Posts Tagged ‘from’

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Transmissible Dog Cancer Genome Reveals the Origin and History of an Ancient Cell Lineage | Science

March 4, 2017

Transmissible Dog Cancer Genome Reveals…History of an Ancient Cell Lineage http://science.sciencemag.org/content/343/6169/437.full After 11k yrs 2M SNVs & 646 genes KO’ed

Elizabeth P. Murchison1,2,*,†,
David C. Wedge1,*,
Ludmil B. Alexandrov1,
Beiyuan Fu1,
Inigo Martincorena1,
Zemin Ning1,
Jose M. C. Tubio1,
Emma I. Werner1,
Jan Allen3,
Andrigo Barboza De Nardi4,
Edward M. Donelan3,
Gabriele Marino5,
Ariberto Fassati6,
Peter J. Campbell1,
Fengtang Yang1,
Austin Burt7,
Robin A. Weiss6,
Michael R. Stratton1,†

+ See all authors and affiliations

Science 24 Jan 2014:
Vol. 343, Issue 6169, pp. 437-440
DOI: 10.1126/science.1247167

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bioarchiv statistics

March 4, 2017

#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.”
“}}

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TP53 copy number expansion is associated with the evolution of increased body size and an enhanced DNA damage response in elephants | eLife

March 4, 2017

TP53 copy number expansion is associated w…enhanced DNA damage response in elephants https://elifesciences.org/content/5/e11994 18 p53 retro- & pseudo- genes

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IOT asthma inhaler

March 2, 2017

https://www.propellerhealth.com/

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Inferring chromatin-bound protein complexes from genome-wide binding assays – Genome Research

February 26, 2017

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.

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Detecting overlapping protein complexes in protein-protein interaction networks : Nature Methods : Nature Research

February 24, 2017

http://www.nature.com/nmeth/journal/v9/n5/abs/nmeth.1938.html

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All Apple aerial screen savers

February 24, 2017

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…

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Computational tools for cancer immunology : Computational genomics tools for dissecting tumour-immune cell interactions : Nature Reviews Genetics : Nature Research

February 24, 2017

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

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interesting paper

February 22, 2017

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.

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Color brewer

February 18, 2017

http://tools.medialab.sciences-po.fr/iwanthue/
http://colorbrewer2.org/

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