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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30111?offset=1320</link>
	<atom:link href="https://bioinformaticsonline.com/related/30111?offset=1320" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33223/tbl2asn-a-command-line-program-that-automates-the-creation-of-sequence-records-for-submission-to-genbank</guid>
	<pubDate>Mon, 29 May 2017 07:37:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33223/tbl2asn-a-command-line-program-that-automates-the-creation-of-sequence-records-for-submission-to-genbank</link>
	<title><![CDATA[Tbl2asn: a command-line program that automates the creation of sequence records for submission to GenBank]]></title>
	<description><![CDATA[<p>Tbl2asn is a command-line program that automates the creation of sequence records for submission to GenBank. It uses many of the same functions as Sequin but is driven generally by data files. Tbl2asn generates .sqn files for submission to GenBank. Additional manual editing is not required before submission.</p>
<p>Tbl2asn is available by anonymous&nbsp;<a href="ftp://ftp.ncbi.nih.gov/toolbox/ncbi_tools/converters/by_program/tbl2asn/">FTP</a>. Copy the right version for your platform, then uncompress the file, rename it to "tbl2asn", and set the permissions, as necessary for the platform.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genbank/tbl2asn2/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genbank/tbl2asn2/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25503/assistant-professor-computational-biology-and-bioinformatics-in-navi-mumbai</guid>
  <pubDate>Fri, 04 Dec 2015 20:40:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Computational Biology and Bioinformatics in Navi Mumbai]]></title>
  <description><![CDATA[
<p>No. ACTREC / ADVT-A/2/2015 <br />Pay in Pay band and Grade Pay : PB-3 (Rs 15,600-39,100) Pay in pay band Rs 21,900+ G.P. of Rs 7,600 <br />Total emoluments = 82,000/- p.m. &amp; nbsp <br />Educational Qualification : Ph.D. or MD/Ph.D. <br />Experience : Post MD / Ph.D. Research experience of 5 years The last date of application submission is January 15th, 2016. <br />Interested candidates shall send the applications through email: office.sao(at)actrec.gov.in. <br />For More Details : www.actrec.gov.in/data%20files/Vacancies/2015/Faculty-Positions-SOE-24-11-15.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34221/alignment-free-sequence-comparison-tools-available-for-next-generation-sequencing-data-analysis</guid>
	<pubDate>Tue, 07 Nov 2017 05:33:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34221/alignment-free-sequence-comparison-tools-available-for-next-generation-sequencing-data-analysis</link>
	<title><![CDATA[Alignment-free sequence comparison tools available for next-generation sequencing data analysis]]></title>
	<description><![CDATA[<div><p><span>kallisto</span></p></div><div><p>Transcript abundance quantification from RNA-seq data (uses pseudoalignment for rapid determination of read compatibility with targets)</p><p>Software (C++)</p><p><a href="https://pachterlab.github.io/kallisto/">https://pachterlab.github.io/kallisto/</a></p><p>Sailfish</p><p>Estimation of isoform abundances from reference sequences and RNA-seq data (<em>k</em>-mer based)</p><p>Software (C++)</p><p><a href="http://www.cs.cmu.edu/~ckingsf/software/sailfish/">http://www.cs.cmu.edu/~ckingsf/software/sailfish/</a></p><p>Salmon</p><p>Quantification of the expression of transcripts using RNA-seq data (uses&nbsp;<em>k</em>-mers)</p><p><a href="https://combine-lab.github.io/salmon/">https://combine-lab.github.io/salmon/</a></p><p>RNA-Skim</p><p>RNA-seq quantification at transcript-level (partitions the transcriptome into disjoint transcript clusters; uses&nbsp;<em>sig</em>-mers, a special type of&nbsp;<em>k</em>-mers)</p><p>Software (C++)</p><p><a href="http://www.csbio.unc.edu/rs/">http://www.csbio.unc.edu/rs/</a></p><p>Variant calling</p><p>ChimeRScope</p><p>Fusion transcript prediction using gene&nbsp;<em>k</em>-mers profiles of the RNA-seq paired-end reads</p><p>Software (Java)</p><p><a href="https://github.com/ChimeRScope/ChimeRScope/wiki">https://github.com/ChimeRScope/ChimeRScope/wiki</a></p><p>FastGT</p><p>Genotyping of known SNV/SNP variants directly from raw NGS sequence reads by counting unique&nbsp;<em>k</em>-mers</p><p>Software (C)</p><p><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></p><p>Phy-Mer</p><p>Reference-independent mitochondrial haplogroup classifier from NGS data (<em>k</em>-mer based)</p><p>Software (Python)</p><p><a href="https://github.com/danielnavarrogomez/phy-mer">https://github.com/danielnavarrogomez/phy-mer</a></p><p>LAVA</p><p>Genotyping of known SNPs (dbSNP and Affymetrix's Genome-Wide