Journal
NATURE REVIEWS GENETICS
Volume 13, Issue 8, Pages 523-536Publisher
NATURE RESEARCH
DOI: 10.1038/nrg3253
Keywords
-
Categories
Funding
- [KUL PFV/10/016 SymBioSys]
- [KUL GOA MaNet]
- [Hercules III PacBio RS]
- [FP7-HEALTH CHeartED]
Ask authors/readers for more resources
At different stages of any research project, molecular biologists need to choose - often somewhat arbitrarily, even after careful statistical data analysis - which genes or proteins to investigate further experimentally and which to leave out because of limited resources. Computational methods that integrate complex, heterogeneous data sets - such as expression data, sequence information, functional annotation and the biomedical literature - allow prioritizing genes for future study in a more informed way. Such methods can substantially increase the yield of downstream studies and are becoming invaluable to researchers.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available