A systems biology approach for modeling microbiomes using split graphs

Suyeon Kim, Ishwor Thapa, Guoqing Lu, Lifeng Zhu, Hesham H. Ali

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

2 Scopus citations

Abstract

With the recent advances in sequencing technology, researchers now have opportunities to study microbiomes associated with various environments. Recent studies have shown that the composition of microbiomes in our bodies and our environments play a significant role in our health. For example, 90% of human DNA is composed of bacterial microbiomes. In this study, we propose a systems biology approach using split graphs to analyze the composition of microbiomes and the impact of such composition on the health and growth of organisms living in associated environments. We focus on a case study related to the composition of microbiomes in fish guts and its impact on various growth parameters for three types of fish. The proposed model explores features in the aquatic ecosystem including correlations among its microorganisms and their abundance levels. The results of the study show that single or groups of bacteria are significantly associated with multiple growth phenotypes in different gut portions of the fish. We also identify bacterial clusters that provide new insight to functional relevance of these bacteria and their contribution to the fish gut microbial ecosystem.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2062-2068
Number of pages7
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period11/13/1711/16/17

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Keywords

  • Microbiomes
  • correlation analysis
  • microbiome composition
  • split graphs
  • systems biology

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

Cite this

Kim, S., Thapa, I., Lu, G., Zhu, L., & Ali, H. H. (2017). A systems biology approach for modeling microbiomes using split graphs. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Eds.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pp. 2062-2068). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217978