electronics Engineers Inc., pp. 301-304, IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, Washington, United States, 11/9/15. https://doi.org/10.1109/BIBM.2015.7359698
Banwait JK, Dougherty SP, Thapa I, Bastola DR. Guilt-by association approach to identify novel human aging-related genes using protein domains. In Schapranow LM, Zhou J, Hu XT, Ma B, Rajasekaran S, Miyano S, Yoo I, Pierce B, Shehu A, Gombar VK, Chen B, Pai V, Huan J, editors, Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 301-304. 7359698. (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015). https://doi.org/10.1109/BIBM.2015.7359698
Banwait, Jasjit K. ; Dougherty, Schuyler P. ; Thapa, Ishwor ; Bastola, Dhundy Raj. / Guilt-by association approach to identify novel human aging-related genes using protein domains. Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. editor / lng. Matthieu Schapranow ; Jiayu Zhou ; Xiaohua Tony Hu ; Bin Ma ; Sanguthevar Rajasekaran ; Satoru Miyano ; Illhoi Yoo ; Brian Pierce ; Amarda Shehu ; Vijay K. Gombar ; Brian Chen ; Vinay Pai ; Jun Huan. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 301-304 (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015).
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