Yang, Jeremy
Cannon, Daniel
Bologa, Cristian
Mathias, Stephen
Jensen, Lars Juhl
Schürer, Stephan
Vidović, Dušica
Oprea, Tudor
2019-02-26
<p>TIN-X is designed to prioritize and visualize associations between proteins and diseases, from scientific literature (PubMed) text mining by JensenLab, via TCRD, and organized by Drug Target Ontology (DTO) based disease and protein classifications. TIN-X was initially conceived and prototyped by Cristian Bologa, then engineered as a full stack webapp by Daniel Cannon, deployed via AWS. Motivated by its success and perceived value to researchers, TIN-X has been continually maintained, updated, and improved. Recently, TIN-X has undergone a major revision to version 2.0, designed and implemented by Iterative Consulting, LLC, co-founded by Daniel Cannon. The new architecture conforms to modern software engineering standards, includes a Swagger/Django REST API, D3 thin client, and tight integration with TCRD. Updates and deployment automation employs Docker and AWS (EC2, S3, CloudFront). Source code is managed via Bitbucket and GitHub. The improvements address the Resource Sharing Plan of KMC, and NIH policies and principles concerning digital resource sharing (e.g. FAIR) as emphasized by the NIH Strategic Plan for Data Science.</p>
https://doi.org/10.5281/zenodo.5038628
oai:zenodo.org:5038628
Zenodo
https://doi.org/10.5281/zenodo.5038627
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
text mining
drug discovery
illuminating the druggable genome
TIN-X v2: modernized architecture with REST API for sustainability & interoperability
info:eu-repo/semantics/conferencePoster