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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22807?offset=1650</link>
	<atom:link href="https://bioinformaticsonline.com/related/22807?offset=1650" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41033/clark-fast-accurate-and-versatile-sequence-classification-system</guid>
	<pubDate>Sat, 15 Feb 2020 01:49:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41033/clark-fast-accurate-and-versatile-sequence-classification-system</link>
	<title><![CDATA[CLARK: Fast, accurate and versatile sequence classification system]]></title>
	<description><![CDATA[<p><span></span><a href="http://dx.doi.org/10.1186/s12864-015-1419-2"><strong>CLARK</strong></a><span>, a method based on a supervised sequence classification using discriminative&nbsp;</span><em>k</em><span>-mers. Considering two distinct specific classification problems (see the article for details), namely (1) the taxonomic classification of metagenomic reads to known bacterial genomes, and (2) the assignment of BAC clones and transcript to chromosome arms/centromeres (in the absence of a finished assembly for the reference genome), CLARK outperforms in classification speed and precision the best state-of-the-art methods.</span></p>
<p><span><a href="http://clark.cs.ucr.edu/Spaced/">http://clark.cs.ucr.edu/Spaced/</a></span></p><p>Address of the bookmark: <a href="http://clark.cs.ucr.edu/Spaced/" rel="nofollow">http://clark.cs.ucr.edu/Spaced/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</guid>
	<pubDate>Thu, 09 Jul 2020 03:13:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</link>
	<title><![CDATA[RNA-Bloom: a fast and memory-efficient de novo transcript sequence assembler]]></title>
	<description><![CDATA[<p><strong>RNA-Bloom</strong><span>&nbsp;</span>is a fast and memory-efficient<span>&nbsp;</span><em>de novo</em><span>&nbsp;</span>transcript sequence assembler. It is designed for the following sequencing data types:</p>
<ul>
<li>single-end/paired-end bulk RNA-seq (strand-specific/agnostic)</li>
<li>paired-end single-cell RNA-seq (strand-specific/agnostic)</li>
<li>nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)</li>
</ul>
<p>Written by<span>&nbsp;</span><a>Ka Ming Nip</a><span>&nbsp;</span>✉️</p><p>Address of the bookmark: <a href="https://github.com/bcgsc/RNA-Bloom" rel="nofollow">https://github.com/bcgsc/RNA-Bloom</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</guid>
	<pubDate>Wed, 18 Aug 2021 00:02:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</link>
	<title><![CDATA[Kmer: a suite of tools for DNA sequence analysis]]></title>
	<description><![CDATA[<p>More at&nbsp;https://help.rc.ufl.edu/doc/Kmer</p>
<p>This also includes:</p>
<ul>
<li>A2Amapper: ATAC, Assembly to Assembly Comparision tool:
<ul>
<li>Comparative mapping between two genome assemblies (same species), or between two different genomes (cross species).</li>
</ul>
</li>
</ul>
<ul>
<li>Sim4db:
<ul>
<li>Spliced alignment of cDNA and genomic sequences, from the same (sim4) or related (sim4cc) species. Optimized for high-throughput batched alignment.</li>
</ul>
</li>
</ul>
<ul>
<li>LEAFF:
<ul>
<li>LEAFF (ahem, Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.</li>
</ul>
</li>
</ul>
<ul>
<li>Meryl:
<ul>
<li>An out-of-core k-mer counter. The amount of sequence that can be processed for any size k depends only on the amount of free disk space.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://help.rc.ufl.edu/doc/Kmer" rel="nofollow">https://help.rc.ufl.edu/doc/Kmer</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24178/essentials-of-statistics-and-data-analysis-using-r</guid>
  <pubDate>Mon, 31 Aug 2015 01:32:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Essentials of Statistics and Data Analysis using R]]></title>
  <description><![CDATA[
<p>Clinical Development Services Agency (CDSA) is an extramural unit of Translational Health Science and Technology Institute (THSTI), Department of Biotechnology, Ministry of Science &amp; Technology, Government of India. CDSA has a national mandate of strengthening capacity and capability building in the area of Clinical development and Translational Research.</p>

<p>CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&amp;A sessions are added advantages of this workshop.</p>

