Archive for September, 2014
My public notes from the Yale Day of Data (#ydod2014, i0dataday)
Tuesday, September 30th, 2014The Institute for Data Intensive Engineering and Science – The Data-Scope
Tuesday, September 30th, 2014Coppi mentions: JHU’s Data-scope (http://idies.jhu.edu/datascope ), which has a specialized architecture for astronomical computation #ydod2014
4 PB / yr
What Big Data means to me — Bourne 21 (2): 194 — Journal of the American Medical Informatics Association
Tuesday, September 30th, 2014Bourne mentions “What Big Data means to me”
(http://jamia.bmj.com/content/21/2/194.extract ) in connection with the creation of a digital ecosystem #ydod2014
Analysis of noncoding regulatory mutations in cancer
Monday, September 29th, 2014http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3101.html
An interesting report of potential non-coding drivers without actually doing any wet lab work.
“These methods identify recurrent mutations in regulatory elements upstream of PLEKHS1, WDR74 and SDHD, as well as previously identified mutations in the TERT promoter”. In the text they mention “Khurana et al. also reported WDR74 promoter mutations in 2 of the 20 prostate cancer genomes analyzed”.
Bina QC Report for Single Sample
Monday, September 29th, 2014Nice viz of the quality of a single sequencing run
{Disclaimer I’m a consultant to this company.}
PLOS Computational Biology: Spatial Generalization in Operant Learning: Lessons from Professional Basketball
Monday, September 29th, 2014Spatial Generalization in… Learning: Lessons from… #Basketball http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003623 How past success changes your tendencies to shoot
Describes constructing a learning matrix for how a player will update his tendency to shoot
from a certain region of the court based on his past successes or failures
The Parable of Google Flu: Traps in Big Data Analysis
Monday, September 29th, 2014Parable of #Google Flu: Traps in #BigData Analysis http://www.sciencemag.org/content/343/6176/1203.summary Replicating results is hard, w/ an ever-changing search algorithm
For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights
Monday, September 29th, 2014For #BigData Scientists, Janitor Work Is Key http://www.nytimes.com/2014/08/18/technology/for-big-data-scientists-hurdle-to-insights-is-janitor-work.html Is a #datascientist a digital maid or a data priest? Perhaps a hybrid.
O’Neil talk
Blood transciptome paper
Sunday, September 28th, 2014Splicing changes along the blood lineage, good ex. of the
state-of-the-art in human transcriptomics
http://www.sciencemag.org/content/345/6204/1251033.abstract
Science 26 September 2014:
Vol. 345 no. 6204
DOI: 10.1126/science.1251033
Transcriptional diversity during lineage commitment of human blood progenitors
Chen et al.