<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38413?offset=370</link>
	<atom:link href="https://bioinformaticsonline.com/related/38413?offset=370" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</guid>
	<pubDate>Tue, 02 May 2017 07:58:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</link>
	<title><![CDATA[Mapping NGS]]></title>
	<description><![CDATA[<p>NGS data are just a bunch of sequences, you have no idea which region in the genome each sequences comes from, which gene it represents...<br>To know that you have to align the sequences to the reference sequence. The reference sequence is in most cases the full genome sequence but sometimes, a library of EST sequences is used.<br>In either way, aligning your sequence reads to the reference sequence is called mapping.</p>
<p>The most used mappers of DNA-seq data are&nbsp;<a href="http://bio-bwa.sourceforge.net/" target="_blank">BWA</a>&nbsp;and&nbsp;<a href="http://bowtie-bio.sourceforge.net/bowtie2/index.shtml" target="_blank">Bowtie</a>&nbsp;for DNA-Seq data and&nbsp;<a href="http://tophat.cbcb.umd.edu/" target="_blank">Tophat</a>,&nbsp;<a href="https://github.com/alexdobin/STAR" target="_blank">STAR</a>&nbsp;or&nbsp;<a href="http://www.ccb.jhu.edu/software/hisat/index.shtml" target="_blank">HISAT</a>&nbsp;for RNA-Seq data. Mappers differ in which options they can take in, how fast and how accurate they are. Bowtie is faster than BWA, but looses some sensitivity (does not map an equal amount of reads to the correct position in the genome).</p><p>Address of the bookmark: <a href="http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data" rel="nofollow">http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</guid>
	<pubDate>Tue, 23 May 2017 05:20:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</link>
	<title><![CDATA[GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.]]></title>
	<description><![CDATA[<p><span>GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexeyG/GRASS" rel="nofollow">https://github.com/AlexeyG/GRASS</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/34368/srbioinformatics-analyst-ngs-at-ocimum</guid>
  <pubDate>Fri, 17 Nov 2017 07:50:44 -0600</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) at Ocimum]]></title>
  <description><![CDATA[
<p>JOB FUNCTIONBio Tech/R&amp;D/Scientist<br />INDUSTRYBiotechnology/Pharmaceutical/Medicine<br />SPECIALIZATIONBasic Research,Bio-Statistician,Clinical Research<br />QUALIFICATION<br />Any Post Graduate<br />BA (Arts), B.Com. (Commerce), BE/ B.Tech (Engineering), B.Pharm. (Pharmacy), B.Sc. (Science), BL/LLB, BDS (Dental Surgery), B.Ed. (Education), BHM (Hotel Management), BBA/ BBM/ BBS, B.Arch. (Architecture), BCA (Computer Application), Diploma-Other Diploma, B.Plan. (Planning), BGL, B.V.Sc. (Veterinary Science), Other School/ Graduation, BHMS (Homeopathy), BAMS (Ayurveda)<br />Job Description</p>

<p>1.  Must have basic understanding of molecular biology and Genomics.<br />2. Experience in application development or must have expertise in programming using either of Perl/Python.<br />3.  Experience in statistical programming using R/Bioconductor/Matlab.<br />4. Strong concept in statistical and mathematical modelling.<br />5.  Experience in designing and developing the bioinformatics pipeline.<br />6.  Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.<br />7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.<br />8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.<br />9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.<br />10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.<br />11. Ability to work as team as well as independently with minimal support.</p>

<p>More at http://www3.ocimumbio.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36758/pbalign-maps-pacbio-reads-to-reference-sequences-and-saves-alignments-to-a-bam-file</guid>
	<pubDate>Thu, 24 May 2018 10:06:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36758/pbalign-maps-pacbio-reads-to-reference-sequences-and-saves-alignments-to-a-bam-file</link>
	<title><![CDATA[pbalign: maps PacBio reads to reference sequences and saves alignments to a BAM file]]></title>
	<description><![CDATA[pbalign aligns PacBio reads to reference sequences, filters aligned reads according to user-specific filtering criteria, and converts the output to either the SAM format or PacBio Compare HDF5 (e.g., .cmp.h5) format. The output Compare HDF5 file will be compatible with Quiver if --forQuiver option is specified.<p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/pbalign" rel="nofollow">https://github.com/PacificBiosciences/pbalign</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37236/installing-salmon-for-trinity</guid>
	<pubDate>Tue, 03 Jul 2018 09:02:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37236/installing-salmon-for-trinity</link>
	<title><![CDATA[Installing Salmon for Trinity !]]></title>
	<description><![CDATA[
<p>➜  trinityrnaseq-Trinity-v2.6.6 git:(master) ✗ conda install salmon<br />Solving environment: done</p>

<p>## Package Plan ##</p>

<p>  environment location: /home/urbe/anaconda3</p>

<p>  added / updated specs: <br />    - salmon</p>

<p>The following packages will be downloaded:</p>

<p>    package                    |            build<br />    ---------------------------|-----------------<br />    boost-1.64.0               |           py36_4         331 KB  conda-forge<br />    jemalloc-5.1.0             |       hfc679d8_0         8.2 MB  conda-forge<br />    boost-cpp-1.64.0           |                1        17.8 MB  conda-forge<br />    salmon-0.10.2              |                1         3.7 MB  bioconda<br />    conda-4.5.5                |           py36_0         624 KB  conda-forge<br />    tbb-2018_20171205          |                0         1.2 MB  conda-forge<br />    ------------------------------------------------------------<br />                                           Total:        31.8 MB</p>

