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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44589?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</guid>
	<pubDate>Sat, 08 Jun 2024 16:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</link>
	<title><![CDATA[MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly]]></title>
	<description><![CDATA[<p><span>The MetaGraph framework</span><span>&nbsp;is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as&nbsp;</span><a href="https://metagraph.ethz.ch/#query">sequence search</a><span>&nbsp;or&nbsp;</span><a href="https://metagraph.ethz.ch/#assembly">differential assembly</a><span>.</span></p>
<p><span>Searcg link&nbsp;https://metagraph.ethz.ch/search&nbsp;</span></p>
<p><span>Pre-print&nbsp;https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4&nbsp;</span></p><p>Address of the bookmark: <a href="https://metagraph.ethz.ch/" rel="nofollow">https://metagraph.ethz.ch/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</guid>
	<pubDate>Thu, 22 Mar 2018 10:40:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2.0: ultra fast and sensitive protein search and clustering suite]]></title>
	<description><![CDATA[<p>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</p>
<p>The MMseqs2 user guide is available as&nbsp;<a href="https://github.com/soedinglab/mmseqs2/wiki">Github Wiki</a>&nbsp;or as&nbsp;<a href="https://mmseqs.com/latest/userguide.pdf">PDF file</a>&nbsp;(Thanks to&nbsp;<a href="https://github.com/jgm/pandoc">pandoc</a>!)</p>
<p>Please cite:&nbsp;<a href="https://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3988.html">Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017)</a>.</p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42664/common-bioinformatics-interview-questions</guid>
	<pubDate>Sat, 23 Jan 2021 06:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42664/common-bioinformatics-interview-questions</link>
	<title><![CDATA[Common Bioinformatics Interview Questions !]]></title>
	<description><![CDATA[<p>The possibility of an interview for a bioinformatics position in the life sciences may be very disquieting, but the same concerns emerge time and again in my experience. So, it is exceedingly worthwhile to plan for future bioinformatics interview questions. Doing this will really give you the advantage in obtaining the position.</p><p>The following 5 questions are those that I have heard many times during the job-search process. There is no reason for not planning responses in such situations.</p><p><strong>1. Tell Us About Yourself</strong><br />This is a very typical opener in interviews. It's a perfect question to ask, and getting something planned will really help you concentrate and ease in the conversation. However, you need to make sure that your response is applicable to the job you're interviewing.<br />It's probably better to keep your answer professional. Try to include these in the answer as well: where did your love of science and bioinformatics come from? How the heck did you end up in this field? Why programming and scripting ?</p><p><strong>2. What is your plan for your bioinformatics career? / How do you look at yourself in five years? / How are your personal objectives to accomplish these goals / What are the plan for your research fundings ?</strong></p><p>Your CV/resume has already impressed the selection panel if you have been invited for an interview. The questions from the bioinformatics interview team provide an incentive for you to market yourself and illustrate the work in question with the most appropriate knowledge.</p><p><strong>3. What do you understand about the job description/What would your suggested research path be if you were a successful candidate?</strong><br />Summarize the specifics of the advertised bioinformatics position in your own words. Follow on with some suggestions of how you want to extend your research and create your own projects within the community.</p><p><strong>4. Will you work as a group or do you want to work on your own?</strong><br />This requirement can vary from jobs to job, so when addressing, be alert. A company/research PI may need a bioinformatician that is able to work on a single project autonomously, or they may need a person who can help direct and organize a team. In your response, refer to the job description.</p><p><strong>5. What particular methods have you used to date with your experiments?</strong><br />You might have experience with all the laboratory techniques described in the job description, but stress the ones you highly experienced with. Highlight your professional abilities and stress that you are extremely capable of mastering new techniques with others ...</p><p>At the end of the day, remember that you're questioning the jury as well as they're interviewing you. You will ought to think of any questions you would like the interview panel to pose. This indicates that you have done your homework and serious about the position.</p><p>All the best for your future job interview.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43683/genview-a-phylogeny-based-comparative-genomics-software-to-analyze-the-genetic-environment-of-genes</guid>
