Biomarkers and Personalized Medicine A Review of Bioinformatics Blogs « Homologus Homolog.us blog is written by professional janitors dedicated to clean up US science. During lunch breaks and other time off from the job, we discuss bioinformatics. The name 'homolog.us' is not a spelling mistake, but is derived by taking Arabic translation of the 'O' in the original word. Please follow us on twitter – @homolog_us. To stay up to date with our commentaries, please follow us on twitter here Today we are reviewing and cleaning up the blog links at the right sidebar. The following three blogs are the ones most visited by us. Living in an Ivory Basement It is a blog maintained by Titus Brown, a Professor from Michigan State University. Why do we say so? The blog is updated once a week, but many updates have enough value to keep you thinking for weeks. NGS – Stuart Brown The blog is maintained by Stuart Brown, an Associate Professor at NYU School of Medicine. RNA-seq Blog This blog provides daily updates on published algorithms and research results related to RNA-seq. Openhelix
Regex Tutorial—From Regex 101 to Advanced Regex Life Sciences & Mathematics & Physical Sciences | Bioinformatics | Next Generation Sequencing Next-generation sequencing technologies are revolutionising genomics and their effects are becoming increasingly widespread. Many tools and algorithms relevant to next-generation sequencing applications have been published in Bioinformatics, and so to celebrate this contribution we have gathered these together in this 'Bioinformatics for Next Generation Sequencing' virtual issue. This will be a living resource that we will continually update to include the very latest papers in this area to help researchers keep abreast of the latest developments. Review: Harnessing virtual machines to simplify next-generation DNA sequencing analysisJulie Nocq et al. Bioinformatics (2013) 29 (17): 2075-2083 doi:10.1093/bioinformatics/btt352 Full Text Editorial -Bioinformatics for Next Generation Sequencing Alex Bateman and John QuackenbushBioinformatics (2009) 25: 429 Full Text Alignment Optimal spliced alignments of short sequence readsFabio De Bona et al.Bioinformatics (2008) 24: i174-80 Full Text ZOOM!
Top Bioinformatics Contributions of 2012 « Homologus Homolog.us blog is written by professional janitors dedicated to clean up US science. During lunch breaks and other time off from the job, we discuss bioinformatics. The name 'homolog.us' is not a spelling mistake, but is derived by taking Arabic translation of the 'O' in the original word. Please follow us on twitter – @homolog_us. Dear readers, two weeks back we asked for your suggestions for best bioinformatics innovations of 2012. In addition to topics covered in our blog over the entire year, we received several other good suggestions by email and in the comment section. That was lot of work, but then we faced the dilemma of how to judge between topics as diverse as a very good alignment algorithm and an excellent educational resource in bioinformatics. Please feel free to discuss in the comment section, if you do not agree with our choices or would like to suggest other interesting contributions missed by us. Best blog + Twitter feed – Getting Genetics Done + @genetics_blog 1. 2.
bedtools: a powerful toolset for genome arithmetic — bedtools 2.30.0 documentation Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line. bedtools is developed in the Quinlan laboratory at the University of Utah and benefits from fantastic contributions made by scientists worldwide. We have developed a fairly comprehensive tutorial that demonstrates both the basics, as well as some more advanced examples of how bedtools can help you in your research. Commands used:
OpenHelix Blog us ENCODE leaders published their latest propaganda piece in PNAS - “Defining functional DNA elements in the human genome” and Dan Graur has done fantastic work of tearing it apart. @ENCODE_NIH in PNAS 2014: In 2012, the Dog Ate Our Lab Notebook and We Had No Laxative to Retrieve It Instead of rewriting his blog post, let us comment on random samples from here and there in the article. —————————————————————Marketing Your Science, LLC We never had honor of writing papers with co-authors from ‘scientific’ organizations like above. That leads to the questions of how much of the PNAS paper is science and how much is ‘advertising’ (i.e. half truths and systematic efforts to hide the negatives)? —————————————————————Proposed Future plan In the last paragraph, ENCODE tells us what their next ‘big science’ scheme is going to be. The data identify very large numbers of sequence elements of differing sizes and signal strengths. That is downright scary !! On Functional Elements ENCODE clowns wrote - Q1.
18.04.6 LTS (Bionic Beaver) Ubuntu is distributed on three types of images described below. Desktop image The desktop image allows you to try Ubuntu without changing your computer at all, and at your option to install it permanently later. This type of image is what most people will want to use. 64-bit PC (AMD64) desktop image Choose this if you have a computer based on the AMD64 or EM64T architecture (e.g., Athlon64, Opteron, EM64T Xeon, Core 2). Server install image The server install image allows you to install Ubuntu permanently on a computer for use as a server. 64-bit PC (AMD64) server install image A full list of available files, including BitTorrent files, can be found below. If you need help burning these images to disk, see the Image Burning Guide.
RHIPE: An Interface Between Hadoop and R for Large and Complex Data Analysis | LectureMaker, LLC Ron Fredericks writes: Dr. Saptarshi Guha created an open-source interface between R and Hadoop called the R and Hadoop Integrated Processing Environment or RHIPE for short. LectureMaker was on the scene filming Saptarshi’s RHIPE presentation to the Bay Area’s useR Group, introduced by Michael E. Driscoll and hosted at Facebook’s Palo Alto office on March 9′th 2010. Special thanks to Jyotsna Paintal for helping me film the event. Saptarshi received his Ph.D from Purdue University in 2010, having been advised by Dr. Hadoop is an open source implementation of both the MapReduce programming model, and the underlying file system Google developed to support web scale data.The MapReduce programming model was designed by Google to enable a clean abstraction between large scale data analysis tasks and the underlying systems challenges involved in ensuring reliable large-scale computation. The RHIPE Video Video Topics and Navigation Table Code Examples from the Video Code (r) References:
: Lab is Simple Step 1: Download Ubuntu 18.04 from Link: Step 2: Install Ubuntu. Select install Open SSHSet the hard disk. You should give all hardisk you have for ubuntu_lv Step 3: Login as root: Login by account you use to create ubuntu 18.04go to root by command sudo -iSet password for root by command: passwdAllow root access over SSH run command: sed -i -e "s/. Step 2: Add repository to end of file: /etc/apt/sources.list deb [trusted=yes] Step 3: Make sure your server can connect to internetRun bellow commandsecho "nameserver 8.8.8.8" > /etc/resolv.confapt-get updateapt-get purge netplan.ioapt-get install pnetlab -y Note: May be get error in installing process. run apt-get update then install pnetlab again apt-get install pnetlab -y Reboot Step 4: Upgrade to the latest version. Follow this guide to upgrade to the latest version: