Progress with Knowledge Enriched Data Analytics
Explanatory-artificial-intelligence (x-AI) has highlighted the growing need to integrate knowledge types into big data analytics. During this seminar, Dr. Bernhald Palsson will describe the three approaches used to progress knowledge in this field:
- The use of Independent Component Analysis (ICA) to define independently modulated sets of genes in bacterial transcriptomes
- The use of pangenome analysis for the thousands of bacterial genome sequences being generated
- The use of machine learning methods for the analysis of antimicrobial resistance
Each of the approaches highlights an important advancement in the integration of knowledge types into x-AI. The first approach illustrates the principle of "getting answers to questions not asked"; the second shows "what is learned with scale"; and the third approach explains how mechanisms are built into genome-wide association studies (GWAS) using flux balance analysis (FBA).
Dr. Bernhald Palsson is the Distinguished Galletti Professor of Bioengineering, the principal investigator of the Systems Biology Research Group in the Department of Bioengineering, and professor of pediatrics at the University of California, San Diego.
Upcoming Events
- Predicting Patients’ Response to Immunotherapy from Tumor Histopathology and Blood: Computational Science in Immuno-oncologyJuly 08, 2025Assessing the Tumor Microenvironment with Systems Immunology: Computational Science in Immuno-oncologyAugust 21, 2025Data Jamboree: Enhancing Childhood Cancer Data Sharing and UtilitySeptember 29, 2025 - September 30, 2025NCI Office of Data Sharing’s Annual Data Sharing Symposium 2025: How Data Advances the Impact of Cancer ResearchSeptember 30, 2025 - October 01, 2025Childhood Cancer Data Initiative (CCDI) Symposium 2025October 06, 2025 - October 07, 2025