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Protein Contacts, Maximum Entropy in Biology, and Why Behavioural Mechanisms Matter: the PLOS Comp Biol May Issue

Check out our highlights from the PLOS Computational Biology May issue:


Inferring Contacting Residues within and between Proteins: What Do the Probabilities Mean?

May Issue Image. Credit: Wiedenhoeft et al.
May Issue Image. Credit: Wiedenhoeft et al.

It has recently been argued that there is no reason to assume that protein sequences should follow maximum entropy distributions, and that it is therefore puzzling that the max-ent formalism is successful for predicting interacting residues in proteins. Erik van Nimwegen argues that such apparent puzzles result from a misconception of the meaning of the max-ent formalism and, more generally, of the meaning of probabilities.

Image Credit: Erik Aurell
Image Credit: Erik Aurell


The Maximum Entropy Fallacy Redux?

Maximum entropy has a long and contested history in statistical physics, the field in which it was first introduced. In contrast to the positive evaluation of maximum entropy in science presented by Erik van Nimwegen (above), Erik Aurell contributes to the ongoing discussion about the use of maximum-entropy models in the modeling of biological data by arguing that max-ent provides no grounds to believe in direct coupling analysis (DCA).




To Cooperate or Not to Cooperate: Why Behavioural Mechanisms Matter

Mutualistic cooperation often requires multiple individuals to behave in a coordinated fashion. Hence, while the evolutionary stability of mutualistic cooperation poses no particular theoretical difficulty, its evolutionary emergence faces a chicken-and-egg problem: an individual cannot benefit from cooperating unless other individuals already do so. Arthur Bernard and colleagues use simulations in evolutionary robotics to study the consequences of this problem.


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