The interests of SoIC researchers in the biohealth arena range from genome and proteome analysis, regulatory networks, and biomarker discovery, to managing specific disease modalities such as cancer, HIV, diabetes, and opioid addiction. Utilizing medical data, they apply innovative technology and develop digital tools to improve patient health care.
DNA to RNA
Funded by a $1.9M NIH grant, Sarath Janga and his team explore factors that control proteins which translate DNA to RNA, and develop technologies for dissecting RNA-protein interactions in cells. To date, more than 160 unique RNA modifications have been documented. Resulting epitranscriptomes act like cellular traffic signals, turning access to RNA on or off—a phenomenon Janga’s lab explores using single-molecule sequencing and deep learning approaches.
Multi-omic data and systems biology networks—genome, transcriptome, proteome, and metabolome—hold the potential for discovering new disease mechanisms and markers for designing new drugs and treatment protocols, but the large, complex data sets are difficult to harness. With NSF CRII grant funding, Jingwen Yan has developed a novel, data-intensive computational framework to analyze and integrate the data and networks, create predictive models, and reveal their associations.
The Mass Graph
$1.18M NIH grant-funded research collaboration between the School of Informatics and Computing and the IU School of Medicine unites two cutting-edge technologies in the discovery and analysis of proteoforms, combining the irrespective expertise in mass spectrometry-based top-down proteomics data analysis, and RNA sequencing. Xiaowen Liu has developed a novel data model, the “mass graph,” incorporating RNA sequence modeling.