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Title: CrowdPhase: crowdsourcing the phase problem

The idea of attacking the phase problem by crowdsourcing is introduced. Using an interactive, multi-player, web-based system, participants work simultaneously to select phase sets that correspond to better electron-density maps in order to solve low-resolution phasing problems. The human mind innately excels at some complex tasks that are difficult to solve using computers alone. For complex problems amenable to parallelization, strategies can be developed to exploit human intelligence in a collective form: such approaches are sometimes referred to as ‘crowdsourcing’. Here, a first attempt at a crowdsourced approach for low-resolution ab initio phasing in macromolecular crystallography is proposed. A collaborative online game named CrowdPhase was designed, which relies on a human-powered genetic algorithm, where players control the selection mechanism during the evolutionary process. The algorithm starts from a population of ‘individuals’, each with a random genetic makeup, in this case a map prepared from a random set of phases, and tries to cause the population to evolve towards individuals with better phases based on Darwinian survival of the fittest. Players apply their pattern-recognition capabilities to evaluate the electron-density maps generated from these sets of phases and to select the fittest individuals. A user-friendly interface, a training stage and a competitivemore » scoring system foster a network of well trained players who can guide the genetic algorithm towards better solutions from generation to generation via gameplay. CrowdPhase was applied to two synthetic low-resolution phasing puzzles and it was shown that players could successfully obtain phase sets in the 30° phase error range and corresponding molecular envelopes showing agreement with the low-resolution models. The successful preliminary studies suggest that with further development the crowdsourcing approach could fill a gap in current crystallographic methods by making it possible to extract meaningful information in cases where limited resolution might otherwise prevent initial phasing.« less
Authors:
;  [1] ;  [1] ;  [2] ;  [2]
  1. Institute for Genomics and Proteomics, 611 Charles Young Drive East, Los Angeles, CA 90095 (United States)
  2. (United States)
Publication Date:
OSTI Identifier:
22347763
Resource Type:
Journal Article
Resource Relation:
Journal Name: Acta Crystallographica. Section D: Biological Crystallography; Journal Volume: 70; Journal Issue: Pt 6; Other Information: PMCID: PMC4051500; PMID: 24914965; PUBLISHER-ID: lv5063; OAI: oai:pubmedcentral.nih.gov:4051500; Copyright (c) Jorda et al. 2014; This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
Denmark
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; ALGORITHMS; CRYSTALLOGRAPHY; CRYSTALS; CURRENTS; DENSITY; ELECTRON DENSITY; ELECTRONS; ERRORS; INTERFACES; LAYERS; MATHEMATICAL SOLUTIONS; PATTERN RECOGNITION; RESOLUTION; SOLUTIONS