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Adaptation through the lense of single-cell multi-omics data Comment on "Dynamic and thermodynamic models of adaptation" by A.N. Gorban et al.

Andrei Zinovyev


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>A.N.Gorban and his colleagues in their inspiring review described several theoretical models of adaptation and&nbsp;highlighted multiple examples convincing us in the existence of surprising at first thought phenomenon: the pattern&nbsp;of dynamical changes of basic statistical measures (correlation between features, their variance) can diagnose and&nbsp;prognose crises in the populations of objects exposed to stress (1). The surprise is caused by the universality of this&nbsp;observation. Firstly, it is manifested in many different situations. Secondly and even more surprising, the features used&nbsp;do not have to be specifically designed to measure stress, even though the feature selection is still important. This&nbsp;suggests that the proposed models can serve as an insightful approach for Big Data analysis and interpretation.&nbsp;One can note that all provided examples deal with macroscopic objects (people, patients, mice, plants, companies&nbsp;at the stock market). What if we will change the focus of the middle-out approach to a significantly smaller scale, e.g.&nbsp;from a tumor or a patient to a single cell? Would the suggested principles of adaptation thermodynamics still hold and&nbsp;what specific problems will arise?</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Institut Curie", 
      "@type": "Person", 
      "name": "Andrei Zinovyev"
    }
  ], 
  "headline": "Adaptation through the lense of single-cell multi-omics data Comment on \"Dynamic and thermodynamic models of adaptation\" by A.N. Gorban et al.", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2021-07-20", 
  "url": "https://zenodo.org/record/5782911", 
  "keywords": [
    "single-cell data", 
    "omics data", 
    "adaptation", 
    "stress", 
    "cancer"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.5782911", 
  "@id": "https://doi.org/10.5281/zenodo.5782911", 
  "@type": "ScholarlyArticle", 
  "name": "Adaptation through the lense of single-cell multi-omics data Comment on \"Dynamic and thermodynamic models of adaptation\" by A.N. Gorban et al."
}
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