Posts Tagged ‘mynotes0mg’

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).
“}}

Jclub paper

January 16, 2017

The impact of #SVs on…gene expression
http://biorxiv.org/content/early/2016/06/09/055962 24k in 147 people in GTEx pilot act as causal variants in 3-7% of ~25k eQTLs

The impact of structural variation on human gene expression

Colby Chiang, Alexandra J Scott, Joe R Davis, Emily
K Tsang, Xin Li, Yungil Kim, Farhan N Damani, Liron Ganel, GTEx Consortium, Stephen B Montgomery, Alexis Battle, Donald F Conrad, Ira M Hall
doi: https://doi.org/10.1101/055962

new CommonMind paper

December 22, 2016

Gene expr. elucidates functional impact of…risk for SCZ
http://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.4399.html CMC resource contains >2.1M #eQTLs involving ~1.6M SNPs

NATURE NEUROSCIENCE | ARTICLE

Gene expression elucidates functional impact of polygenic risk for schizophrenia

Menachem Fromer,
Panos Roussos,
Solveig K Sieberts,
Jessica S Johnson,
David H Kavanagh,
Thanneer M Perumal,
Douglas M Ruderfer,
….
Eric E Schadt,
Keisuke Hirai,
Kathryn Roeder,
Kristen J Brennand,
Nicholas Katsanis,
Enrico Domenici,
Bernie Devlin
& Pamela Sklar

Protein-structure-guided discovery of functional mutations across 19 cancer types : Nature Genetics : Nature Research

December 11, 2016

Protein-structure-guided discovery of functional mutations across 19 #cancer types http://www.nature.com/ng/journal/v48/n8/abs/ng.3586.html Cancer3D relates SNVs to drugs

http://www.nature.com/ng/journal/v48/n8/abs/ng.3586.html

A scored human protein-protein interaction network to catalyze genomic interpretation : Nature Methods : Nature Research

December 9, 2016

Scored…PPI #network to catalyze genomic interpretation http://www.Nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4083.html >500k links from lit. mining; up weights small-scale expt

Thoughts on BD2K AHM

December 6, 2016

TWEETS

https://storify.com/markgerstein/favorite-tweets-from-bd2k-all-hands-meeting-16-bd2

TAGGED ITEMS

https://linkstream2.gerstein.info/tag/i0bd2k16

PRIVATE SLIDE PICS

http://archive.gersteinlab.org/meetings/s/2016/12.03/i0bd2k16–bd2k_ahm-posters/

PLOS Computational Biology: PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

November 28, 2016

PredictSNP…Consensus Classifier for Prediction of Disease-Related
Mutations http://journals.PLOS.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003440 Demo of various #ensemble approaches

My notes from #BioData16 with a collection of links related to education in biomedical data science

November 7, 2016

# The meeting
https://meetings.cshl.edu/meetings.aspx?meet=DATA&year=16

# The panel

My lecture
http://lectures.gersteinlab.org/summary/Education-in-Bio-DataScience–20161028-i0bds16/

List of Curricular Topics for Bioinformatics http://goo.gl/303KXr An invitation for crowd-sourced comments to the talk

Panel Slides
https://docs.google.com/presentation/d/1mhcXpr_BhxvCx4Ki4jR4hLRNzm524JMW76H8zL31Yt4/edit?usp=sharing

Cached copy of above gdocs
http://archive.gersteinlab.org/public-docs/2016/11.01/cached-copy-of-biodata16-i0bds16-gdocs/

Earlier versions of the crowd-source edit:
http://cbb752b16.gersteinlab.org/assignments/homework0
Also:
http://blog.gerstein.info/2015/11/list-of-study-topics-prerequisites-for.html

# Related educational resources (unfortunately, Yale-centric):

The Yale CBB program & its focus on Data Science
http://cbb.yale.edu
http://cbb.yale.edu/graduate-program/optional-focus-biomedical-data-science

CBB752 – Biomedical Data Science: Mining & Modeling
http://www.gersteinlab.org/courses/452/

My ’14 list of US Bioinformatics Programs:
http://blog.gerstein.info/2015/05/updated-again-listing-of-us-programs-in.html https://twitter.com/markgerstein/status/600763647095341056

Hackathon slides:
https://docs.google.com/presentation/d/123NLmlYAUrJf2M709kPyDJl3N5wIcOO8W-EGJVxZKN4/edit?usp=sharing

Article on online curriculum:
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003662

Masters of Data Science
http://www.slideshare.net/ttimbers/ubc-mds-education-slides

Favorite Tweets
https://storify.com/markgerstein/favorite-tweets-from-biological-data-science-16-bi

Tagged from meeting
https://linkstream2.gerstein.info/tag/i0bds16/