<p>The following NEW packages will be INSTALLED:</p>

<p>    boost:     1.64.0-py36_4    conda-forge<br />    boost-cpp: 1.64.0-1         conda-forge<br />    jemalloc:  5.1.0-hfc679d8_0 conda-forge<br />    salmon:    0.10.2-1         bioconda   <br />    tbb:       2018_20171205-0  conda-forge</p>

<p>The following packages will be UPDATED:</p>

<p>    conda:     4.5.4-py36_0     conda-forge --&gt; 4.5.5-py36_0 conda-forge</p>

<p>Proceed ([y]/n)? y</p>

<p>Downloading and Extracting Packages<br />boost-1.64.0         |  331 KB | ####################################################################################################################################### | 100% <br />jemalloc-5.1.0       |  8.2 MB | ####################################################################################################################################### | 100% <br />boost-cpp-1.64.0     | 17.8 MB | ####################################################################################################################################### | 100% <br />salmon-0.10.2        |  3.7 MB | ####################################################################################################################################### | 100% <br />conda-4.5.5          |  624 KB | ####################################################################################################################################### | 100% <br />tbb-2018_20171205    |  1.2 MB | ####################################################################################################################################### | 100% <br />Preparing transaction: done<br />Verifying transaction: done<br />Executing transaction: done</p>
]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</guid>
	<pubDate>Fri, 09 Nov 2018 13:34:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</link>
	<title><![CDATA[AMStat: display statistics of large sequence files from next generation sequencing projects]]></title>
	<description><![CDATA[<p><span>SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to&nbsp;</span><a href="http://samstat.sourceforge.net/#about">SAM/BAM</a><span>&nbsp;files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.</span></p><p>Address of the bookmark: <a href="http://samstat.sourceforge.net/" rel="nofollow">http://samstat.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/39469/introduction-to-bioinformatics</guid>
	<pubDate>Wed, 05 Jun 2019 14:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/39469/introduction-to-bioinformatics</link>
	<title><![CDATA[Introduction to Bioinformatics]]></title>
	<description><![CDATA[<p><img src="https://edu.t-bio.info/wp-content/uploads/2017/07/Introduction-Course-Title-11.jpg" alt="Introduction to Bioinformatics Course" width="600" height="315.6" style="vertical-align: top; border: 0px; border: 0px;"></p><p>Introduction to bioinformatics is a course for biologists and clinicians that would like to learn more about the way bioinformatics is used in healthcare, biotech and pharmaceuitcal industry as well as basic research. The course covers many of the topics transformed by the emergence of big data and computational technologies. To learn more about the course, visit:&nbsp;<a href="https://edu.t-bio.info/course/introduction-bioinformatics/">https://edu.t-bio.info/course/introduction-bioinformatics/</a></p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</guid>
	<pubDate>Wed, 13 Nov 2019 05:00:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</link>
	<title><![CDATA[Industrial Training in Computer Aided Drug Designing (CADD)]]></title>
	<description><![CDATA[<p>Learn More about&nbsp; Computer Aided Drug Designing (CADD)!!!</p><p>#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,</p><h2 style="text-align: center;"><strong>Batch Starts From 18<sup>th</sup> November 2019</strong></h2><p>#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will&nbsp; learn from industry leaders&nbsp;how to apply these skills in life science &amp; have a command over software developing process &nbsp;by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/40770/scientist-bioinformatics-positions</guid>
  <pubDate>Thu, 30 Jan 2020 06:53:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist Bioinformatics Positions]]></title>
  <description><![CDATA[
<p>Bioinformatics-Multi_Omics_Integration</p>

<p>https://www.researchgate.net/job/939073_Senior_Scientist_Bioinformatics-Multi_Omics_Integration</p>

<p> <br />Senior_Scientist_Bioinformatics-Transcriptomics_Analysis     </p>

<p>https://www.researchgate.net/job/939075_Senior_Scientist_Bioinformatics-Transcriptomics_Analysis-Belgium_France_Switzerland_The_Netherlands</p>

<p>Senior Scientist Bioinformatics - Network Analytics</p>

<p>https://www.researchgate.net/job/939070_Senior_Scientist_Bioinformatics-Network_Analytics_Belgium_France_Switzerland_the_Netherlands</p>

<p>Team Leader Bioinformatics Data Sciences - Mechelen, Belgium</p>

<p>https://www.researchgate.net/job/938787_Team_Leader_Bioinformatics_Data_Sciences-Mechelen_Belgium</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</guid>
	<pubDate>Thu, 28 May 2020 21:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</link>
	<title><![CDATA[Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data]]></title>
	<description><![CDATA[<p>Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.</p>
<p>Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.</p><p>Address of the bookmark: <a href="https://github.com/dnanexus/parliament2" rel="nofollow">https://github.com/dnanexus/parliament2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>