What kind of novelties can machine learning possibly generate? The case of genomics-Reference-Cited by-同舟云学术

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What kind of novelties can machine learning possibly generate? The case of genomics

Published:2020-10 Issue: Volume:83 Page:86-96
ISSN:0039-3681
Container-title:Studies in History and Philosophy of Science Part A
language:en
Short-container-title:Studies in History and Philosophy of Science Part A

Author:

Ratti Emanuele

Publisher

Elsevier BV

Subject

History and Philosophy of Science,History

Reference51 articles.

1. Molecular biology of the cell;Alberts,2007

2. Deep learning for computational biology;Angermueller;Molecular Systems Biology,2016

3. Gene Ontology : Tool for the Unification of Biology;Ashburner;Nature Genetics,2000

4. Comprehensive characterization of cancer driver genes and mutations;Bailey;Cell,2018

5. Network biology: Understanding the cell’s functional organization;Barabasi;Naure Reviews Genetics,2004

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2. The predictive reframing of machine learning applications: good predictions and bad measurements;European Journal for Philosophy of Science;2022-08-26

3. A pragmatic approach to scientific change: transfer, alignment, influence;European Journal for Philosophy of Science;2022-07-13

4. Values and inductive risk in machine learning modelling: the case of binary classification models;European Journal for Philosophy of Science;2021-10-26

5. Hypothesis-driven science in large-scale studies: the case of GWAS;Biology & Philosophy;2021-09-19

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