Ontology highlight
ABSTRACT:
SUBMITTER: Ciesielski TH
PROVIDER: S-EPMC4112852 | biostudies-literature | 2014
REPOSITORIES: biostudies-literature
Ciesielski Timothy H TH Pendergrass Sarah A SA White Marquitta J MJ Kodaman Nuri N Sobota Rafal S RS Huang Minjun M Bartlett Jacquelaine J Li Jing J Pan Qinxin Q Gui Jiang J Selleck Scott B SB Amos Christopher I CI Ritchie Marylyn D MD Moore Jason H JH Williams Scott M SM
BioData mining 20140630
In omic research, such as genome wide association studies, researchers seek to repeat their results in other datasets to reduce false positive findings and thus provide evidence for the existence of true associations. Unfortunately this standard validation approach cannot completely eliminate false positive conclusions, and it can also mask many true associations that might otherwise advance our understanding of pathology. These issues beg the question: How can we increase the amount of knowledg ...[more]