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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/8265?offset=960</link>
	<atom:link href="https://bioinformaticsonline.com/related/8265?offset=960" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16160/research-scientist-%E2%80%93-bioinformatics-at-sidra-medical-and-research-center</guid>
  <pubDate>Wed, 10 Sep 2014 14:35:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Scientist – Bioinformatics at Sidra Medical and Research Center]]></title>
  <description><![CDATA[
<p>Sidra Medical and Research Center(Doha, Qatar) is looking for talented Research Scientists (Bioinformatics / NGS Data Analysis).</p>

<p>Research Scientists within the Bioinformatics Program are involved in research related to cutting edge genomics and analysis of omics data. The research will utilize concepts, theories and best practices obtained from bioinformatics discipline and applied to biological and other biomedical data for analysis. The role may also involve designing databases, algorithm and/or computation methods for analyzing genomics and other omics data.  The scientist will be working closely with the Translational Medicine Program within a state-of-the art research setting.</p>

<p>Please check the details of the opening and apply here: http://careers.sidra.org/sidra/Vacan...acancyID=60181</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36842/gap-filling-or-contigs-extensions-tools</guid>
	<pubDate>Fri, 01 Jun 2018 08:07:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36842/gap-filling-or-contigs-extensions-tools</link>
	<title><![CDATA[Gap filling or Contigs extensions tools !]]></title>
	<description><![CDATA[
<p>There are many tools to perform gap filling using Illumina short reads, for example "GapFiller: a de novo assembly approach to fill the gap within paired reads" or "Toward almost closed genomes with GapFiller". There are also some tools like GAPresolution that can help to perform local re-assemblies using 454 reads. We used GAPresolution but it is not a very good software, it is useful only in some specific situations.</p>

<p>Take a look at the PRICE software from the DeRisi lab. Its meant to do something very similar. http://derisilab.ucsf.edu/index.php?page=software</p>

<p>You could also look at SSPACE (http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/sspacev12/), ATLAS tools (http://www.hgsc.bcm.tmc.edu/content/bcm-hgsc-software), and SCARPA (http://compbio.cs.toronto.edu/hapsembler/scarpa.html).</p>

<p>See the PAGIT protocol: http://www.sanger.ac.uk/resources/software/pagit/ </p>

<p>In particular, take a look at the IMAGE tool: http://genomebiology.com/2010/11/4/R41 </p>

<p>Also SOAPdenovo has ha function for scaffolding. Not sure about ABYSS</p>

<p>Here there is a useful explanation of several tools.</p>

<p>https://bioinformaticsonline.com/search?q=scaffolding&amp;entity_type=object&amp;entity_subtype=bookmarks&amp;offset=0&amp;search_type=entities</p>

<p>I could be wrong, but the above answers to your hypothetical scenario appear to miss the point that you aren't interested in assembling the full genome, just the 100 kb part you're interested in. I suggest the following algorithm:</p>

<p>1. Start with the initial assembly C0 of the contigs you have identified as overlapping your region of interest, and the set S of reads those contigs contain. Let C = C0.</p>

<p>2. Repeat:<br />a. Identify paired-end reads (not in C) for which one or both ends align within, or extending, contigs in C.<br />b. Identify unpaired reads that align extending these new paired-end reads.<br />c. Construct a new assembly C' from C and the new reads identified in (a) and (b).<br />d. Trim C' so it does not extend more than 100 kb to either end of C0. Set C = C'.<br />e. Let S' denote the reads that contribute to C'. If S' does not contain any reads not present in S, stop. Otherwise, Set S = S'.</p>

<p>3. If you don't have a complete assembly of the region of interest, generate an STS for each end of each contig, probe a library for clones including these STSes, subclone these clones into a paired-end sequencing vector, and generate paired-end reads for this library; then try steps (1) and (2) again, adding these new sequencing reads to what you had before.</p>

<p>4. If your average sequencing depth for the region of interest exceeds 25 or so without filling all gaps, it is likely that the remaining gaps represent sequences that are not getting cloned in your sequencing vectors. Try different sequencing vectors.</p>
]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16472/internship-nipgr</guid>
  <pubDate>Sat, 13 Sep 2014 16:02:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[INTERNSHIP @ NIPGR]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for six months ‘Training Fellowship' at National Institute of Plant Genome Research (NIPGR).</p>

<p>About National Institute Of Plant Genome Research (NIPGR) http://www.nipgr.res.in/</p>

