#bioRxiv: a progress report http://ASAPbio.org/biorxiv Great stats on the archive’s 1st years: 134 days from deposit until journal publication
QT:{{”
“The median interval is 134 days. Authors choose to post preprints at a variety of times in the publication cycle of a manuscript, ranging from first draft to simultaneous submission of a completed paper at bioRxiv and a journal. bioRxiv declines papers that have been published or already assigned a journal DOI.”
“}}
TP53 copy number expansion is associated w…enhanced DNA damage response in elephants https://elifesciences.org/content/5/e11994 18 p53 retro- & pseudo- genes
Inferring [w. NMF] chromatin-bound protein complexes [of TFs] from [ENCODE ChIP-seq] binding assays, by @ElementoLab
http://genome.cshlp.org/content/23/8/1295.full
Giannopoulou E, Elemento O. 2013. Inferring chromatin-bound
protein complexes from genome-wide binding assays. Genome Research, Published in Advance April 3, 2013, doi: 10.1101/gr.149419.112.
This study uses nonnegative matrix factorization (NMF) of ENCODE CHIP-seq data (transcription
factors and histone modifications) to predict complexes of
transcription factors that bind DNA
together; it then assesses how these predicted complexes regulate gene expression. It goes beyond
previous studies in that it attempts to treat the TFs as complexes rather than individuals. A handful of
the predicted complexes correspond to known regulatory complexes, e.g. PRC2, and overall, the
complexes were enriched for known protein-protein interactions. Linear regression and random forest
models were then used to predict the effects of the complexes on the expression of adjacent genes. In
both models, the complexes performed better than those predicted from a scrambled TF read count
matrix. Overall, this study provides a large set of hypotheses for combinations of TFs that may
function together, as well as potential new components of known complexes.
All $AAPL aerial #ScreenSavers
http://benjaminmayo.co.uk/watch-all-the-apple-tv-aerial-video-screensavers#D388F00A-5A32-4431-A95C-38BF7FF7268D Neat hack to get MOV files of each of drone flight –
SF,London,NY,LA,HK,HI,China…
http://www.nature.com/nrg/journal/v17/n8/fig_tab/nrg.2016.67_T1.html
Table 1: Computational tools for cancer immunology
FromComputational genomics tools for dissecting tumour–immune cell interactions
Hubert Hackl,
Pornpimol Charoentong,
Francesca Finotello
& Zlatko Trajanoski
Nature Reviews Genetics 17, 441–458 (2016) doi:10.1038/nrg.2016.67
Partitioning heritability of regulatory…variants across 11 common diseases http://www.Cell.com/ajhg/abstract/S0002-9297(14)00426-1 Almost 80% #noncoding v 10% coding
The paper below claims to find most of the heritability of 11 common diseases in regulatory regions (79% of heritability found in regulatory regions, <10% in protein coding regions).
Partitioning heritability of regulatory and cell-type-specific variants across 11 common
diseases.
Gusev A, Lee SH, Trynka G, Finucane H, Vilhjálmsson BJ, Xu H, Zang C, Ripke S, Bulik-Sullivan B, Stahl E; Schizophrenia Working Group of the Psychiatric Genomics Consortium; SWE-SCZ Consortium, Kähler AK, Hultman CM, Purcell SM, McCarroll SA, Daly M, Pasaniuc B, Sullivan PF, Neale BM, Wray NR, Raychaudhuri S, Price AL; Schizophrenia Working Group of the Psychiatric Genomics Consortium; SWE-SCZ Consortium.
Am J Hum Genet. 2014 Nov 6;95(5):535-52. doi:
10.1016/j.ajhg.2014.10.004. Epub 2014 Nov 6.
A #circadian gene-expr atlas in mammals by @jbhclock lab
http://www.PNAS.org/content/111/45/16219.abstract 43% of genes have a daily rhythm in at least 1 tissue [1/2]
.@jbhclock Fewest circadian genes in brain; most in liver. Perhaps this more reflects daily feeding cycle than true light-dark cycle? [2/2]
A circadian gene expression atlas in mammals: Implications for biology and medicine
Ray Zhanga,1,
Nicholas F. Lahensa,1,
Heather I. Ballancea,
Michael E. Hughesb,2, and
John B. Hogenescha,2
* Interestingly brain regions have the fewest circ genes(only ~3%), liver has most
* Diseases assoc with circadian genes correlate with NIH funding
* Genes can have up to a 6-hour phase diff. Between diff. organs (eg Vegfa betw. Heart & fat)
* 56 of the top 100 drugs incl. Top 7, targeted the product of a circadian gene. Related to the half-life of drugs.
* Could the liver genes be more reflective of feeding rhythm rather than true circadian clock.
linkstream2 microblog 