Crowdsourcing and knowledge models
12
Jun
Crowdsourcing is increasingly helping to channel the collective knowledge 
of the scientific community to find solutions to significant challenges in medicine and other fields, the collective models are more successful in the polls.
Sage Bionetworks and Dialogue for Reverse Engineering Assessments and Methods (DREAM) are hosting free software, changes in big data computing, top changes in statistical thinking, learning machines, and discoveries in computational biology, new predictive models of disease, appear The Scientist.
Teams compete with each other, but the competitions also encourage collaboration needed to respond to emerging biological
issues, according to Stephen Friend, founder of Sage Bionetworks: “The Meshing of these data with clinical outcomes for the development of indicators of what is likely to respond to therapy or who is likely to have an aggressive disease is a problem that needs to boldly great work and ideas of each other. ”
The model of scientific work using crowdsourcing, adapted the model collective and collaborative science to the use of an “overly intellectual” available in the crowd.
