linkstream2 microblog

Landscape of lncRNAs in the human #transcriptome
http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3192.html Derived from RNAseq read assembly; not much overlap w/ @GencodeGenes

Matthew K Iyer,
Yashar S Niknafs,
Rohit Malik,
Udit Singhal,
Anirban Sahu,
Yasuyuki Hosono,
Terrence R Barrette,
John R Prensner,
Joseph R Evans,
Shuang Zhao,
Anton Poliakov,
Xuhong Cao,
Saravana M Dhanasekaran,
Yi-Mi Wu,
Dan R Robinson,
David G Beer,
Felix Y Feng,
Hariharan K Iyer
& Arul M Chinnaiyan

Nature Genetics (2015) doi:10.1038/ng.3192Received 20 June 2014 Accepted 18 December 2014

Reconciling differential gene expression
w/…#networkshttp://bioinformatics.oxfordjournals.org/content/29/5/622 Propagating this across interactions finds perturbed pathways

This paper basically propagates scores of disease-related highly differentially expressed genes (-log10 p) over human protein interaction network, calculates new scores using four major algorithms (Vanilla, PageRank, GeneMANIA, Heat Kernel), re-ranks genes based on the new scores and then finds enriched pathways among top-ranking genes. Compared with traditional ways by ranking highly differentially expressed genes based on p-values without any network information, the approach not only recovered canonical pathways but also discovered novel ones such as an insulin-mediated glucose transport pathway in Huntington’s disease. The authors also explored differences among four algorithms and identified the top-ranking genes specifically found by particular algorithms. In short, the paper provides a valuable framework for integrating networks and gene expression data. Their analysis for comparing four major algorithms is also helpful.

http://bioinformatics.oxfordjournals.org/content/29/5/622

http://www.nytimes.com/2015/01/28/nyregion/new-york-blizzard.html?_r=0

http://news.harvard.edu/gazette/story/2015/01/harvards-odyssey-unlocks-big-data/

http://www.ftc.gov/news-events/press-releases/2015/01/ftc-report-internet-things-urges-companies-adopt-best-practices

http://mashable.com/2015/01/28/ibm-identity-mixer/?utm_cid=mash-com-Tw-main-link

Snow totals: Guilford 17′, New Haven 9′, Fairfield 7′, NYC 10′

==

http://forecast.weather.gov/product.php?site=NWS&issuedby=OKX&product=PNS&format=CI&version=1&glossary=0

********************STORM TOTAL SNOWFALL********************

LOCATION STORM TOTAL TIME/DATE COMMENTS
SNOWFALL OF
/INCHES/ MEASUREMENT

CONNECTICUT

…..

…NEW HAVEN COUNTY…
GUILFORD 17.0 1030 AM 1/27 TRAINED SPOTTER MERIDEN 12.5 100 PM 1/27 CT DOT
WEST HAVEN 11.0 1112 AM 1/27 PUBLIC
BEACON FALLS 9.0 100 PM 1/27 CT DOT
NEW HAVEN 8.5 100 PM 1/27 CT DOT
SOUTHBURY 6.5 100 PM 1/27 CT DOT
BETHANY 6.0 1100 AM 1/27 TRAINED SPOTTER WATERBURY 5.5 100 PM 1/27 CT DOT

…NEW YORK COUNTY…
CENTRAL PARK 9.8 100 PM 1/27 CENTRAL PARK ZOO

http://en.m.wikipedia.org/wiki/Jeffrey_Katzenberg

http://en.m.wikipedia.org/wiki/John_Lasseter

http://en.m.wikipedia.org/wiki/Michael_Eisner