A Distributed Data Infrastructure for Open Bioinformatics Research

  • Dali Wang
  • , Mung Shu Shen
  • , Eric Wang
  • , Feng Chen
  • , Weijiao Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper outlines a distributed data infrastructure designed to enhance open bioinformatics research, particularly in enzyme structure investigation. Utilizing high-throughput computing and cloud resources, such as AWS, the architecture facilitates collaborative workflows while ensuring robust user management, security, data integrity, and scalability. Powered by a Django backend and an Angular frontend, the infrastructure promotes seamless communication and data handling. A case study demonstrates its application in enzyme structure analysis using computational tools like AlphaFold and AlphaFill, revealing improvements in understanding enzymatic functions and accelerating drug discovery. Ultimately, this infrastructure aims to improve the efficiency and accessibility of bioinformatics research.

Original languageEnglish
Title of host publicationProceedings - 2025 8th International Conference on Information and Computer Technologies, ICICT 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages429-434
Number of pages6
ISBN (Electronic)9798331505189
DOIs
StatePublished - 2025
Event8th International Conference on Information and Computer Technologies, ICICT 2025 - Hawaii-Hilo, United States
Duration: Mar 14 2025Mar 16 2025

Publication series

NameProceedings - 2025 8th International Conference on Information and Computer Technologies, ICICT 2025

Conference

Conference8th International Conference on Information and Computer Technologies, ICICT 2025
Country/TerritoryUnited States
CityHawaii-Hilo
Period03/14/2503/16/25

Funding

This work was partially supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internships program. This research used resources at Oak Ridge National Laboratory and the University of Tennessee, Knoxville, including those resources supported by the NIH projects (R01GM097576 and 1R01GM152927-01) that were awarded to the Memorial Sloan Kettering Cancer Center and the University of Tennessee, Knoxville.

Keywords

  • bioinformatics
  • data infrastructure
  • enzyme design

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