Using the PubMed Abstract Sifter for Computational Modeling of Complex Biological Processes

Modeling complex biological processes can require retrieving, organizing, and extracting entities and relationships from thousands of PubMed citations. The USEPA’s Center for Computational Toxicology and Exposure’s Virtual Tissue project team has developed an Excel-based literature mining tool called the PubMed Abstract Sifter that facilitates each literature task in complex biological modeling. We will demonstrate how the publicly available tool can be used to identify gene and protein participants in a biological process, to build out a network of gene relationships, and to identify the chemical stressors that can be used to perturb that network to produce adverse outcomes. DISCLAIMER: does not necessarily reflect Agency policy Moderator: James A. Glazier, PhD, Indiana University, Bloomington For a publication on Abstract Sifter see: Baker, Nancy, Thomas Knudsen, and Antony Williams. "Abstract Sifter: a comprehensive front-end system to PubMed." F1000Research 6 (2017): Chem-Inf. https://lnkd.in/gaRGpjhc To view the slides for this video visit: https://docs.google.com/presentation/d/1Kby57vKCaD4nsJFRvuxZw5IXt9iZVL4M/ If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://tinyurl.com/GLIMPRINTVideos Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/