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High-performance computing service for bioinformatics and data science

Despite having an ideal setup in their labs for wet work, researchers often lack the computational infrastructure to analyze the magnitude of data that result from “-omics” experiments. In this innovative project, the library supports analysis of high-throughput data from global molecular profiling...

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Detalles Bibliográficos
Autores principales: Courneya, Jean-Paul, Mayo, Alexa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medical Library Association 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6148605/
https://www.ncbi.nlm.nih.gov/pubmed/30271293
http://dx.doi.org/10.5195/jmla.2018.512
Descripción
Sumario:Despite having an ideal setup in their labs for wet work, researchers often lack the computational infrastructure to analyze the magnitude of data that result from “-omics” experiments. In this innovative project, the library supports analysis of high-throughput data from global molecular profiling experiments by offering a high-performance computer with open source software along with expert bioinformationist support. The audience for this new service is faculty, staff, and students for whom using the university’s large scale, CORE computational resources is not warranted because these resources exceed the needs of smaller projects. In the library’s approach, users are empowered to analyze high-throughput data that they otherwise would not be able to on their own computers. To develop the project, the library’s bioinformationist identified the ideal computing hardware and a group of open source bioinformatics software to provide analysis options for experimental data such as scientific images, sequence reads, and flow cytometry files. To close the loop between learning and practice, the bioinformationist developed self-guided learning materials and workshops or consultations on topics such as the National Center for Biotechnology Information’s BLAST, Bioinformatics on the Cloud, and ImageJ. Researchers apply the data analysis techniques that they learned in the classroom in the library’s ideal computing environment.