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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27261?offset=620</link>
	<atom:link href="https://bioinformaticsonline.com/related/27261?offset=620" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</guid>
	<pubDate>Mon, 20 Aug 2018 04:08:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</link>
	<title><![CDATA[FinisherSC:a repeat-aware tool for upgrading de novo assembly using long reads]]></title>
	<description><![CDATA[<p><br>Here is the command to run the tool:</p>
<pre><code>python finisherSC.py destinedFolder mummerPath
</code></pre>
<p>If you are running on server computer and would like to use multiple threads, then the following commands can generate 20 threads to run FinisherSC.</p>
<pre><code>python finisherSC.py -par 20 destinedFolder mummerPath
</code></pre>
<p>Sometimes, if the names of raw reads and contigs consists of special characters/formats, FinisherSC/MUMmer may not parse them correctly. In that case, you want to have a quick renaming of the names of contigs/reads in contigs.fasta or raw_reads.fasta using the following command.</p>
<pre><code>    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' raw_reads.fasta &gt; newRaw_reads.fasta
    cp newRaw_reads.fasta raw_reads.fasta
    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' contigs.fasta &gt; newContigs.fasta
    cp newContigs.fasta contigs.fasta</code></pre><p>Address of the bookmark: <a href="https://github.com/kakitone/finishingTool" rel="nofollow">https://github.com/kakitone/finishingTool</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19635/walk-in-interview-for-research-associate-studentship-and-traineeship-at-bif-nehu-tura-campus</guid>
  <pubDate>Thu, 18 Dec 2014 11:02:05 -0600</pubDate>
  <link></link>
  <title><![CDATA[Walk in interview for Research Associate, Studentship and Traineeship at BIF, NEHU, Tura Campus]]></title>
  <description><![CDATA[
<p>BIOINFORMATICS INFRASTRUCTURE FACILITY (BIF)<br />Department of RDAP<br />North-Eastern Hil University, Tura Campus<br />Tura-79402, Meghalaya</p>

<p>Walk in interview for Research Associate, Studentship and Traineeship at BIF</p>

<p>Applications are invited for the Post of Research Associate, Traineeship and Studentship in the DBT sponsored Bioinformatics Infrastructure Facility (BIF) at the Bioinformatics Centre, Department of RDAP, North-Eastern Hil University, Tura Campus, Tura-79402, Meghalaya. The Posts are purely temporary and terminable at any time without prior notice or assigning any reason thereof. The person engaged, shall not be entailed for any claim implicit or explicit for permanent absorption in the University.</p>

<p>Research Associate- 01</p>

<p>Essential Qualification: M.Sc. in Bioinformatics/Biotechnology from a recognized University/ institute.</p>

<p>Desirable: PhD or Pursuing PhD in the relevant subject(s) or equivalent published work in reputed peer reviewed journals or Advance PG diploma in Bioinformatics courses.</p>

<p>Duties: Creation of database, web designing, maintenance of internet, training of students in Bioinformatics, handling and knowledge of Bioinformatics software tools and technique, conducting Bioinformatics based research and other day to day laboratory work, writing report and scientific papers.</p>

<p>Pay:Rs. 2,00/- + Admissible 10% HRA per month</p>

<p>Age: Below 35 years</p>

<p>Traineeship- 02</p>

<p>Students who have completed Masters Degree in Bioinformatics/Biotechnology or any branch of Life Sciences/Agricultural Sciences/Computer Science to cary out a project work in Bioinformatics.</p>

<p>Desirable: Prior Knowledge of programming languages such as C, JAVA, MySQL is preferable.</p>

<p>Stipend: Rs. 800/- p.m. fixed. Purely temporary for a period of six months.</p>

<p>Studentship: 02</p>

<p>Students pursuing postgraduate degree in Bioinformatics/biotechnology/Agricultural Sciences or any branch of Life Science</p>

<p>Desirable: Prior knowledge of bioinformatics/ programming language is preferable.</p>

