Posts Tagged ‘mynotes0mg’

Thoughts on last week’s conferences GP-Write & BoG ’17

May 15, 2017

TWEETS

https://storify.com/markgerstein/favorite-tweets-from-bog-17-gp-write-ib.html

TAGGED ITEMS

https://linkstream2.gerstein.info/tag/i0gpwrite/

SLIDES

http://lectures.gersteinlab.org/summary/Scaling-Computation-to-Keep-Pace-w-Data-Gen–20170510-i0gpwrite/

Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors : Nature Genetics : Nature Research

May 6, 2017

http://www.nature.com/ng/journal/v49/n5/full/ng.3818.html

Ref component analysis..of transcriptomes, by @Robson_Paul &co http://www.Nature.com/ng/journal/v49/n5/full/ng.3818.html Clustering similarity of samples to tissue references

Aging increases cell-to-cell transcriptional variability upon immune stimulation | Science

April 21, 2017

#Aging increases cell-to-cell transcriptional variability upon immune stimulation, but just for 225 up-reg. genes http://science.ScienceMag.org/content/355/6332/1433

Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression: Cell

April 16, 2017

"Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression"

(http://www.sciencedirect.com/science/article/pii/S0092867417301289)

#Neanderthal-Introgressed Sequences [&]…Gene Expression http://www.Cell.com/cell/abstract/S0092-8674(17)30128-9?_returnURL=http%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867417301289%3Fshowall%3Dtrue ASE for Hn SNPs shows lower #brain expression vs reference

Phys. Rev. E 92, 032810 (2015) – Thermodynamic characterization of networks using graph polynomials

March 31, 2017

Thermodynamic characterization of #networks using graph polynomials https://journals.APS.org/pre/abstract/10.1103/PhysRevE.92.032810 Application to the stockmarket & biological data

Is American Pet Health Care (Also) Uniquely Inefficient?

March 11, 2017

Is American Pet Health Care (Also) Uniquely Inefficient?
http://www.NBER.org/papers/w22669 High correlation betw. #healthcare costs for people & pets

A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human: Cell

February 24, 2017

FissionNet: Proteome-wide [pombe] Interactome Reveals #Network Evolution Principles
http://www.Cell.com/cell/abstract/S0092-8674(15)01556-1 Involving ~1300 soluble proteins

JClub papers

February 16, 2017

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.

Exploiting Temporal Collateral Sensitivity in Tumor Clonal Evolution: Cell

February 4, 2017

Temporal Collateral Sensitivity in Tumor…Evolution
http://www.cell.com/cell/abstract/S0092-8674(16)30059-9 Drug-fitness landscape illuminates transiently vulnerable state

Exploiting Temporal Collateral Sensitivity in Tumor Clonal Evolution

Boyang Zhao
Joseph C. Sedlak
Raja Srinivas
Pau Creixell
Justin R. Pritchard
Bruce Tidor
Douglas A. Lauffenburger
Michael T. Hemann

Genome-wide, integrative analysis implicates microRNA dysregulation in autism spectrum disorder : Nature Neuroscience : Nature Research

January 28, 2017

Genome-wide…analysis implicates miRNA dysregulation in #ASD http://www.nature.com/neuro/journal/v19/n11/full/nn.4373.html 58 diff. expr. miRNAs incl 17 strongly down in cases

http://www.nature.com/neuro/journal/v19/n11/full/nn.4373.html

QT:{{”
The miRNA expression profiles were very similar between the frontal and temporal cortex, but were distinct in the cerebellum
(Supplementary Fig. 2a–f), consistent with previous observations for mRNAs11, 12. We therefore combined 95 covariate-matched samples (47 samples from 28 ASD cases and 48 samples from 28 controls;
Supplementary Fig. 1c and Supplementary Table 1) from the FC and TC for differential gene expression (DGE) analysis, comparing ASD and CTL using a linear mixed-effects regression framework to control for potential confounders (Online Methods). We identified 58 miRNAs showing significant (false discovery rate (FDR) < 0.05) expression changes between ASD and CTL: 17 were downregulated and 41 were upregulated in ASD cortex (Fig. 1b and Supplementary Table 2). The fold changes for the differentially expressed miRNAs were highly concordant between the FC and TC (Pearson correlation coefficient R = 0.96, P < 2.2 × 10−16; Fig. 1c).
“}}