Posts Tagged ‘scinews’

The quiet rise of the NIH’s hot new metric : Nature News & Comment

November 16, 2016

The quiet rise of the NIH’s hot new #metric [RCR] Rank a popular paper in boring field be highly? HT @Magda_Skipper

Researchers wrestle with a privacy problem

September 25, 2016

Researchers wrestle w. a #privacy problem Qt: “Public trust is…fragile – it’s difficult to build & easy to break”

“The lesson is to not underestimate public concerns,” she says. “Public trust is very fragile — it’s difficult to build and easy to break.””

In dramatic statement, European leaders call for ‘immediate’ open access to all scientific papers by 20 20

June 7, 2016

European leaders call for immediate #OpenAccess to all sci papers by
’20 Spearheaded by Holland, home to Elsevier

“goal is part of a broader set of recommendations in support of open science, a concept that also includes improved storage of and access to research data. The Dutch government, which currently holds the rotating E.U. presidency, had lobbied hard for Europe-wide support for open science, as had Carlos Moedas, the European commissioner for research and innovation.
We probably don’t realize it yet, but what the Dutch presidency has achieved is just unique and huge,” Moedas said

Who’s downloading pirated papers?

May 2, 2016

“Bill Hart-Davidson, MSU’s associate dean for graduate education, suggests that the likely answer is “text-mining,” the use of computer programs to analyze large collections of documents to generate data. When I called Hart-Davidson, I suggested that the East Lansing Sci-Hub scraper might be someone from his own research team. But he laughed and said that he had no idea who it was. But he understands why the scraper goes to Sci-Hub even though MSU subscribes to the downloaded ” “}}

Who’s downloading pirated papers? Everyone freely available data on @scihub usage

The Stem-Cell Scandal

April 10, 2016

The #StemCell Scandal #STAP (stim.-triggered acquisition of pluripotency) & why it’s bad to over-believe your data

How quality control could save your science : Nature News & Comment

February 7, 2016

How QC could save your science “Traceable Data” is a key for #ReproducibleResearch via @iddux

Glycan Notation Standardized At Last | January 4, 2016 Issue – Vol. 94 Issue 1 | Chemical & Engineering News

January 13, 2016

Glycan Notation Standardized Merging 2 systems: essentials (sugars) & Oxford (bonds/angles). A prereq. for glycomics

QT:{{"Carbohydrate chemists and glycobiologists have now agreed on an expanded and standardized symbol nomenclature based primarily on the Essentials notation (Glycobiology 2015, DOI:10.1093/glycob/cwv091). The agreement “is a major step, as without a common vocabulary and language the glycosciences cannot advance as genomics and proteomics have,” says carbohydrate chemist Peter H. Seeberger of the Max Planck Institute of Colloids & Interfaces. For nonglycan experts, here we explain the two notation systems. ▪

The newly standardized Essentials system permits an optional mixed form of notation in which the Oxford system’s angles and dashed and solid bonds are used but its sugar symbols are not.

Species-Specific | The Scientist Magazine(R)

September 6, 2015

Scientists uncover striking differences between mouse and human gene expression across a variety of tissues.
By Jyoti Madhusoodanan | November 17, 2014

The results “go a little against the grain,” said bioinformatician Mark Gerstein of Yale University who was not involved in the study. “We might think that humans and mice are very similar [genetically], but when we compare their transcriptomes, they’re more different than we thought.”

The brain chip

May 13, 2015

The brain chip #Neuromorphic #computers overcome bottlenecks in classic von Neumann architecture

QT:{{"…consists of 20,000 chips, each of which represents 1000 neurons. This fall, Furber says, he expects that number will rise to 100,000 chips representing 100 million neu-rons, and eventually a 1-million-chip system representing 1 billion neurons—about 1% of the neurons in the human brain

All computer chips made today rely on the same general architecture that was outlined nearly 70 years ago. This architecture separates the two primary tasks a chip needs to carry out—processing and memory—into different regions and continuously communicates data back and forth. Though this strategy works well for crunching numbers and running spreadsheets, it’s much less efficient for handling tasks that manage vast amounts of data, such as vision and language processing. But in recent years, researchers around the globe have been pursuing a new approach called neuromorphic computing. On page 668 of this issue, researchers at IBM and Cornell University report creating the world’s first production-scale neuromorphic computing chip. The novel approach to hardware is made up of 5.4 billion transistors that are wired to emulate a brain with 1 million "neurons" that talk to one another via 256 million "synapses."


Core services: Reward bioinformaticians

May 9, 2015

QT:{{"The research system does not recognize bioinformaticians for doing what the scientific community needs most. “People realize the importance, but currently there are no real solutions,” says Xiaole Liu, a bioinformatician at the Dana-Farber Cancer Institute in Boston, Massachusetts, and at Tongji University in Shanghai, China. This is why it can take more than six months to fill positions at a core, why many of biology’s brightest are leaving science for technology companies, and why conventional biologists wait nine months to get help to dissect their data.

Reward bioinformaticians [for collaboration] Despite #bigdata boom, biomedical analysis could be made more appealing