<p>The National Institute of Plant Genome Research is an autonomous institution supported by the Department of Biotechnology, Government of India. It is committed to make the institute a premier Institution for plant genomic research in the country. It was established to contribute in the achievement of such hopes as a part of national effort for meeting the challenges in the midst of fast pace of international genomic research and grasping of opportunities on long-term basis.</p>

<p>About the Internship:</p>

<p>The selected intern(s) will work in the area of in Bioinformatics under the BTISNET program of DBT in the Distributed Information Sub center (DISC) facility at NIPGR, New Delhi, under the supervision of Dr. Gitanjali Yadav, Scientist, NIPGR.</p>

<p>Who can apply:</p>

<p>Students currently pursuing the final year of Masters Degree (or equivalent) in Bioinformatics/Biotechnology with strong interest in Computational Biology and First class/division throughout academic career may apply.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/16682/java-utilities-for-next-generation-sequencing-by-pierre-lindenbaum</guid>
	<pubDate>Mon, 15 Sep 2014 17:24:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/16682/java-utilities-for-next-generation-sequencing-by-pierre-lindenbaum</link>
	<title><![CDATA[Java utilities for Next Generation Sequencing  by Pierre Lindenbaum]]></title>
	<description><![CDATA[<div>
<div>
<p>Java utilities for Bioinformatics</p>
</div>
<div>
<p><a href="https://github.com/lindenb/jvarkit">https://github.com/lindenb/jvarkit</a></p>
</div>
</div><p>Address of the bookmark: <a href="https://github.com/lindenb/jvarkit" rel="nofollow">https://github.com/lindenb/jvarkit</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42023/encode3-a-collection-of-research-articles-and-related-content-describing-the-encyclopedia-of-dna-elements-its-datasets-and-tools</guid>
	<pubDate>Sat, 08 Aug 2020 08:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42023/encode3-a-collection-of-research-articles-and-related-content-describing-the-encyclopedia-of-dna-elements-its-datasets-and-tools</link>
	<title><![CDATA[ENCODE3: A collection of research articles and related content describing the Encyclopedia of DNA Elements, its datasets and tools.]]></title>
	<description><![CDATA[<p>How cells, tissues and organisms interpret the information encoded in the genome has vital implications for our understanding of development, health and disease. Launched in 2003, the ENCyclopedia Of DNA Elements (ENCODE) project has the aim of mapping the functional elements in the human genome (later expanded to include model organisms).</p><p>During the first phase of ENCODE, published in 2007, microarray-based technologies were used to detect regions associated with transcription factors, certain histone modifications and open chromatin within a pre-specified 1% of the human genome.</p><p>ENCODE&rsquo;s second phase saw a switch to sequencing-based technologies, the addition of new assay types and the analysis of functional elements genome-wide, described in a collection of research articles in 2012.</p><p><span>The&nbsp;</span><a href="https://www.nature.com/articles/s41586-020-2493-4">Encyclopedia paper of ENCODE 3</a><span>, published in&nbsp;</span><em>Nature</em><span>, gives an overview of the various assays that were performed in human and mouse cell lines and tissues and describes a Registry of human and mouse candidate&nbsp;</span><em>cis</em><span>-regulatory elements (cCREs).</span></p><p>More at&nbsp;<a href="https://www.nature.com/immersive/d42859-020-00027-2/index.html">https://www.nature.com/immersive/d42859-020-00027-2/index.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17505/kau-thrissur-biotechbioinformatics-rasrfjrftraineestudentships</guid>
  <pubDate>Fri, 26 Sep 2014 20:07:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[KAU Thrissur Biotech/Bioinformatics RA/SRF/JRF/Trainee/Studentships]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates for the following posts at Bioinformatics Centre (DIC), IT- BT Complex, College of Horticulture, Kerala Agricultural University, Vellanikkara, Thrissur.</p>

<p>1. Research Associate <br />Emoluments*: 14880/- + HRA 	<br />Qualification needed: Ph.D/M.Sc in Bioinformatics or Ph.D/M.Sc in Agriculture or Biotechnology with advanced Diploma in Bioinformatics <br />Desirable: 2 year experience in Bioinformatics.</p>

<p>2 Senior Research Fellow <br />Emoluments*: 10230/- 	<br />Qualification needed: M.Sc/ M.tech in Bioinformatics or M.Sc in Agriculture/ Biotechnology with Diploma in Bioinformatics. <br />Desirable: One year experience in Bioinformatics</p>

