https://twitter.com/EvoMRI/status/960633150115282944
Here’s an overview of the GPCR literature as indexed on Wikidata: https://tools.wmflabs.org/scholia/topic/Q38173
Posts Tagged ‘twitter’
overview of the GPCR literature as indexed on Wikidata
February 8, 2018Twitter CEO finally explains why random favorites are inserted into your timeline – The Verge
December 16, 2017Spurious Correlations
January 25, 2016.@fionabrinkman @BioMickWatson @iddux Spurious Correlations
(http://tylervigen.com/spurious-correlations) related to Stat Frankenstein (https://twitter.com/markgerstein/status/689478730343837696)
Banjo Raises $100 Million to Detect World Events in Real Time
May 9, 2015Banjo Raises $100 Million to Detect World Events in Real Time http://blogs.wsj.com/digits/2015/05/06/banjo-raises-100-million-to-detect-world-events-in-real-time Will their global "crystal ball" notice this tweet?
A tool to easily edit DNA transforms research, holds potential for medicine – The Boston Globe
January 1, 2015A tool to easily edit DNA transforms research, holds potential for medicine – The Boston Globe
https://www.bostonglobe.com/metro/2014/11/30/tool-easily-edit-dna-transforms-research-holds-potential-for-medicine/X7srGGFardarsWBfCqEL2H/story.html
The technique has become so ubiquitous that it has entered the casual vernacular of science as a verb; people talking about “CRISPRing” genes they want to tweak or delete.
Twitter “Exhaust” Reveals Patterns of Unemployment | MIT Technology Review
December 1, 2014Social media fingerprints of unemployment, from detecting network components in tweet mining arxiv.org/abs/1411.3140 +
http://www.technologyreview.com/view/532746/twitter-exhaust-reveals-patterns-of-unemployment
Lots of press for an arxiv paper, viz:
Twitter “Exhaust” Reveals Patterns of Unemployment | MIT Technology Review
QT:{{”
So the team analysed the rate at which messages were exchanged between regions using a standard community detection algorithm. This revealed 340 independent areas of economic activity, which largely coincide with other measures of geographic and economic distribution. “This result shows that the mobility detected from geolocated tweets and the communities obtained are a good description of economical areas,” they say.
Finally, they looked at the unemployment figures in each of these regions and then mined their database for correlations with twitter activity.
“}}
PLOS Computational Biology: Ten Simple Rules of Live Tweeting at Scientific Conferences
September 19, 201410… Rules of Live Tweeting at Sci #Conferences by @eperlste http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003789 Great list but no mention of #crowdsourced note taking
‘Kardashian index’ in science
July 30, 2014A great article discussing the major issue of hyped social media presence:
“Social media makes it very easy for people to build a seemingly impressive persona by essentially ‘shouting louder’ than others. Having an opinion on something does not make one an expert.”
