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December 2015 Volume 16 Number 12 | |||||||||||||||||||||||||||||||||||||
In this issue Research Highlights Reviews
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REVIEWS | Top | ||||||||||||||||||||||||||||||||||||
Protective alleles and modifier variants in human health and disease Andrew R. Harper, Shalini Nayee & Eric J. Topol p689 | doi:10.1038/nrg4017 Many disease-associated genetic variants have been identified, but how genetic variation contributes to protection from disease is less well understood. In this Review, the authors discuss the identification and characterization of protective alleles and modifier variants, and the potential implications of these findings for disease prevention and drug development. Abstract | Full Text | PDF | |||||||||||||||||||||||||||||||||||||
Article series: Computational tools Human genotype-phenotype databases: aims, challenges and opportunities Anthony J. Brookes & Peter N. Robinson p702 | doi:10.1038/nrg3932 With biomedical datasets growing exponentially in size and number, efforts to increase their utility and availability are essential, but much work remains to maximize exploitability. This Review summarizes trends, developments and future perspectives in the rapidly advancing field of human genotype-phenotype databases. Abstract | Full Text | PDF | |||||||||||||||||||||||||||||||||||||
Article series: Single-cell omics Single-cell epigenomics: techniques and emerging applications Omer Schwartzman & Amos Tanay p716 | doi:10.1038/nrg3980 Various methodologies have been developed to characterize diverse features of chromatin, but understanding how epigenomic states contribute to cellular heterogeneity requires adoption of these techniques at the single-cell level. This article discusses the technological developments driving single-cell epigenomics, including the practical and bioinformatic challenges and emerging biological insights. Abstract | Full Text | PDF | |||||||||||||||||||||||||||||||||||||
Article series: Computational tools Methods and models for unravelling human evolutionary history Joshua G. Schraiber & Joshua M. Akey p727 | doi:10.1038/nrg4005 The rapid accumulation and increasing quality of human DNA sequence-variation data brought about by advances in genome-scale sequencing present opportunities to investigate human evolution. The authors discuss the statistical methods and models that can be used to gain insight into the evolution of human populations from analyses of large-scale genomic data sets, as well as the challenges associated with these approaches. Abstract | Full Text | PDF | Supplementary information | |||||||||||||||||||||||||||||||||||||
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*2013 Journal Citation Report (Thomson Reuters, 2014) |
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