Human tissue-specific #networks by @TroyanskayaLab
http://www.nature.com/ng/journal/v47/n6/full/ng.3259.html
Brain-specific ones & NetWAS approach for combining #GWAS genes
access all tissue networks including the brain-specific
networks at giant.princeton.edu
#Enhancer Evolution across 20 Mammal[s is faster than for promoters] by @PaulFlicek lab http://www.cell.com/cell/abstract/S0092-8674(15)00007-0 H3K27ac & H3K4me3 #chipseq
Treefinder Retraction Note [interestingly, done editorially due to change in software-license terms] http://www.biomedcentral.com/1471-2148/15/243 HT @bornalibran
Canonical genetic signatures [across 132 structures] of the adult human #brain [in 6 individuals]
http://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.4171.html HT @ozgunharmanci
QT:{{”
We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations.
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#Thermodynamics of Antimicrobial Lipopeptide Binding to Membranes http://www.cell.com/biophysj/abstract/S0006-3495(14)00928-X Non-human selectivity studied w. coarse-grained MD
A Multiscale Coarse-Graining Method for Biomolecul[es] http://pubs.acs.org/doi/abs/10.1021/jp044629q Simplified force field from fitting to all-atom #simulations
Sergei Izvekov and Gregory A. Voth *
J. Phys. Chem. B, 2005, 109 (7), pp 2469–2473
DOI: 10.1021/jp044629q
Heterogeneity in #singlecell RNAseq…hidden subpopulations by @OliverStegle lab http://www.nature.com/nbt/journal/v33/n2/full/nbt.3102.html scLVM corrects for cell cycle phase
Buettner, Florian, Kedar N. Natarajan, F. Paolo Casale, Valentina
Proserpio, Antonio Scialdone, Fabian J. Theis, Sarah A. Teichmann,
John C. Marioni, and Oliver Stegle. "Computational analysis of
cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals
hidden subpopulations of cells." Nature biotechnology 33, no. 2
(2015): 155-160.
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