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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28807?offset=530</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <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>
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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/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>
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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/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/news/view/20015/illumina-smartphone-chip</guid>
	<pubDate>Tue, 30 Dec 2014 23:19:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20015/illumina-smartphone-chip</link>
	<title><![CDATA[Illumina Smartphone Chip !!!]]></title>
	<description><![CDATA[<p>Illumina, the company that claims it brought human genome sequencing down to $1000 prices, has now turned its attention to a consumer product - a chip that you can plug into your smartphone and have it read your genetic information.<br /><br />The biggest challenge ahead of Illumina is simplifying the process of genetic sequencing. Currently, Illumina&rsquo;s DNA sequencers are gigantic machines that use techinques like colorimetry to work, but while the core technology is computational, it takes some 30 steps to extract genetic data and run it through. This process will likely have to be hugely simplified on mobile devices, given the fact that some studies require extracting 10 mililiters of blood. Illumina researchers are also working on finding the optimal technology for this on-chip DNA sequencing - be it electrical, optical, or other.<br /><br />Illumina is one of the most prominent names in genetics, often said to be the Intel of genetic sequencing, as just like Intel it provides the algorithms, the processing brain that runs a DNA reading task.<br /><br />In other recent smartphone-related biotech news, drug company Pfizer launched its REMOTE project, a new type of clinical trial that does not require going to a hospital for checks - targeted at patients with overactive bladder problems, the FDA-approved REMOTE project allowed to gather data from patients from over 10 states remotely, via mobile devices.<br /><br /></p><p>This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.</p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20449/walk-in-interview-for-the-post-of-jrf-and-project-assistant-cift</guid>
  <pubDate>Tue, 20 Jan 2015 23:03:20 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN-INTERVIEW for the post of JRF and Project Assistant @ CIFT]]></title>
  <description><![CDATA[
<p>Eligible candidates are invited to attend a walk-in-Interview with all relevant documents for the following positions of Project Fellows (on contractual basis) to work in the Project “ Genetic Diversity of Clostridium botulinum in seafood and Development of Lateral Flow Immuno Assay (LFIA) for toxinotyping  funded by Department of Biotechnology.   The duration of the project is 3 years / co-terminus with the scheme.</p>

<p>Jr. Research Fellow – 2 posts</p>

<p>    Fellowship    :   Rs. 25000/- + 20% HRA pm  for Ist &amp; 2nd year and Rs.28000/- + HRA on 3rd year</p>

<p>    Qualification :    Ist class Masters Degree in Microbiology/Fishery Microbiology/Bio-technology.</p>

<p>    Desirable        :  </p>

<p>    1. CSIR/UGC NET/JRF qualified</p>

<p>    2. Excellent analytical skills and computer documentation</p>

<p>    3. Prior experience in handling microbial cultures and molecular techniques</p>

<p>Project Assistant – 1 post</p>

<p>Fellowship    :    Rs.8000/- p.m (consolidated)</p>

<p>Qualification:   Masters degree in Microbiology/Biotechnology with skill in Bioinformatics</p>

<p>Desirable:   Excellent analytical skills in Bioinformatics and computer documentation</p>

<p>Terms &amp; Conditions:</p>

<p>Registration will begin at 8.30 a.m and will close at 11.00 am<br />Age limit (as on 29.1.2015):  Below 35 years for men and 40 years for women.<br />Age relaxation of 3 year for OBC candidates and 5 years for SC/ST candidates is permissible.<br />Candidates are required to submit self-attested copies of all the Certificates in support of their claims    regarding age, educational qualifications, scheduled caste/scheduled tribe/OBC etc.  The original certificates shall be produced for verification before the interview.<br />Candidates should bring detailed bio-data (in the enclosed format)  affixing a recent passport size photograph.<br />The selected candidate will be recruited on contract basis under ICAR norms.  The post is purely temporary and is co-terminus with the project.<br />The candidates attending the interview should ensure that they fulfil all the eligibility conditions.  No correspondence will be entertained from the candidates for selection/test/appointment.<br />No TA/DA will be paid to attend the interview.<br />Canvassing in any form will render the candidate disqualified for the post.<br />The Director’s decision will be final and binding in all aspects regarding the selection to the post.</p>

<p>Venue: CIFT, Matsyapuri.P.O, Cochin                  Date of interview:  29.01.2015          Time:  10.00 am</p>

<p>http://www.cift.res.in/uploads/userfiles/file/file/srf%20appn.doc</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39726/jackalope-a-swift-versatile-phylogenomic-and-high-throughput-sequencing-simulator</guid>
	<pubDate>Fri, 26 Jul 2019 00:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39726/jackalope-a-swift-versatile-phylogenomic-and-high-throughput-sequencing-simulator</link>
	<title><![CDATA[jackalope: A swift, versatile phylogenomic and high-throughput sequencing simulator]]></title>
	<description><![CDATA[<p><code>jackalope</code> simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants can be simulated using summary statistics, phylogenies, Variant Call Format (VCF) files, and coalescent simulations&mdash;the latter of which can include selection, recombination, and demographic fluctuations. <code>jackalope</code> can simulate single, paired-end, or mate-pair Illumina reads, as well as reads from Pacific Biosciences These simulations include sequencing errors, mapping qualities, multiplexing, and optical/PCR duplicates. All outputs can be written to standard file formats.</p>
<p><span>A swift, versatile phylogenomic and high-throughput sequencing simulator </span> <span><a href="https://jackalope.lucasnell.com">https://jackalope.lucasnell.com</a></span></p><p>Address of the bookmark: <a href="https://github.com/lucasnell/jackalope" rel="nofollow">https://github.com/lucasnell/jackalope</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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