	<pubDate>Tue, 28 Dec 2021 01:49:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43683/genview-a-phylogeny-based-comparative-genomics-software-to-analyze-the-genetic-environment-of-genes</link>
	<title><![CDATA[GEnView: A phylogeny based comparative genomics software to analyze the genetic environment of genes]]></title>
	<description><![CDATA[<p><span>A phylogeny based comparative genomics software to analyze the genetic environment of genes. The user can select one or several taxa and provide one or several reference protein(s). Genomes and plasmids (based on user choice) will be downloaded from the NCBI Assembly/NR database and searched for the respective gene. Alternatively, custom genomes can be provided. User selected stretches (20kbp by default) of the genes genetic environment are extracted, annotated and aligned between all genomes. The sequences are then visualized, enabling comparison of synteny and gene content.</span></p>
<p><span>More at&nbsp;https://pubmed.ncbi.nlm.nih.gov/34951622/</span></p><p>Address of the bookmark: <a href="https://github.com/EbmeyerSt/GEnView" rel="nofollow">https://github.com/EbmeyerSt/GEnView</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30234/last</guid>
	<pubDate>Mon, 19 Dec 2016 14:07:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30234/last</link>
	<title><![CDATA[LAST]]></title>
	<description><![CDATA[<p>LAST can:</p>
<ul>
<li>Handle&nbsp;<strong>big</strong>&nbsp;sequence data, e.g:
<ul>
<li>Compare two vertebrate genomes</li>
<li>Align billions of DNA reads to a genome</li>
</ul>
</li>
<li>Indicate the&nbsp;<a href="http://lastweb.cbrc.jp/about.html">reliability</a>&nbsp;of each aligned column.</li>
<li>Use sequence quality data&nbsp;<a href="http://nar.oxfordjournals.org/content/38/7/e100.abstract">properly</a>.</li>
<li>Compare DNA to proteins, with frameshifts.</li>
<li>Compare PSSMs to sequences</li>
<li>Calculate the likelihood of chance similarities between random sequences.</li>
<li>Do split and spliced alignment.</li>
<li><a href="http://last.cbrc.jp/doc/last-train.html">Train</a>&nbsp;alignment parameters for unusual kinds of sequence (e.g. nanopore).</li>
</ul><p>Address of the bookmark: <a href="http://last.cbrc.jp/" rel="nofollow">http://last.cbrc.jp/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42421/geo2r-compare-two-or-more-groups-of-samples</guid>
	<pubDate>Sun, 20 Dec 2020 11:49:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42421/geo2r-compare-two-or-more-groups-of-samples</link>
	<title><![CDATA[GEO2R: compare two or more groups of Samples]]></title>
	<description><![CDATA[<p><span>GEO2R to compare two or more groups of Samples in order to identify genes that are differentially expressed across experimental conditions.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/geo/geo2r/" rel="nofollow">https://www.ncbi.nlm.nih.gov/geo/geo2r/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</guid>
	<pubDate>Fri, 17 Sep 2021 01:57:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</link>
	<title><![CDATA[LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets]]></title>
	<description><![CDATA[<p><span>The pipeline was developed based on a popular workflow framework&nbsp;</span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a><span>, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report.&nbsp;</span><a href="https://github.com/likelet/LncPipe">LncPipe</a><span>&nbsp;allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.</span></p>
<p>Ref&nbsp;https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/</p>
<p><img src="https://ars.els-cdn.com/content/image/1-s2.0-S1673852718301176-gr1.jpg" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/likelet/LncPipe" rel="nofollow">https://github.com/likelet/LncPipe</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9429/srf-vacancy-at-nipgr</guid>
  <pubDate>Tue, 25 Mar 2014 19:20:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Vacancy at NIPGR]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for filling up the purely temporary position of one Senior Research Fellow in DST’s Indo-Australian Joint project (with ICRISAT) entitled “Genomic Approach for Stress Tolerant Chickpea” under the guidance of Dr. Mukesh Jain, Scientist, NIPGR.</p>

