Strong negative correlation between the precision of algorithms and the evolutionary distance from the training data.

Precision of TargetP across eukaryotes for plastid (a) and mitochondria (b); A. thaliana is shown in darker shade. Taxonomic classification of test species is shown on the X axis, skewed towards eudicots due to geno...

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Bibliographic Details
Main Author:	Sven B. Gould (12237287) (author)
Other Authors:	Jonas Magiera (20161413) (author), Carolina García García (20161416) (author), Parth K. Raval (8551167) (author)
Published:	2024
Subjects:	Biochemistry Evolutionary Biology Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified zea mays </ studies make use query species increases plastids import thousands physcomitrium patens </ mitochondrial proteome data chlamydomonas reinhardtii </ arabidopsis thaliana </ experimental data ranges experimental localisation remains div >< p current performance issues localisation based experimental plastid sometimes impossible results worsen results encourage random sampling protein ’ performance borders organelle errors optimizing performance next generation neural networks main driver frequent task diverse set 2 %.
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Strong negative correlation between the precision of algorithms and the evolutionary distance from the training data.

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