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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29284?offset=560</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</guid>
	<pubDate>Fri, 03 Mar 2017 05:15:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</link>
	<title><![CDATA[MetaPred2CS]]></title>
	<description><![CDATA[<p style="text-align: justify;"><strong>MetaPred2CS Web server&nbsp;</strong>is a meta-predictor based on&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17160063">Support Vector Machine (SVM)</a>&nbsp;that combines 6 individual sequence based protein-protein interaction prediction methods to predict&nbsp;<strong>prokaryotic two-component system&nbsp;</strong>protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11933068">in-silico two hybrid (i2h)</a>&nbsp;and&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11707606">mirror tree (MT)</a>&nbsp;methods and 4 genomics context based methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/15947018">phylogenetic profiling (PP)</a>,&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/10573422">gene fusion (GF)</a>,&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene neighbourhood (GN)</a>&nbsp;and and&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene operon methods (GO)</a>.</p>
<p>&nbsp;http://metapred2cs.ibers.aber.ac.uk/</p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/MetaPred2CS" rel="nofollow">https://github.com/martinjvickers/MetaPred2CS</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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	<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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24666/bioinformatics-faculty-at-bharathidasan-university</guid>
  <pubDate>Sat, 26 Sep 2015 20:34:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Faculty at BHARATHIDASAN UNIVERSITY]]></title>
  <description><![CDATA[
<p>BHARATHIDASAN UNIVERSITY</p>

<p>(Reaccredited by NAAC with ‘A’ grade)</p>

<p>TIRUCHIRAPPALLI - 620 024</p>

<p>I N V I T E S</p>

<p>APPLICATIONS FOR FACULTY POSITIONS UNDER UGC XII PLAN CREATED POSTS ON CONTRACTUAL BASIS TILL 31.03.2017 IN THE FOLLOWING UNIVERSITY DEPARTMENTS. (Notification No. 31300 /H2/2015, Dt.: 18.09.2015)</p>

<p>ASSISTANT PROFESSOR</p>

<p>1. Bio-Informatics ONE (MBC)</p>

<p>2. Bio-Chemistry ONE G.T.(W)DW</p>

<p>Consolidated Pay of Rs.45,000/- p.m.</p>

<p>Qualification : As per UGC/AICTE/NCTE norms</p>

<p>Application along with other details including specialization can be downloaded from the University website www.bdu.ac.in</p>

<p>LAST DATE FOR RECEIPT OF FILLED IN APPLICATION IS 07.10.2015 BY 5.00 P.M.</p>

<p>More Info : www.bdu.ac.in/adv/UGC_XII_Plan_Contract_Positions.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43227/project-associate-i-project-associate-ii-senior-project-associate-igib</guid>
  <pubDate>Thu, 05 Aug 2021 16:11:32 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Associate-I | Project Associate-II | Senior Project Associate @ IGIB]]></title>
  <description><![CDATA[
<p>Experience in Next Generation Sequencing (NGS) application and interest in Genomics/ Clinical / Translational Applications. OR Good computational programming skills and deep interest in working on interface of Genomics and Clinical application. </p>

<p>Project Scientist-I <br />Experimental / Computation analysis experience in highthroughput genomics/ clinical application.</p>

<p>Project Manager <br />Experience in handling large biological projects involving high-throughput genomics/ clinical application.</p>

<p>Scientific Administrative Assistant <br />Lab Work. </p>

<p>More at https://vinodscaria.genomes.in/positionsopen</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27253/ra-bioinformatics-at-jnu-delhi</guid>
  <pubDate>Tue, 10 May 2016 01:50:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[R.A Bioinformatics at JNU, Delhi]]></title>
  <description><![CDATA[
<p>R.A Jobs opportunity in Jawaharlal Nehru University (JNU) on purely temporary basis</p>

<p>Project Title : "Structural and functional characterization of serine biosynthetic pathway enzymes from Entamoeba histolytica"</p>