<p>(A) Senior Research Fellow (One Post):    Emoluments as per DST/DBT norms.</p>

<p>Candidates having M.Sc. degree (with minimum of 55% marks) or equivalent in Life Sciences/Biotechnology/Bioinformatics/ Molecular Biology or any other related field with minimum of two years of post M.Sc. research experience are eligible to apply. The candidate having computer skill (Linux, Perl, Java, MySQL) and/or experience in advanced molecular biology, next generation sequencing data analysis and molecular markers analysis will be preferred.</p>

<p>The position is completely on temporary basis and co-terminus with the project. The initial appointment will be for one year, which can be curtailed/extended on the basis of assessment of the candidate’s performance and discretion of the Competent Authority. NIPGR reserves the right to select the candidate against the above posts depending upon the qualifications and experience of the candidates. Reservation of posts shall be as per Govt. of India norms.</p>

<p>Eligible candidates may apply by sending hard copy of completed application in the given format with a cover letter showing interest and attested copies of the certificates and proof of research experience. The applications should reach at the address given below within 15 days from the date of the advertisement. The subject line on envelope must be superscribed by “Application for the Post of SRF in DST - AISRF project”.</p>

<p>Note: ONLY hard copy of the application in the given format will be accepted.</p>

<p>Last date April 03, 2014</p>

<p>Dr. Mukesh Jain<br />Staff Scientist<br />National Institute of Plant Genome Research<br />Aruna Asaf Ali Marg, P.O. Box NO. 10531,<br />New Delhi - 110067</p>

<p>Advertisement: http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44934/genomic-basis-of-evolutionary-innovations-gevol</guid>
	<pubDate>Sat, 06 Dec 2025 06:11:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44934/genomic-basis-of-evolutionary-innovations-gevol</link>
	<title><![CDATA[Genomic Basis of Evolutionary Innovations (GEvol)]]></title>
	<description><![CDATA[<p>The Priority Programme (SPP 2349) funded by German Science Foundation (DFG) started 2022: &bdquo;Genomic Basis of Evolutionary Innovations (GEvol)&ldquo;</p>
<p>GEvol is unique as it will use, for the first time, a large taxonomic group to focus on one goal: to characterise the dynamics and mechanisms of genomic innovations underlying novel traits using comparative evolutionary genomics (and related data).<br>Thus, projects participating in GEvol we will ask fundamental evolutionary questions such as:<br>1. At what level is evolution repeatable?<br>2. How does genomic plasticity interfere with phenotypic plasticity during evolution?<br>3. How do inter- and intra-specific interactions influence genomic architectures?<br>4. How predictable is phenotypic variation given some knowledge about the dynamics and mechanisms of underlying genome evolution?</p><p>Address of the bookmark: <a href="https://g-evol.uni-muenster.de/open-positions/" rel="nofollow">https://g-evol.uni-muenster.de/open-positions/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</guid>
	<pubDate>Thu, 23 Nov 2017 08:37:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</link>
	<title><![CDATA[Taxoblast : Taxoblast is a pipeline to identify contamination in genomic sequence]]></title>
	<description><![CDATA[<p><span>Modern genome sequencing strategies are highly sensitive to contamination making the detection of foreign DNA sequences an important part of analysis pipelines. Here we use Taxoblast, a simple pipeline with a graphical user interface, for the post-assembly detection of contaminating sequences in the published genome of the kelp&nbsp;</span><em>Saccharina japonica</em><span>. Analyses were based on multiple blastn searches with short sequence fragments. They revealed a number of probable bacterial contaminations as well as hybrid scaffolds that contain both bacterial and algal sequences. This or similar types of analysis, in combination with manual curation, may thus constitute a useful complement to standard bioinformatics analyses prior to submission of genomic data to public repositories. Our analysis pipeline is open-source and freely available at&nbsp;</span><a href="http://sdittami.altervista.org/taxoblast" title="">http://sdittami.altervista.org/taxoblast</a><span>&nbsp;and via SourceForge (</span><a href="https://sourceforge.net/projects/taxoblast" title="">https://sourceforge.net/projects/taxoblast</a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/taxoblast/files/" rel="nofollow">https://sourceforge.net/projects/taxoblast/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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