2021 journal article

Multiomic Big Data Analysis Challenges: Increasing Confidence in the Interpretation of Artificial Intelligence Assessments

ANALYTICAL CHEMISTRY, 93(22), 7763–7773.

By: M. Odenkirk n, D. Reif n  & E. Baker n 

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
MeSH headings : Artificial Intelligence; Big Data; Data Analysis
Source: Web Of Science
Added: July 19, 2021

The need for holistic molecular measurements to better understand disease initiation, development, diagnosis, and therapy has led to an increasing number of multiomic analyses. The wealth of information available from multiomic assessments, however, requires both the evaluation and interpretation of extremely large data sets, limiting analysis throughput and ease of adoption. Computational methods utilizing artificial intelligence (AI) provide the most promising way to address these challenges, yet despite the conceptual benefits of AI and its successful application in singular omic studies, the widespread use of AI in multiomic studies remains limited. Here, we discuss present and future capabilities of AI techniques in multiomic studies while introducing analytical checks and balances to validate the computational conclusions.