Research prioritization through prediction of future impact on biomedical science: a position paper on inference-analytics.

ABSTRACT:

Background

Advances in biotechnology have created "big-data" situations in molecular and cellular biology. Several sophisticated algorithms have been developed that process big data to generate hundreds of biomedical hypotheses (or predictions). The bottleneck to translating this large number of biological hypotheses is that each of them needs to be studied by experimentation for interpreting its functional significance. Even when the predictions are estimated to be very accurate, from a biologist's perspective, the choice of which of these predictions is to be studied further is made based on factors like availability of reagents and resources and the possibility of formulating some reasonable hypothesis about its biological relevance. When viewed from a global perspective, say fr

SUBMITTER: Ganapathiraju MK 

PROVIDER: S-EPMC3844564 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature