Open AccessData sources for in vivo molecular profiling of human phenotypes
Author(s) -
Cardozo Timothy,
Gupta Priyanka,
Ni Eric,
Young Lauren M.,
Tivon Doreen,
Felsovalyi Klara
Publication year - 2016
Publication title -
wiley interdisciplinary reviews: systems biology and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.087
H-Index - 51
eISSN - 1939-005X
pISSN - 1939-5094
DOI - 10.1002/wsbm.1354
Subject(s) - computational biology , proteomics , biology , profiling (computer programming) , rna , human genome , phenotype , genome , in vivo , context (archaeology) , genomics , genetics , gene , bioinformatics , computer science , paleontology , operating system
Molecular profiling of human diseases has been approached at the genetic ( DNA ), expression ( RNA ), and proteomic (protein) levels. An important goal of these efforts is to map observed molecular patterns to specific, mechanistic organic entities, such as loci in the genome, individual RNA molecules or defined proteins or protein assemblies. Importantly, such maps have been historically approached in the more intuitive context of a theoretical individual cell, but diseases are better described in reality using an in vivo framework, namely a library of several tissue‐specific maps. In this article, we review the existing data atlases that can be used for this purpose and identify critical gaps that could move the field forward from cellular to in vivo dimensions. WIREs Syst Biol Med 2016, 8:472–484. doi: 10.1002/wsbm.1354 This article is categorized under: Biological Mechanisms > Chemical Biology Laboratory Methods and Technologies > Genetic/Genomic Methods Laboratory Methods and Technologies > Proteomics Methods