Dataset Information

Parallel vs. comparative evaluation of alternative options by colonies and individuals of the ant Temnothorax rugatulus.

ABSTRACT: Both a single ant and the colony to which it belongs can make decisions, but the underlying mechanisms may differ. Colonies are known to be less susceptible than lone ants to "choice overload", whereby decision quality deteriorates with increasing number of options. We probed the basis of this difference, using the model system of nest-site selection by the ant Temnothorax rugatulus. We tested the applicability of two competing models originally developed to explain information-processing mechanisms in vertebrates. The Tug of War model states that concurrent alternatives are directly compared, so that choosing between two alternatives takes longer than accepting a single one. In contrast, the Sequential Choice Model assumes that options are examined in parallel, and action takes place once any option reaches a decision criterion, so that adding more options shortens time to act. We found that single ants matched the Tug of War model while colonies fitted the Sequential Choice model. Our study shows that algorithmic models for decision-making can serve to investigate vastly different domains, from vertebrate individuals to both individuals and colonies of social insects.

SUBMITTER: Sasaki T

PROVIDER: S-EPMC6109163 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Parallel vs. comparative evaluation of alternative options by colonies and individuals of the ant Temnothorax rugatulus.

Sasaki Takao T Pratt Stephen C SC Kacelnik Alex A

Scientific reports 20180824 1

Both a single ant and the colony to which it belongs can make decisions, but the underlying mechanisms may differ. Colonies are known to be less susceptible than lone ants to "choice overload", whereby decision quality deteriorates with increasing number of options. We probed the basis of this difference, using the model system of nest-site selection by the ant Temnothorax rugatulus. We tested the applicability of two competing models originally developed to explain information-processing mechan ...[more]

PMID: 30143679

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Project description:INTRODUCTION: The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. METHODS: We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. RESULTS: We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. CONCLUSIONS: This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

Dataset Information

Parallel vs. comparative evaluation of alternative options by colonies and individuals of the ant Temnothorax rugatulus.

Publications

Parallel vs. comparative evaluation of alternative options by colonies and individuals of the ant Temnothorax rugatulus.

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