ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2010-08-06
    Description: People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2956414/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2956414/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Cooper, Seth -- Khatib, Firas -- Treuille, Adrien -- Barbero, Janos -- Lee, Jeehyung -- Beenen, Michael -- Leaver-Fay, Andrew -- Baker, David -- Popovic, Zoran -- Players, Foldit -- Howard Hughes Medical Institute/ -- England -- Nature. 2010 Aug 5;466(7307):756-60. doi: 10.1038/nature09304.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Computer Science and Engineering, University of Washington, Box 352350, Seattle, Washington 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20686574" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Computational Biology/*methods ; Computer Graphics ; Computer Simulation ; Cooperative Behavior ; Cues ; *Games, Experimental ; *Group Processes ; Humans ; Hydrogen Bonding ; Hydrophobic and Hydrophilic Interactions ; Imaging, Three-Dimensional ; *Internet ; Leisure Activities ; Models, Molecular ; Nuclear Magnetic Resonance, Biomolecular ; Photic Stimulation ; *Problem Solving ; Protein Conformation ; *Protein Folding ; Proteins/*chemistry/metabolism ; Stochastic Processes ; Thermodynamics
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2015-03-14
    Description: Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...