<p>Stipend: 800/- p.m. fixed. Purely temporary for a period of six months.</p>

<p>Candidates must send the detailed Biodata via mail/post and bring al the relevant documents in original and one set of attested photocopies of the same at the time of interview. No TA/DA will be paid for attending the interview and candidates have to make their own arrangements.</p>

<p>Last date for receiving application by mail or by post: 16.02.2014</p>

<p>Contact Information:<br />Dr.B.K. Mishra<br />Cordinator BIF,<br />RDAP Department, NEHU, Tura Campus<br />Phone: 91-03651-23107<br />Fax: 91-03651-23953<br />E-mail: drbkm1972@yaho.co.in, birendramishra14@gmail.com</p>

<p>Advertisement: http://www.nehu.ac.in/Advertisements/BIF_TuraAdtvPV_171214.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19597/assistant-professor-at-gauhati-university-guwahati</guid>
  <pubDate>Tue, 16 Dec 2014 01:15:30 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at GAUHATI UNIVERSITY, GUWAHATI]]></title>
  <description><![CDATA[
<p>Advt. No.T/2014/4</p>

<p>Ref. No. GU/Estt/T/308(VI)/2014/6451-61</p>

<p>Applications are invited from the Indian citizens for five (5) teaching posts of Assistant Professor (Contractual) under various departments of Gauhati University. Details of the advertisement, other terms and conditions and the application forms are available in the University website www.gauhati.ac.in</p>

<p>Asstt. Professor (Contractual)</p>

<p>    2. M.Sc. Microbiology Course in Botany</p>

<p>    3 1.M.Sc. Microbiology/M.Sc. Botany (Specialization in Microbiology)/M.Sc. Biochemistry (1 post). (Preference will be given to candidates having experience in Biochemistry).</p>

<p>    2.M.Sc. Microbiology/M.Sc. Botany (Specialization in Microbiology)/M.Sc. Biotechnology(1 post). (Preference will be given to candidates having experience in Bioinformatics).</p>

<p>    3.M.Sc. Microbiology/M.Sc. Botany (Specialization in Microbiology)/M.Sc.  Biotechnology(1 post). (Preference will be given to candidates having experience in Microbial Genetics).</p>

<p>As per UGC norms</p>

<p>Pay Band &amp; Academic Grade Pay : (Consolidated pay) : Rs. 21,600/- per month</p>

<p>Application Form : Prescribe application form may download from the G.U. website www.gauhati.ac.in</p>

<p>Last date of receipt of filled-in application is 08.01.2015.</p>

<p>Advertisement: www.gauhati.ac.in/openfile.php?file=Notice1258.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37959/rainbow-an-integrated-tool-for-efficient-clustering-and-assembling-rad-seq-reads</guid>
	<pubDate>Fri, 19 Oct 2018 08:23:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37959/rainbow-an-integrated-tool-for-efficient-clustering-and-assembling-rad-seq-reads</link>
	<title><![CDATA[Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads]]></title>
	<description><![CDATA[<p><span>Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top&ndash;down manner. And along a guided tree, it iteratively merges sibling leaves in a bottom&ndash;up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, we show that Rainbow is more competent than the other tools in dealing with RAD-seq data</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/bio-rainbow/files/" rel="nofollow">https://sourceforge.net/projects/bio-rainbow/files/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19695/china-university-of-macau-phd-position-2015-in-bioinformatics-computer-science</guid>
  <pubDate>Mon, 22 Dec 2014 00:12:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[China University of Macau PhD Position 2015 in Bioinformatics, Computer Science]]></title>
  <description><![CDATA[
<p>The Computational Biology and Bioinformatics Group at the University of Macau is inviting applications for PhD Position. Applicants will work on a research project focusing on the flexible receptor protein-ligand docking algorithms for computer-aided drug design.  The candidate will be working as part of a team in developing novel metaheuristic algorithms and scoring functions for large-scale, highly flexible protein-ligand docking problems. The duration of this PhD position is 2-3 years, starting in August 2015. Remuneration paid to candidate is MOP 11000-14000/month (~USD 1375-1750/month). The applications should be submitted before March 2015.</p>

