Dimensional reduction in complex living systems: Where, why, and how.
allostery
data compression
dimensional reduction
genotype-to-phenotype map
intrinsic dimension
learning
protein evolution
Journal
BioEssays : news and reviews in molecular, cellular and developmental biology
ISSN: 1521-1878
Titre abrégé: Bioessays
Pays: United States
ID NLM: 8510851
Informations de publication
Date de publication:
09 2021
09 2021
Historique:
revised:
18
06
2021
received:
02
03
2021
accepted:
22
06
2021
pubmed:
11
7
2021
medline:
29
10
2021
entrez:
10
7
2021
Statut:
ppublish
Résumé
The unprecedented prowess of measurement techniques provides a detailed, multi-scale look into the depths of living systems. Understanding these avalanches of high-dimensional data-by distilling underlying principles and mechanisms-necessitates dimensional reduction. We propose that living systems achieve exquisite dimensional reduction, originating from their capacity to learn, through evolution and phenotypic plasticity, the relevant aspects of a non-random, smooth physical reality. We explain how geometric insights by mathematicians allow one to identify these genuine hallmarks of life and distinguish them from universal properties of generic data sets. We illustrate these principles in a concrete example of protein evolution, suggesting a simple general recipe that can be applied to understand other biological systems.
Identifiants
pubmed: 34245050
doi: 10.1002/bies.202100062
doi:
Substances chimiques
Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2100062Informations de copyright
© 2021 The Authors. BioEssays published by Wiley Periodicals LLC.
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