A New Graph Database System for Multi-omics Data Integration and Mining Complex Biological Information

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

Abstract

Due to the advancement in high throughput technologies and robust experimental designs, many recent studies attempt to incorporate heterogeneous data obtained from multiple technologies to improve our understanding of the molecular dynamics associated with biological processes. Currently available technologies produce wide variety of large amount of data spanning from genomics, transcriptomics, proteomics, and epigenetics. Due to the fact that such multi-omics data are very diverse and come from different biological levels, it has been a major research challenge to develop a model to properly integrate all available and relevant data to advance biomedical research. It has been argued by many researchers that the integration of multi-omics data to extract relevant biological information is currently one of the major biomedical informatics challenges. This paper proposes a new graph database model to efficiently store and mine multi-omics data. We show a working model of this graph database with transcriptomics, genomics, epigenetics and clinical data for three cancer types from the Cancer Genome Atlas. Moreover, we highlight the usefulness of graph database mining to extract relevant biological interpretations and also to find novel relationships between different data levels.

Original languageEnglish (US)
Title of host publicationComputational Advances in Bio and Medical Sciences - 9th International Conference, ICCABS 2019, Revised Selected Papers
EditorsIon Mandoiu, Sanguthevar Rajasekaran, T.M. Murali, Giri Narasimhan, Pavel Skums, Alexander Zelikovsky
PublisherSpringer
Pages171-183
Number of pages13
ISBN (Print)9783030461645
DOIs
StatePublished - 2020
Event9th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2019 - Miami, United States
Duration: Nov 15 2019Nov 17 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12029 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2019
CountryUnited States
CityMiami
Period11/15/1911/17/19

Keywords

  • Data integration
  • Graph database
  • Information mining
  • Multi-omics data

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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