MicroSIA: A Gut-Microbes Information-Extraction Method with Semantic Inverse Analysis for Discovering Unique Bacteria-Combinations in Nationality

Shiori Hikichi, Yasushi Kiyoki

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

Abstract

Extraction of gut-microbes information is important for analyzing the effects on human gut microbiome from the difference of human attributes such as nationality, gender, age and so on. It is pointed out that human gut microbiome, a set of bacteria, has various pathological and biological impacts on a hosting human body system. However, analyzing and estimating such kinds of impact from biological data resources are difficult even for data analysts with biological background. This paper presents MicroSIA, a new analytical method for human gut microbiome's effect by extracting the unknown relations with other adjunct metadata such as human attributes with Semantic Inverse Analysis. The most important feature of our method is the inverse processes (Semantic Inverse Analysis, computing the selection of axes in inversed direction to clustering) to discover potentially existing bacteria-combinations for classifying nationalities in human attribute data. MicroSIA extracts unique bacteria-combination selected from all bacteria-combinations by our original criteria such as the purity of a data cluster and the range of target human attributes. This paper also presents experimental studies on gut-microbes information acquisition to show the feasibility and the effectiveness of our method.

Original languageEnglish
Title of host publicationProceedings - IEEE 11th International Conference on Semantic Computing, ICSC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9-16
Number of pages8
ISBN (Electronic)9781509048960
DOIs
Publication statusPublished - 2017 Mar 29
Event11th IEEE International Conference on Semantic Computing, ICSC 2017 - San Diego, United States
Duration: 2017 Jan 302017 Feb 1

Other

Other11th IEEE International Conference on Semantic Computing, ICSC 2017
CountryUnited States
CitySan Diego
Period17/1/3017/2/1

Keywords

  • Bacterial components acquisition
  • Data mining
  • Inverse problem
  • Personalised medicine
  • Semantic analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications

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  • Cite this

    Hikichi, S., & Kiyoki, Y. (2017). MicroSIA: A Gut-Microbes Information-Extraction Method with Semantic Inverse Analysis for Discovering Unique Bacteria-Combinations in Nationality. In Proceedings - IEEE 11th International Conference on Semantic Computing, ICSC 2017 (pp. 9-16). [7889497] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSC.2017.65