Bioinformatics and Computational Biology Core (BCB)

Indiana University Indianapolis, Indianapolis IN

Investigators

Linked publications, trials & patents

Abstract

PROJECT ABSTRACT/SUMMARY Bioinformatics and Computational Biology Core (BCB) Alzheimer's disease (AD) affects about 40 million people worldwide today and is the most common form of dementia found predominantly in the elderly. AD is a highly heterogeneous disease with major symptoms including progressive memory and cognitive domain deterioration over years, which eventually leads to death about 3-9 years after diagnosis. During the past few decades, many hypotheses have been proposed as potential mechanisms for AD, which involve multiple biological processes such as proteopathogenesis, mitochondrial abnormality, viral infection, and other glia cell-mediated immunological responses. However, the disease etiology and mechanism still remain unclear, and currently, there is still no curative treatment for AD. During the past years, multiple endeavors have been taken by the AD research community to identify potential drug targets and large amount of data have been generated which enables mining for evidences for drug targets. The large amount of data accumulated from these projects calls for deeper analysis coupled with extensive downstream drug development technologies to refine the target candidate lists and also identify potential new targets as well as possible drugs. As part of the Indiana University School of Medicine Purdue University TaRget Enablement to Accelerate Therapy Development for Alzheimer's Disease (IUSM-Purdue TREAT-AD) Center, the Bioinformatics and Computational Biology Core (BCB Core) will play a critical role. Specifically, the BCB Core will continue to develop advanced and novel data integration methods for predicting and prioritizing drug targets. These targets will be further refined based on additional evidences from data and experiments in collaboration with other cores of the IUSM-Purdue TREAT-AD Center. In addition, the BCB core will leverage the recent development of AI technology to develop an AI-based pipeline for predicting small molecules targeting specific proteins. The pipeline is based on advanced graph-learning methods developed by the team and will initially focus on specific protein kinases. Last but not the least, the BCB Core will provide biostatistics design and bioinformatics data analysis support for the entire center covering the lifecycle of the AD drug target identification and testing by closely collaborating and coordinating with other cores for the TREAT-AD Center. The BCB core will maintain frequent interactions with the rest of the center and also actively communicate the other Center in the TREAT-AD consortium for data standards, tool sharing, and best practices.