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Taming the complexity of large models
Author(s) -
Oberhardt Matthew,
Ruppin Eytan
Publication year - 2013
Publication title -
embo reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.584
H-Index - 184
eISSN - 1469-3178
pISSN - 1469-221X
DOI - 10.1038/embor.2013.145
Subject(s) - computer science , process (computing) , data science , operating system
There are many complex biological models that fit the data perfectly and yet do not reflect the cellular reality. The process of validating a large model should therefore be viewed as an ongoing mission that refines underlying assumptions by improving low‐confidence areas or gaps in the model's construction.