Literature DB >> 28762619

Crowd sourcing difficult problems in protein science.

Nathan S Alexander1, Krzysztof Palczewski1,2.   

Abstract

Dedicated computing resources are expensive to develop, maintain, and administrate. Frequently, research groups require bursts of computing power, during which progress is still limited by available computing resources. One way to alleviate this bottleneck would be to use additional computing resources. Today, many computing devices remain idle most of the time. Passive volunteer computing exploits this unemployed reserve of computing power by allowing device-owners to donate computing time on their own devices. Another complementary way to alleviate bottlenecks in computing resources is to use more efficient algorithms. Engaging volunteer computing employs human intuition to help solve challenging problems for which efficient algorithms are difficult to develop or unavailable. Designing engaging volunteer computing projects is challenging but can result in high-quality solutions. Here, we highlight four examples.
© 2017 The Protein Society.

Entities:  

Keywords:  crowd sourcing; distributed computing; interaction networks; protein structure prediction; protein-ligand docking; volunteer computing

Mesh:

Substances:

Year:  2017        PMID: 28762619      PMCID: PMC5654861          DOI: 10.1002/pro.3247

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  16 in total

1.  Algorithm discovery by protein folding game players.

Authors:  Firas Khatib; Seth Cooper; Michael D Tyka; Kefan Xu; Ilya Makedon; Zoran Popovic; David Baker; Foldit Players
Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-07       Impact factor: 11.205

2.  A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

Authors:  T Estrada; B Zhang; P Cicotti; R S Armen; M Taufer
Journal:  Comput Biol Med       Date:  2012-06-02       Impact factor: 4.589

3.  Progress and challenges in high-resolution refinement of protein structure models.

Authors:  Kira M S Misura; David Baker
Journal:  Proteins       Date:  2005-04-01

4.  Toward high-resolution de novo structure prediction for small proteins.

Authors:  Philip Bradley; Kira M S Misura; David Baker
Journal:  Science       Date:  2005-09-16       Impact factor: 47.728

5.  COMPUTING: Screen Savers of the World Unite!

Authors:  M Shirts; V S Pande
Journal:  Science       Date:  2000-12-08       Impact factor: 47.728

6.  Crowd sourcing in drug discovery.

Authors:  Monika Lessl; Justin S Bryans; Duncan Richards; Khusru Asadullah
Journal:  Nat Rev Drug Discov       Date:  2011-04       Impact factor: 84.694

7.  Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions.

Authors:  K T Simons; C Kooperberg; E Huang; D Baker
Journal:  J Mol Biol       Date:  1997-04-25       Impact factor: 5.469

8.  Predicting protein structures with a multiplayer online game.

Authors:  Seth Cooper; Firas Khatib; Adrien Treuille; Janos Barbero; Jeehyung Lee; Michael Beenen; Andrew Leaver-Fay; David Baker; Zoran Popović; Foldit Players
Journal:  Nature       Date:  2010-08-05       Impact factor: 49.962

9.  Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

Authors:  Rohit Vashisht; Anupam Kumar Mondal; Akanksha Jain; Anup Shah; Priti Vishnoi; Priyanka Priyadarshini; Kausik Bhattacharyya; Harsha Rohira; Ashwini G Bhat; Anurag Passi; Keya Mukherjee; Kumari Sonal Choudhary; Vikas Kumar; Anshula Arora; Prabhakaran Munusamy; Ahalyaa Subramanian; Aparna Venkatachalam; S Gayathri; Sweety Raj; Vijaya Chitra; Kaveri Verma; Salman Zaheer; J Balaganesh; Malarvizhi Gurusamy; Mohammed Razeeth; Ilamathi Raja; Madhumohan Thandapani; Vishal Mevada; Raviraj Soni; Shruti Rana; Girish Muthagadhalli Ramanna; Swetha Raghavan; Sunil N Subramanya; Trupti Kholia; Rajesh Patel; Varsha Bhavnani; Lakavath Chiranjeevi; Soumi Sengupta; Pankaj Kumar Singh; Naresh Atray; Swati Gandhi; Tiruvayipati Suma Avasthi; Shefin Nisthar; Meenakshi Anurag; Pratibha Sharma; Yasha Hasija; Debasis Dash; Arun Sharma; Vinod Scaria; Zakir Thomas; Nagasuma Chandra; Samir K Brahmachari; Anshu Bhardwaj
Journal:  PLoS One       Date:  2012-07-11       Impact factor: 3.240

10.  A crowd-sourcing approach for the construction of species-specific cell signaling networks.

Authors:  Erhan Bilal; Theodore Sakellaropoulos; Ioannis N Melas; Dimitris E Messinis; Vincenzo Belcastro; Kahn Rhrissorrakrai; Pablo Meyer; Raquel Norel; Anita Iskandar; Elise Blaese; John J Rice; Manuel C Peitsch; Julia Hoeng; Gustavo Stolovitzky; Leonidas G Alexopoulos; Carine Poussin
Journal:  Bioinformatics       Date:  2014-10-07       Impact factor: 6.937

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  1 in total

1.  PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics.

Authors:  Muhammad Farhan Khalid; Kanzal Iman; Amna Ghafoor; Mujtaba Saboor; Ahsan Ali; Urwa Muaz; Abdul Rehman Basharat; Taha Tahir; Muhammad Abubakar; Momina Amer Akhter; Waqar Nabi; Wim Vanderbauwhede; Fayyaz Ahmad; Bilal Wajid; Safee Ullah Chaudhary
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

  1 in total

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