<p>Study Subject(s): PhD position is award in the field of Bioinformatics/Computer Science.<br />Course Level: Position is available for pursuing PhD degree level at the University of Macau.<br />Scholarship Provider: University of Macau<br />Scholarship can be taken at: China</p>

<p>Eligibility: The ideal candidate would be a master degree holder in Bioinformatics or related disciplines with knowledge in Medical sciences or Life sciences (with GPA of at least 3.0 on a 4-point scale or equivalent) . Knowledge in programming (C and C++) and Linux scripting are necessary; experience in molecular docking, molecular dynamics simulations or molecular modeling is an advantage. The candidate should be fluent in spoken and written English; preference will be given to applicants with good publication records in relevant areas.</p>

<p>Scholarship Open for International Students: Researchers from China can apply for this PhD position.</p>

<p>Scholarship Description:</p>

<p>The Computational Biology and Bioinformatics Group at the University of Macau is looking for a motivated PhD student in Bioinformatics or Computer Science to work on a research project focusing on the flexible receptor protein-ligand docking algorithms for computer-aided drug design.  The candidate will be working as part of a team in developing novel metaheuristic algorithms and scoring functions for large-scale, highly flexible protein-ligand docking problems.</p>

<p>Number of award(s): There is only one PhD position available.</p>

<p>Duration of award(s): The duration of this PhD position is 2-3 years.</p>

<p>What does it cover? Remuneration paid to candidate is  MOP 11000-14000/month (~USD 1375-1750/month).</p>

<p>Selection Criteria: Not Known</p>

<p>Notification: Not Known</p>

<p>How to Apply: Send your current CV, your academic transcripts, a letter of motivation and research interests, two letters of recommendations from academic faculty to Dr. Shirley Siu at shirleysiu[at]umac.mo before March 2015.</p>

<p>Scholarship Application Deadline: The applications should be submitted before March 2015.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</guid>
	<pubDate>Sat, 19 Jan 2019 17:29:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</link>
	<title><![CDATA[Genome assembly tutorial &quot;Genome Assembly for short and long reads&quot;]]></title>
	<description><![CDATA[<p>In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will know:</p>
<ol>
<li>How to perform basic quality checks on the input data</li>
<li>How to run a short read assembler on Illumina data</li>
<li>How to run a long read assembler on Pacific Biosciences or Oxford Nanopore data</li>
<li>How to improve the accuracy of a long read assembly using short reads</li>
<li>How to assess the quality of an assembly</li>
</ol>
<p>https://bioinformaticsdotca.github.io/high-throughput_biology_2017</p><p>Address of the bookmark: <a href="https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab" rel="nofollow">https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19811/jnu-neurosciencesystems-biologymathematical-modeling-jrf-vacancies</guid>
  <pubDate>Fri, 26 Dec 2014 11:22:20 -0600</pubDate>
  <link></link>
  <title><![CDATA[JNU Neuroscience/Systems Biology/Mathematical modeling JRF Vacancies]]></title>
  <description><![CDATA[
<p>School of Computational and Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi 110067</p>

<p>Recruitment for Project</p>

<p>Applications were invited from the citizens of India for filling up the following temporary position for the CSIR sponsored Fellowship in the School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067. This position is temporary for a period of two and half years or tenable only for the duration of the project. The requisite qualifications &amp; experience are given below.</p>

<p>Project Title : "Understanding Complex dynamics and Information processing in Brain Networks"<br />Funding Agency : CSIR</p>