<p>No. of Post : 01</p>

<p>Qualification : Ph.D in any computational biology / bioinformatics</p>

<p>Desirable : 1. Experience with docking, simulations and structural biology with proof of publications is preferred. 2. National Eligibility Test cleared [CSIR/UGC] candidate is preferred.</p>

<p>Salary : According to CSIR rules<br />How to apply</p>

<p>The application on plain paper indicating name, date of birth/age, address, essential/technical/professional qualifications. experience, list of publications should reach The Prof. S. Gourinath, Principal Investigator, [Project Director], School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, on or before 23rd May 2016.</p>

<p>More at http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44758/the-ifs-and-buts-of-ngs-quality-control-and-trimming</guid>
	<pubDate>Thu, 02 Jan 2025 20:11:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44758/the-ifs-and-buts-of-ngs-quality-control-and-trimming</link>
	<title><![CDATA[The &quot;Ifs&quot; and &quot;Buts&quot; of NGS Quality Control and Trimming]]></title>
	<description><![CDATA[<p>Next-Generation Sequencing (NGS) has revolutionized biological research, providing vast amounts of data for a wide range of applications. However, the reliability of NGS analyses heavily depends on the quality of raw sequencing data. Quality control (QC) and trimming are critical preprocessing steps that can make or break your downstream analyses. In this blog, we explore the "ifs" (why you should perform QC and trimming) and the "buts" (challenges or considerations) of this vital step in NGS workflows.</p><h3><strong>The "Ifs" of NGS QC and Trimming</strong></h3><ol>
<li>
<p><strong>Ensures Data Integrity</strong><br />If you want to minimize errors in downstream analyses, QC and trimming remove low-quality reads and bases, ensuring high-confidence data. This step is essential for reliable variant calling, assembly, and other applications.</p>
</li>
<li>
<p><strong>Removes Contaminants</strong><br />If adapter sequences or contaminants are present in the raw reads, trimming can eliminate them. This prevents issues like misalignment or incorrect biological interpretations, ensuring cleaner data for analysis.</p>
</li>
<li>
<p><strong>Improves Mapping and Assembly</strong><br />If your goal is better alignment to a reference genome or improved de novo assembly, trimming low-quality bases and adapters is critical. High-quality reads map more efficiently and generate more accurate assemblies.</p>
</li>
<li>
<p><strong>Reduces Computational Load</strong><br />If you want to save computational resources, trimming reduces the dataset size, which speeds up processing and analysis. Clean datasets mean less computational time spent on processing low-quality data.</p>
</li>
<li>
<p><strong>Prepares for Standardized Analyses</strong><br />If your project involves multiple datasets, QC and trimming ensure uniformity across them. This standardization makes comparisons valid and reproducible, particularly in large collaborative studies.</p>
</li>
</ol><h3><strong>The "Buts" of NGS QC and Trimming</strong></h3><ol>
<li>
<p><strong>Risk of Over-Trimming</strong><br />But excessive trimming can lead to the loss of informative sequences, reducing read depth and potentially discarding biologically relevant data. This is especially critical in studies with limited sequencing depth.</p>
</li>
<li>
<p><strong>Bias Introduction</strong><br />But trimming algorithms might introduce biases, especially if they inadvertently remove sequences with specific biological patterns. This can skew results and compromise biological insights.</p>
</li>
<li>
<p><strong>Loss of Context in Paired-End Reads</strong><br />But trimming one read in a pair more than the other can lead to loss of pairing information. This complicates downstream analyses that rely on paired-end data, such as structural variant detection.</p>
</li>
<li>
<p><strong>Time and Resource Intensive</strong><br />But running QC and trimming for large datasets can be computationally expensive and time-consuming. As sequencing depth increases, preprocessing becomes a bottleneck in the analysis pipeline.</p>
</li>
<li>
<p><strong>Variable Standards</strong><br />But the criteria for trimming (e.g., quality threshold, minimum read length) can vary between tools and datasets. This variability may affect reproducibility and comparability of results across studies.</p>
</li>
</ol><h3><strong>Balancing the "Ifs" and "Buts"</strong></h3><p>To maximize the benefits of QC and trimming while mitigating the challenges, consider the following best practices:</p><ul>
<li>
<p><strong>Use QC Tools Wisely:</strong> Start with tools like <strong>FastQC</strong> to identify quality issues in your raw data. Visualizing quality metrics helps tailor your trimming parameters.</p>
</li>
<li>
<p><strong>Choose Reliable Trimming Tools:</strong> Tools like <strong>Trimmomatic</strong>, <strong>Cutadapt</strong>, and <strong>BBduk</strong> offer adaptive and customizable trimming options. Select one that aligns with your dataset and project goals.</p>
</li>
<li>
<p><strong>Set Reasonable Parameters:</strong> Avoid over-trimming by setting quality thresholds and minimum read lengths that balance data retention and quality improvement.</p>
</li>
<li>
<p><strong>Test Downstream Effects:</strong> Validate the impact of QC and trimming on downstream analyses, such as alignment efficiency, variant calling accuracy, or assembly quality.</p>
</li>
<li>
<p><strong>Document Your Workflow:</strong> Maintain detailed records of the parameters and tools used for QC and trimming. This ensures reproducibility and enables better troubleshooting.</p>
</li>
</ul><h3><strong>Conclusion</strong></h3><p>NGS quality control and trimming are essential steps to ensure reliable and accurate data for analysis. While the "ifs" highlight the clear benefits of these steps, the "buts" remind us of the potential pitfalls. By adopting best practices and carefully balancing these considerations, you can optimize your preprocessing workflow and unlock the full potential of your sequencing data.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25306/research-trainees-recruitment-in-national-agri-food-biotechnology-institute-nabi</guid>
  <pubDate>Sun, 29 Nov 2015 02:47:28 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Trainees recruitment in National Agri-Food Biotechnology Institute (NABI)]]></title>
  <description><![CDATA[
<p>Research Trainees recruitment in National Agri-Food Biotechnology Institute (NABI)</p>

