Posts Tagged ‘from_stl’

Small research teams ‘disrupt’ science more radically than large ones

Friday, March 1st, 2019

QT:[[”
“The authors describe and validate a citation-based index of ‘disruptiveness’ that has previously been proposed for patents6. The intuition behind the index is straightforward: when the papers that cite a given article also reference a substantial proportion of that article’s references, then the article can be seen as consolidating its scientific domain. When the converse is true — that is, when future citations to the article do not also acknowledge the article’s own intellectual forebears — the article can be seen as disrupting its domain.

The disruptiveness index reflects a characteristic of the article’s underlying content that is clearly distinguishable from impact as conventionally captured by overall citation counts. For instance, the index finds that papers that directly contribute to Nobel prizes tend to exhibit high levels of disruptiveness, whereas, at the other extreme, review articles tend to consolidate their fields.”
“]]

http://www.nature.com/articles/d41586-019-00350-3

George Church Medical Info

Saturday, January 6th, 2018

https://my.pgp-hms.org/profile/hu43860C
George Church discloses a lot of his medical records

Timing, rates and spectra of human germline mutation : Nature Genetics : Nature Publishing Group

Tuesday, May 17th, 2016

Timing, rates & spectra of human germline mutation
http://www.nature.com/ng/journal/v48/n2/full/ng.3469.html Metaanalysis of >6500 events gives a de novo mutational signature

PLOS Genetics: A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures

Saturday, February 27th, 2016

Model-Based Approach to Inferring…#Cancer Mutation Signatures http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005657 Assuming independence betw 3 NTs, 11 v 95 parameters

QT:{{”
The first contribution of this paper is to suggest a more parsimonious approach to modelling mutation signatures, with the benefit of producing both more stable estimates and more easily interpretable signatures. In brief, we substantially reduce the number of parameters per signature by breaking each mutation pattern into “features”, and assuming independence across mutation features. For example, consider the case where a mutation pattern is defined by the substitution and its two flanking bases. We break this into three features
(substitution, 3′ base, 5′ base), and characterize each mutation signature by a probability distribution for each feature (which, by our independence assumption, are multiplied together to define a distribution on mutation patterns). Since the number of possible values for each feature is 6, 4, and 4 respectively this requires 5 + 3 + 3 = 11 parameters instead of 96 − 1 = 95 parameters. Furthermore, extending this model to account for ±n neighboring bases requires only 5 + 6nparameters instead of 6 × 42n − 1. For example, considering ±2 positions requires 17 parameters instead of 1,535. Finally,
incorporating transcription strand as an additional feature adds just one parameter, instead of doubling the number of parameters. “}}

Identification of neutral tumor evolution across cancer types : Nature Genetics : Nature Publishing Group

Saturday, February 27th, 2016

Neutral tumor #evolution across #cancer types
http://www.nature.com/ng/journal/v48/n3/full/ng.3489.html Initial burst of driver events followed by random mutations

H1B visa statistics

Thursday, July 23rd, 2015

http://www.myvisajobs.com/

1000 or 1024

Friday, June 26th, 2015

KiB v kb, 1024 v 1000. Appears powers of 10 win out over powers of 2 http://www.quora.com/Where-do-we-use-1-kB-1000-bytes-1-MB-1000-kB-1-GB-1000-MB-1-TB-1000-GB-And-where-do-we-use-1-KB-1024-bytes-1-MB-1024-KB-1-GB-1024-MB-1-TB-1024-GB

Calendar exporter

Thursday, August 14th, 2014

calendar exporter:

http://www.gcal2excel.com/

It is simple but does the work you need: calendar exporting, event filter based on keywords and simple statistics.