dc.contributor.author
Jurisica, Igor
dc.date.accessioned
2026-02-14T02:19:14Z
dc.date.available
2026-02-14T02:19:14Z
dc.date.issued
2021-10-14
dc.identifier
Jurisica, I. Advancing patient treatment through integrative computational biology. A: Severo Ochoa Research Seminars at BSC. «Research Seminar Lectures at BSC, Barcelona, 2021-22». Barcelona: Barcelona Supercomputing Center, 2021, p. 16-17.
dc.identifier
https://hdl.handle.net/2117/455091
dc.identifier.uri
http://hdl.handle.net/2117/455091
dc.description.abstract
Integrative computational biology and artificial intelligence help improving treatment of complex diseases by building explainable models. From systematic data analysis to improved biomarkers, drug mechanism of action, and patient selection, such analyses influence multiple steps of drug discovery pipeline. Data mining, machine learning, graph theory and advanced visualization help characterize interactome and drug orphans with accurate predictions, making disease modelling more comprehensive. Intertwining computational prediction and modelling with biological experiments will lead to more useful findings faster and more economically.
dc.format
application/pdf
dc.publisher
Barcelona Supercomputing Center
dc.rights
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights
Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
dc.subject
High performance computing
dc.subject
Càlcul intensiu (Informàtica)
dc.title
Advancing patient treatment through integrative computational biology
dc.type
Conference report