<p>Eligibility : Pursuing final year of M.Sc./M.Tech.</p>

<p>Subject category for training : I. Agricultural biotechnology II. Computational biology and bioinformatics III. Food Science &amp; Technology IV. Nutrition Science &amp; Technology</p>

<p>Duration of Training : 6 months (January to June 2016)</p>

<p>Selection Procedure : Through screening and selection based on merit, experience, and expression of interest submitted by candidates <br />How to apply</p>

<p>The last date of application to reach NABI latest by November 30, 2015 by 5:30 PM </p>

<p>More at http://www.nabi.res.in/Training.aspx</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25251/m-d-university-rohtak-is-looking-for-the-post-of-research-associate</guid>
  <pubDate>Fri, 13 Nov 2015 02:56:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[M. D. University, Rohtak is looking for the post of Research Associate]]></title>
  <description><![CDATA[
<p>M. D. University, Rohtak - Rohtak, Haryana<br />M. D. University, Rohtak is looking vacancies for the post of Research Associate</p>

<p>Project entitled: "Establish of Bioinformatics Facility for biology teaching through bioinformatics"</p>

<p>Name of post: Research Associate /Trainees</p>

<p>Number of post: 03</p>

<p>Educational Qualification and Experience: Candidates should have Ph D in relevant subjects with experience in handling computational biology resources and software</p>

<p>Selection mode: Walk in interview</p>

<p>How to apply?<br />Interested and eligible candidates may appear for a walk-in interview on 14th November 2015 at 11.00 am, in the office of Director, Centre for Bioinformatics along with CV and attested copies of all testimonials and additional qualifications.</p>

<p>Recruitment reference: http://www.mdurohtak.ac.in/pdf/career/adv_research_asso_dbt_bioinfo.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39213/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Tue, 02 Apr 2019 21:54:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39213/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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