<p>Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.</p>

<p>Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</guid>
	<pubDate>Thu, 04 Apr 2024 01:44:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</link>
	<title><![CDATA[A web-based tool for sequence alignment statistics and innovative visualization]]></title>
	<description><![CDATA[<p>AlignStatPlot, a new R package and online tool that is well-documented and easy-to usefor MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analy-ses on sequencing data and generates new visualisation methods for MSA results. Whencompared to currently available tools, AlignStatPlot provides a robust ability to handle andvisualise diversity data, while the online version will save time and encourage researchersto focus on explaining their findings. It is a simple tool that can be used in conjunction withpopulation genetics software (PDF) AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data.</p><p>Address of the bookmark: <a href="https://bioinformatics.um6p.ma/AlignStatPlot/" rel="nofollow">https://bioinformatics.um6p.ma/AlignStatPlot/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24298/staff-scientists-at-national-institute-of-plant-genome-research-new-delhi</guid>
  <pubDate>Fri, 04 Sep 2015 22:06:59 -0500</pubDate>
  <link></link>
  <title><![CDATA[Staff Scientists at National Institute of Plant Genome Research, New Delhi]]></title>
  <description><![CDATA[
<p>National Institute of Plant Genome Research, New Delhi is an Autonomous Research Institution funded by Department of Biotechnology, Ministry of Science &amp; Technology, Govt. of India, to pursue research on various aspects of plant genomics. The Institute is also in the process of establishing a NIPGR Translational Centre at Biotech Science Cluster, NCR, Faridabad. NIPGR invites applications from Indian Citizens for filling up the vacant posts on Direct Recruitment basis, as detailed below. The posts are temporary but likely to continue.</p>

<p>Staff Scientists</p>

<p>Specialization: Applicant should have a Ph.D. with excellent academic credentials along with the track record of scientific productivity evidenced by publications/patents/products in the frontier areas of Plant Biology such as, Computational Biology, Genome Analysis and Molecular Mapping, Molecular Mechanism of Abiotic Stress Responses, Nutritional Genomics, Plant Development and Architecture, Plant Immunity, Molecular Breeding, Transgenics for crop improvement and other emerging areas based on plant genomics.</p>

<p>Remuneration: The length of experience and scientific accomplishments/quality of scientific productivity record will be major factors in deciding the level of appointment as Staff Scientist as well as starting salary in the Pay Bands of Rs 15,600-39,100 (with grade pay of  5400), and Rs 37,400-67,000 (with grade pay of  8,700 and  8,900) plus usual allowances admissible to the Central Government employees. However, NIPGR reserves the right to select candidates in the lower grade against the foregoing posts depending upon the qualifications and experience of the candidate. Reservation of posts shall be as per Govt. of India norms. Five posts (SC-2, ST-1, OBC-2) in the Pay Band of Rs 15,600-39,100 with Grade Pay of  Rs 5400, are reserved.</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>

<p>Apply online at http://www.nipgr.res.in/nipgr_recu/nipgr_recu.php</p>

<p>Form http://www.nipgr.res.in/files/careers/Application_Performa_2015.doc</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44675/variant-calling-pipeline</guid>
	<pubDate>Sat, 19 Oct 2024 12:23:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44675/variant-calling-pipeline</link>
	<title><![CDATA[Variant Calling Pipeline]]></title>
	<description><![CDATA[<p dir="auto">The&nbsp;<a href="https://github.com/Tom-Jenkins/maerl-wgs-pipelines/blob/main/src/variantcalling.nf"><code>variantcalling.nf</code></a>&nbsp;nextflow script will take any number of samples with paired-end reads in FASTQ format, map reads using Bowtie2, process BAM files, and finally call variants using BCFtools v1.21 and/or Freebayes v1.3.6. If part of the pipeline is unsuccessful for a sample then these errors are ignored.</p>
<p dir="auto">Pipeline flowchart:</p>
<div dir="auto">
<div dir="auto">
<div>&nbsp;</div>
<div></div>
</div>
<div>&nbsp;</div>
<div dir="auto">
<h2 dir="auto">Dependencies (version tested)</h2>
<a href="https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md#dependencies-version-tested"></a></div>
<ul dir="auto">
<li>Nextflow (24.04.4)</li>
<li>Java (18.0.2.1)</li>
<li>Python (3.10)</li>
<li>Perl (5.32.1)</li>
<li>Bowtie2 (2.5.3)</li>
<li>SAMtools (1.19.2)</li>
<li>GATK4 (4.5)</li>
<li>BCFtools (1.21)</li>
<li>Freebayes (1.3.6)</li>
</ul>
</div><p>Address of the bookmark: <a href="https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md" rel="nofollow">https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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