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• W2116947789 abstract "Abstract Motivation: Bioinformatics is faced with a variety of problems that require human involvement. Tasks like genome annotation, image analysis, knowledge-base population and protein structure determination all benefit from human input. In some cases, people are needed in vast quantities, whereas in others, we need just a few with rare abilities. Crowdsourcing encompasses an emerging collection of approaches for harnessing such distributed human intelligence. Recently, the bioinformatics community has begun to apply crowdsourcing in a variety of contexts, yet few resources are available that describe how these human-powered systems work and how to use them effectively in scientific domains. Results: Here, we provide a framework for understanding and applying several different types of crowdsourcing. The framework considers two broad classes: systems for solving large-volume ‘microtasks’ and systems for solving high-difficulty ‘megatasks’. Within these classes, we discuss system types, including volunteer labor, games with a purpose, microtask markets and open innovation contests. We illustrate each system type with successful examples in bioinformatics and conclude with a guide for matching problems to crowdsourcing solutions that highlights the positives and negatives of different approaches. Contact: bgood@scripps.edu" @default.
• W2116947789 created "2016-06-24" @default.
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• W2116947789 date "2013-06-19" @default.
• W2116947789 modified "2023-09-23" @default.
• W2116947789 title "Crowdsourcing for bioinformatics" @default.
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• W2116947789 doi "https://doi.org/10.1093/bioinformatics/btt333" @default.
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