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Bioinformatics Resources for the Study of Glycan-Mediated Protein Interactions
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High-performance computing service for bioinformatics and data science.

Jean-Paul Courneya1, Alexa Mayo2

  • 1Bioinformationist, Health Sciences and Human Services Library, University of Maryland, Baltimore, MD 21201.

Journal of the Medical Library Association : JMLA
|October 2, 2018
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Summary

This project provides researchers with high-performance computing and bioinformatics support for analyzing large "-omics" datasets. The library empowers users to process complex molecular profiling data independently.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Researchers often face challenges with computational infrastructure for analyzing large datasets from -omics experiments.
  • Existing large-scale computational resources may exceed the needs of smaller, individual research projects.
  • There is a need for accessible, specialized computational support for high-throughput data analysis.

Purpose of the Study:

  • To establish a library-based service offering high-performance computing and bioinformatics support for researchers.
  • To empower faculty, staff, and students to analyze high-throughput molecular profiling data.
  • To bridge the gap between data generation and computational analysis capabilities.

Main Methods:

  • Acquisition of high-performance computing hardware tailored for bioinformatics tasks.
  • Selection and implementation of open-source bioinformatics software for diverse data types (e.g., sequence reads, scientific images, flow cytometry files).
  • Development of self-guided learning materials and workshops on bioinformatics tools and techniques (e.g., BLAST, Cloud Bioinformatics, ImageJ).

Main Results:

  • A new service providing accessible computational infrastructure and expert support for high-throughput data analysis.
  • Increased user capability in analyzing complex molecular profiling data.
  • Successful integration of learning resources with practical application in a dedicated computing environment.

Conclusions:

  • Libraries can play a crucial role in providing specialized computational resources and support for scientific research.
  • Empowering researchers with accessible tools and training facilitates advanced data analysis.
  • This initiative enhances the research capacity of individuals and smaller projects by overcoming computational barriers.