Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/10879
Title: Unifying theories in high-dimensional biophysics: approaches, challenges and opportunities
Authors: Bauer, Marianne
LEELAVATI NARLIKAR et al.
Dept. of Data Science
Keywords: Biophysics
Computational biology and bioinformatics
Mathematics and computing
Neuroscience
Systems biology
2026-APR-WEEK2
TOC-APR-2026
2026
Issue Date: Mar-2026
Publisher: Springer Nature
Citation: npj systems biology and applications, 12, 43.
Abstract: Across biological subdisciplines, the last decade has seen an explosion of high-dimensional datasets. At the ICTS workshop ‘Unifying Theories in High-Dimensional Biophysics’, we discussed whether this high dimensionality poses a challenge or an opportunity for theoretically describing, understanding and predicting biological systems. We discussed methods, models and frameworks that can be used for this purpose. This Comment summarizes our discussions from the perspectives of individual participants
URI: https://doi.org/10.1038/s41540-026-00680-9
http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/10879
ISSN: 2056-7189
Appears in Collections:JOURNAL ARTICLES

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