<p>3 Junior Research Fellow <br />Emoluments*: 9300/- 	<br />Qualification needed: M.Sc/ M.tech in Bioinformatics or M.Sc in Agriculture/Biotechnology/Plant Sciences with Diploma in Bioinformatics.</p>

<p>4 .Trainee/Studentship Bioinformatics <br />Emoluments*: 5000/- 	<br />Qualification needed: M.Sc in Bioinformatics with good knowledge of Bioinformatics softwares and tools.</p>

<p>5 Trainee/ Studentship Biotechnology <br />Emoluments*: 5000/- 	<br />Qualification needed: M.Sc in Biotechnology, with working knowledge in tissue culture, molecular markers and cloning of genes.</p>

<p>Candidates with the required qualifications and experience may give an application in the prescribed format with attested copies of certificates to prove eligibility on or before 30th November 2014. The applications are to be addressed to The Associate Dean, College of Horticulture and send to "Professor &amp; Coordinator, Bioinformatics Centre (DIC), IT-BT Complex, Kerala Agricultural University, Vellanikkara, Thrissur, Kerala 680 656”. The envelope may be superscribed “Application for the post at Bioinformatics Centre”.</p>

<p>*Emoluments are likely to be revised in 2014-2015</p>

<p>More at http://www.kaubic.in/downloads/Notification_bic.pdf<br />http://www.kaubic.in/downloads/Application%20form.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</guid>
	<pubDate>Mon, 31 Jan 2022 07:18:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</link>
	<title><![CDATA[Short-read assembly using Spades !]]></title>
	<description><![CDATA[<h2 id="short-read-assembly-a-comparison">If we only had Illumina reads, we could also assemble these using the tool Spades.</h2><p>You can try this here, or try it later on your own data.</p><h2 id="get-data">Get data</h2><p>We will use the same Illumina data as we used above:</p><ul>
<li>illumina_R1.fastq.gz: the Illumina forward reads</li>
<li>illumina_R2.fastq.gz: the Illumina reverse reads</li>
</ul><h2 id="assemble">Assemble</h2><p>Run Spades:</p><div><pre>spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina
</pre></div><ul>
<li><code>-1</code>&nbsp;is input file of forward reads</li>
<li><code>-2</code>&nbsp;is input file of reverse reads</li>
<li><code>--careful</code>&nbsp;minimizes mismatches and short indels</li>
<li><code>--cov-cutoff auto</code>&nbsp;computes the coverage threshold (rather than the default setting, &ldquo;off&rdquo;)</li>
<li><code>-o</code>&nbsp;is the output directory</li>
</ul><h2 id="results">Results</h2><p>Move into the output directory and look at the contigs:</p><div><pre>infoseq contigs.fasta</pre></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17894/faculty-position-at-national-institute-of-technology-rourkela</guid>
  <pubDate>Sun, 05 Oct 2014 15:45:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[FACULTY POSITION at NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA]]></title>
  <description><![CDATA[
<p>NIT, Rourkela, an institute of national importance under Ministry of HRD, Govt. of India invites applications from Indian nationals possessing excellent academic background along with commitment to quality teaching and research for faculty positions at the level of Professor, Associate Professor and Assistant Professor in most branches of Engineering, Science, Management and Humanities as per following table:-</p>

<p>    1 Asst. Professor (on Pre-Ph.D. Contract)</p>

<p>    2 Asst. Professor (on Contract)</p>

<p>    3 Asst. Professor</p>

<p>    4 Associate Professor</p>

<p>    5 Professor</p>

<p>Life Sciences:-</p>

<p>    i)Biochemistry and Molecular Biology; ii)Cell and Developmental Biology; iii)Immunology and Molecular Medicine; (iv) Microbiology and Ecology (v)Bioinformatics Group; vi)Biophysical Sciences</p>

<p>HOW TO APPLY:-</p>

<p>a. Candidates willing to apply for one or more posts are requested to apply online at “http://www.nitrkl.ac.in/ JOBS &amp; TENDERS /Faculty Position” .<br />b. Persons employed in Government and Semi-Government organizations may apply directly against the standing advertisement. For this the application should be completed online. The printout of the application generated online should be submitted through employer if shortlisted for interview.<br />c. The online application can be filled in multiple sessions.<br />d. Candidates are required to check the Institute website from time to time for latest information, application status call for interview, change of dates and final results.<br />e. Applications shall be received online only. Please do not send application or CV against this advertisement by email or letter mail.</p>