<p>Principal Investigator : Dr. R.K. Brojen Singh</p>

<p>Position : Junior Research Fellow(One post)</p>

<p>Salary : As per CSIR rules and guidelines for JRF.</p>

<p>Qualifications &amp; Experience : M.Sc. in Physics/Mathematics/Biology/B.Tech. In Eng. Physics/Comp. Sc. and desirable CSIR-UGC NET Qualified. Candidates should also have at least one years research experience after M. Sc./B.Tech. in works related to Neuroscience/Mathematical modeling.</p>

<p>Candidates possessing requisite qualifications may apply either on plain paper stating the project title along with CV and send to the following address or send as email attachment (pdf or word format) so as to reach on or before 8 January, 2014.</p>

<p>Dr. R.K. Brojen Singh<br />School of Computational and Integrative Sciences<br />Jawharlal Nehru University<br />New Delhi 110067<br />Email: brojen@jnu.ac.in, brojen@mail.jnu.ac.in</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads</guid>
	<pubDate>Sun, 22 Dec 2019 03:48:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads</link>
	<title><![CDATA[SViper: Swipe your Structural Variants called on long (ONT/PacBio) reads with short exact (Illumina) reads.]]></title>
	<description><![CDATA[<p>Call sviper</p>
<pre><code>~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants
</code></pre>
<p>This will output a&nbsp;<code>polished_variants.vcf</code>&nbsp;file, that contains all the refined variants.</p>
<p>Sometimes it is helpful to look at the polished sequence, e.g. with the IGV browser. In that case you want SViper to output the polished and aligned sequences in a bam file via the option&nbsp;<code>--output-polished-bam</code>:</p>
<pre><code>~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants --output-</code>polished-bam</pre><p>Address of the bookmark: <a href="https://github.com/smehringer/SViper" rel="nofollow">https://github.com/smehringer/SViper</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40889/rcorrector-efficient-and-accurate-error-correction-for-illumina-rna-seq-reads</guid>
	<pubDate>Tue, 04 Feb 2020 23:23:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40889/rcorrector-efficient-and-accurate-error-correction-for-illumina-rna-seq-reads</link>
	<title><![CDATA[Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads]]></title>
	<description><![CDATA[<p><span>Rcorrector has an accuracy higher than or comparable to existing methods, including the only other method (SEECER) designed for RNA-seq reads, and is more time and memory efficient. With a 5 GB memory footprint for 100 million reads, it can be run on virtually any desktop or server. The software is available free of charge under the GNU General Public License from&nbsp;</span><a href="https://github.com/mourisl/Rcorrector/" target="_blank">https://github.com/mourisl/Rcorrector/</a><span>.</span></p>
<pre><code>Usage: perl run_rcorrector.pl [OPTIONS]
OPTIONS:
	Required
	-s seq_files: comma separated files for single-end data sets
	-1 seq_files_left: comma separated files for the first mate in the paried-end data sets
	-2 seq_files_right: comma separated files for the second mate in the paired-end data sets
	-i seq_files_interleaved: comma sperated files for interleaved paired-end data sets
	Optional
	-k INT: kmer_length (&lt;=32, default: 23)
	-od STRING: output_file_directory (default: ./)
	-t INT: number of threads to use (default: 1)
	-trim : allow trimming (default: false)
	-maxcorK INT: the maximum number of correction within k-bp window (default: 4)
	-wk FLOAT: the proportion of kmers that are used to estimate weak kmer count threshold, lower for more divergent genome (default: 0.95)
	-ek INT: expected number of kmers; does not affect the correctness of program but affects the memory usage (default: 100000000)
	-stdout: output the corrected reads to stdout (default: not used)
	-verbose: output some correction information to stdout (default: not used)
	-stage INT: start from which stage (default: 0)
		0-start from begining(storing kmers in bloom filter) ;
		1-start from count kmers showed up in bloom filter;
		2-start from dumping kmer counts into a jf_dump file;
		3-start from error correction.</code></pre><p>Address of the bookmark: <a href="https://github.com/mourisl/Rcorrector/" rel="nofollow">https://github.com/mourisl/Rcorrector/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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