Bioinformatics challenges for personalized medicine

Authors:
Guy Haskin Fernald;Emidio Capriotti;Roxana Daneshjou;Konrad J. Karczewski;Russ B. Altman
Affiliations:
-;-;-;-;-
Venue:
Bioinformatics
Year:
2011

Citing 0
Cited 4

COEUS: a semantic web application framework

Proceedings of the 4th International Workshop on Semantic Web Applications and Tools for the Life Sciences
Large-Scale DNA sequence analysis in the cloud: a stream-based approach

Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing - Volume 2
Profile Ori Inbar: Making augmented reality a reality

XRDS: Crossroads, The ACM Magazine for Students - Wearable Computing: Getting Dressed in Tech
On constructing the tree of life

XRDS: Crossroads, The ACM Magazine for Students - Wearable Computing: Getting Dressed in Tech

Quantified Score

Hi-index	3.84

Visualization

Abstract

Motivation: Widespread availability of low-cost, full genome sequencing will introduce new challenges for bioinformatics. Results: This review outlines recent developments in sequencing technologies and genome analysis methods for application in personalized medicine. New methods are needed in four areas to realize the potential of personalized medicine: (i) processing large-scale robust genomic data; (ii) interpreting the functional effect and the impact of genomic variation; (iii) integrating systems data to relate complex genetic interactions with phenotypes; and (iv) translating these discoveries into medical practice. Contact: russ.altman@stanford.edu Supplementary information: Supplementary data are available at Bioinformatics online.