Here is a link for some helpful information on the new NIH format for biosketches:
Posts Tagged ‘email’
New NIH Biosketch–Helpful Website
January 23, 2015NEw paper using BrainSpan data
January 12, 2015The discovery of integrated gene networks for autism and related disorders
Fereydoun Hormozdiari
Osnat Penn
Elhanan Borenstein
Evan E. Eichler
Published in Advance November 5, 2014, doi:10.1101/gr.178855.114 Genome Res. 2015. 25: 142-154
QT:{{”
Motivated by this observation, we have developed a novel method that simultaneously integrates information from both PPI and coexpression networks to identify highly connected modules in both types of networks that are also enriched in mutations in cases and not in controls. We call this method MAGI, short for merging affected genes into integrated networks. MAGI is based on a combinatorial
optimization algorithm that aims to maximize the number of mutations in the modules while accounting for gene length and distribution of putative LoF and missense mutations in cases and controls. MAGI is generic and can be applied to any disease, given a list of de novo mutations in cases and relevant coexpression information. Using neurodevelopmental RNA-seq data from the BrainSpan Atlas
(http://www.brainspan.org/), we have applied it to exome sequence data generated from ASD, ID, epilepsy, and schizophrenia, providing a comprehensive comparison of common and specific gene modules for these diseases.
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example experiment.com research
June 23, 2014Experiment.com specializes in funding early-stage research projects by way of “crowd-funding” (similar concept to Kickstarter).
Here is a recent example of the type of research funded: https://experiment.com/projects/what-are-the-patterns-and-effects-of-american-crow-movements
GDoc Track Changes
June 14, 2014Track-changes in #GDocs, plug-in that provides some functionality. However, wish #Google just had this built-in.
https://chrome.google.com/webstore/detail/track-changes/pgjeblaieehjmmahlikmifaggjckpcnp?hl=en
Use of ontologies in RNAseq data analysis
December 16, 2013came across this paper: http://genomebiology.com/content/11/2/R14, which uses GO for RNA-seq data analysis
looks interesting – GoSeq !
linkstream2 microblog 