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g++ compiler for STAR aligner v 2.7.0e - Google Groups | https://groups.google.com/
Google Groups allows you to create and participate in online forums and email-based groups with a rich experience for community conversations.
build  fromsource  c++11  bioinformatics  star  aligner 
march 2019 by kme
bed to bigBed conversion | https://www.biostars.org/
<code class="language-bash">
$ wget http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/bedToBigBed
$ wget http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/fetchChromSizes
$ chmod +x ./bedToBigBed ./fetchChromSizes
$ ./fetchChromSizes hg38 > hg38.chrom.sizes
$ sort-bed regions.unsorted.bed > regions.bed
$ ./bedToBigBed regions.bed hg38.chrom.sizes regions.bb
</code>
ucsc  genomebrowser  bigbed  bioinformatics  solution 
january 2019 by kme
Introduction to Circos, Features and Uses // CIRCOS Circular Genome Data Visualization | http://circos.ca/
Have you noticed how beautifully everyday science and technology is rendered in movies? Information is delivered seamlessly from interfaces oozing with style and function. While others complain that the movie doesn't get the science facts right, I contrarily note that it doesn't get the science look right. No busy scientist is able to make such great design and type face choices!
visualization  infographic  plots  bioinformatics 
december 2018 by kme
Healing the NIH-funded Biomedical Research Enterprise | https://www.ncbi.nlm.nih.gov/
1. Casadevall A, Fang FC. Reforming science: methodological and cultural reforms. Infect Immun. 2012;80:891–6. [PMC free article] [PubMed]
2. Alberts B, Kirschner MW, Tilghman S, Varmus H. Rescuing US biomedical research from its systemic flaws. Proc Natl Acad Sci U S A. 2014;111:5773–72014. [PMC free article] [PubMed]
3. Alberts B, Kirschner MW, Tilghman S, Varmus H. Opinion: Addressing systemic problems in the biomedical research enterprise. Proc Natl Acad Sci U S A. 2015;112:1912–3. [PMC free article] [PubMed]
4. Daniels RJ. A generation at risk: young investigators and the future of the biomedical workforce. Proc Natl Acad Sci U S A. 2015;112:313–8. [PMC free article] [PubMed]
5. Lorsch JR. Maximizing the return on taxpayers’ investments in fundamental biomedical research. Mol. Biol. Cell. 2015;26:1578–1582. [PMC free article] [PubMed]
research  bioinformatics  funding  commentary  opinion 
november 2018 by kme
Gene Frequently Asked Questions - Gene Help - NCBI Bookshelf | https://www.ncbi.nlm.nih.gov/
Here's probably the canonical reference for ftp://ftp.ncbi.nlm.nih.gov/gene/DATA/GENE_INFO/, where you can get aliases (and ENSG IDs) for all mammalian genes.
gene  geneid  genealias  bioinformatics  reference 
november 2018 by kme
The myths of bioinformatics software | Bits of DNA | https://liorpachter.wordpress.com/
If you make your software free for commercial use, you are effectively creating a subsidy for companies, one that is funded by your university / your grants. You are a corporate hero! Congratulations! You have found a loophole for transferring scarce public money to the private sector. If you’ve licensed your software with BSD you’ve added another subsidy: a company using your software doesn’t have any reason to share their work with the academic community. There are two reasons why you might want to reconsider offering such subsidies. First, by denying yourself potential profits from sale of your software to industry, you are definitively removing any incentive for future development/maintenance of the software by yourself or future graduate students. Most bioinformatics software, when sold commercially, costs a few thousand dollars. This is a rounding error for companies developing cancer or other drugs at the cost of a billion dollars per drug and a tractable proposition even for startups, yet the money will make a real difference to you three years out from your Ph.D. when you’re earning a postdoc salary.
licensing  bioinformatics  devel  software  myths  debunked 
june 2018 by kme
Experimental Factor Ontology - Summary | NCBO BioPortal | http://bioportal.bioontology.org/
The Experimental Factor Ontology (EFO) is an application focused ontology modelling the experimental variables in multiple resources at the EBI and Open Targets. The ontology has been developed to increase the richness of the annotations that are currently made in resources and to promote consistent annotation, to facilitate automatic annotation and to integrate external data. The ontology pulls together classes from reference ontologies such as disease, cell line, cell type and anat...
bioinformatics  disease  phenotype  searchengine  ontology 
february 2018 by kme
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