<p>More Info: http://nitrkl.ac.in/Jobs_Tenders/1FacultyPosition/Default.aspx</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44551/bioinformatic-tools-for-pathogens-informatics-at-cvr</guid>
	<pubDate>Sat, 08 Jun 2024 15:59:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44551/bioinformatic-tools-for-pathogens-informatics-at-cvr</link>
	<title><![CDATA[Bioinformatic tools for pathogens informatics at CVR]]></title>
	<description><![CDATA[<div><div><div><div><div><p>Novel sequencing and analytical approaches focused on studying viruses and virus-host interactions. Below you will find summaries and links to a number of bioinformatic tools that have been developed @ CVR.</p></div><div><h3><a href="http://giffordlabcvr.github.io/DIGS-tool/" target="_blank" title="DIGS">DIGS</a></h3></div><div><p>The database-integrated genome-screening (DIGS) tool provides a framework for implementing automated in silico screening of sequence databases using BLAST in combination with a relational database (MySQL).</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/discvr/" target="" title="DisCVR">DisCVR</a></h3></div><div><p>DisCVR is a Diagnostic tool for detecting known human viruses in clinical samples from Next-Generation Sequencing (NGS) data. The tool uses a simple and straightforward Graphical User Interface and is optimized on Windows OS without compromising speed and accuracy.</p></div><div><h3><a href="http://josephhughes.github.io/DiversiTools/" target="_blank" title="DiversiTools">DiversiTools</a></h3></div><div><p>DiversiTools is a computational tool that is specifically tailored towards viral HTS data sets and the analysis of the underlying viral populations that they represent. It was initially developed in collaboration with a number of virologists interested in characterising the intra-host diversity of viral populations and studying their evolution across transmission chains at the micro-evolutionary scale.</p></div><div><h3><a href="http://glue-tools.cvr.gla.ac.uk/" target="_blank" title="GLUE">GLUE</a></h3></div><div><p>GLUE is a flexible data-centric bioinformatics environment for virus sequence data, with a focus on virus evolution and genomic variation. GLUE has been applied to a range of viruses. A GLUE-based resource focused on Hepatitis C virus is HCV-GLUE.</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/tanoti/" target="_blank" title="Tanoti">Tanoti</a></h3></div><div><p>Tanoti is a BLAST guided reference based short read aligner. It is developed for maximising alignment in highly variable next generation sequence data sets (Illumina).</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/victree/" target="_blank" title="VicTREE">ViCTree</a></h3></div><div><p>ViCTree is a bioinformatic framework that automatically selects new candidate virus sequences from GenBank, generates multiple sequence alignments, calculates a maximum likelihood phylogeny and integrates the sequences into the existing phylogenetic trees.&nbsp;<span>For more information click&nbsp;</span><a href="https://bioinformatics.cvr.ac.uk/victree_web/" target="_blank">here</a>.</p></div></div></div></div></div><div><div><div><div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/viral-host-predictor/" target="" title="Viral Host Predictor">Viral Host Predictor</a></h3></div><div><p>Viral Host Predictor provides a fast and simple way to predict the hosts and vectors of RNA viruses from viral sequences.</p></div><div><h3><a href="https://github.com/salvocamiolo/GRACy/releases/tag/v0.4.4" target="_blank" title="GRACy">GRACy</a></h3></div><div><p>GRACy is a bioinformatic tool designed for the analysis of Illumina data originated from Human cytomegalovirus samples. GRACy can be used to perform read quality filtering, genotyping, de novo assembly, variant detection, annotation and data submission to public database.</p></div><div><h3><a href="https://github.com/salvocamiolo/LoReTTA/releases/tag/v0.1" target="_blank" title="LoReTTA">LoReTTA</a></h3></div><div><p>LoReTTA (Long Read Template Targeted Assembler) is a reference assisted de novo assembler specifically designed to deal with PacBio reads generated from viral genomes.&nbsp;</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/bingleseq/" target="" title="BingleSeq">BingleSeq</a></h3></div><div><p>BingleSeq is a R-package enables the user-friendly analysis of count tables obtained by both Bulk RNA-Seq and single-cell RNA-Seq protocols. The development of BingleSeq focused on providing a flexible and intuitive user experience.</p></div></div></div></div></div>]]></description>
	<dc:creator>Abhi</dc:creator>
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