Human SNP Array) from raw NGS reads (<em>k</em>-mer based)</p><p>Software (C)</p><p><a href="http://lava.csail.mit.edu/">http://lava.csail.mit.edu/</a></p><p>MICADo</p><p>Detection of mutations in targeted third-generation NGS data (can distinguish patients&rsquo; specific mutations; algorithm uses&nbsp;<em>k</em>-mers and is based on colored de Bruijn graphs)</p><p>Software (Python)</p><p><a href="http://github.com/cbib/MICADo">http://github.com/cbib/MICADo</a></p><p>General mapper</p><p>Minimap</p><p>Lightweight and fast read mapper and read overlap detector (uses the concept of &ldquo;minimazers&rdquo;, a special type of&nbsp;<em>k</em>-mers)</p><p>Software (C)</p><p><a href="https://github.com/lh3/minimap">https://github.com/lh3/minimap</a></p><p>Assembly</p><p>De novo genome assembly</p><p>MHAP</p><p>Produces highly continuous assembly (fully resolved chromosome arms) from third-generation long and noisy reads (10 kbp) using a dimensionality reduction technique MinHash</p><p>Software (Java)</p><p><a href="https://github.com/marbl/MHAP">https://github.com/marbl/MHAP</a></p><p>Miniasm</p><p>Assembler of long noisy reads (SMRT, ONT) using the Overlap-Layout Consensus (OLC) approach without the necessity of an error correction stage (uses minimap)</p><p>Software (C)</p><p><a href="https://github.com/lh3/miniasm">https://github.com/lh3/miniasm</a></p><p>LINKS</p><p>Scaffolding genome assembly with error-containing long sequence (e.g., ONT or PacBio reads, draft genomes)</p><p>Software (Perl)</p><p><a href="https://github.com/warrenlr/LINKS/">https://github.com/warrenlr/LINKS/</a></p><p>Read clustering</p><p>afcluster</p><p>Clustering of reads from different genes and different species based on&nbsp;<em>k</em>-mer counts</p><p>Software (C++)</p><p><a href="https://github.com/luscinius/afcluster">https://github.com/luscinius/afcluster</a></p><p>QCluster</p><p>Clustering of reads with alignment-free measures (<em>k</em>-mer based) and quality values</p><p>Software (C++)</p><p><a href="http://www.dei.unipd.it/~ciompin/main/qcluster.html">http://www.dei.unipd.it/~ciompin/main/qcluster.html</a></p><p>Reads error correction</p><p>Lighter</p><p>Correction of sequencing errors in raw, whole genome sequencing reads (<em>k</em>-mer based)</p><p>Software (C++)</p><p><a href="https://github.com/mourisl/Lighter">https://github.com/mourisl/Lighter</a></p><p>QuorUM</p><p>Error corrector for Illumina reads using k-mers</p><p>Software (C++)</p><p><a href="https://github.com/gmarcais/Quorum">https://github.com/gmarcais/Quorum</a></p><p>Trowel</p><p>Software (C++)</p><p><a href="https://sourceforge.net/projects/trowel-ec/">https://sourceforge.net/projects/trowel-ec/</a></p><p>Metagenomics</p><p>Assembly-free phylogenomics</p><p>AAF</p><p>Phylogeny reconstruction directly from unassembled raw sequence data from whole genome sequencing projects; provides bootstrap support to assess uncertainty in the tree topology (<em>k</em>-mer based)</p><p>Software (Python)</p><p><a href="https://github.com/fanhuan/AAF">https://github.com/fanhuan/AAF</a></p><p>kSNP v3</p><p>Reference-free SNP identification and estimation of phylogenetic trees using SNPs (based on&nbsp;<em>k</em>-mer analysis)</p><p>Software (C)</p><p><a href="https://sourceforge.net/projects/ksnp/files/">https://sourceforge.net/projects/ksnp/files/</a></p><p>NGS-MC</p><p>Phylogeny of species based on NGS reads using alignment-free sequence dissimilarity measures d2* and d2&nbsp;S&nbsp;under different Markov chain models (using&nbsp;<em>k</em>-words)</p><p>R package</p><p><a href="http://www-rcf.usc.edu/~fsun/Programs/NGS-MC/NGS-MC.html">http://www-rcf.usc.edu/~fsun/Programs/NGS-MC/NGS-MC.html</a></p><p>Species identification/taxonomic profiling</p><p>CLARK</p><p>Taxonomic classification of metagenomic reads to known bacterial genomes using&nbsp;<em>k</em>-mer search and LCA assignment</p><p>Software (C++)</p><p><a href="http://clark.cs.ucr.edu/">http://clark.cs.ucr.edu/</a></p><p>FOCUS</p><p>Reports organisms present in metagenomic samples and profiles their abundances (uses composition-based approach and non-negative least squares for prediction)</p><p>Web service Software (Python)</p><p><a href="http://edwards.sdsu.edu/FOCUS/">http://edwards.sdsu.edu/FOCUS/</a></p><p>GSM</p><p>Estimation of abundances of microbial genomes in metagenomic samples (<em>k</em>-mer based)</p><p>Software (Go)</p><p><a href="https://github.com/pdtrang/GSM">https://github.com/pdtrang/GSM</a></p><p>Mash</p><p>Species identification using assembled or unassembled Illumina, PacBio, and ONT data (based on MinHash dimensionality-reduction technique)</p><p>Software (C++)</p><p><a href="https://github.com/marbl/mash">https://github.com/marbl/mash</a></p><p>Kraken</p><p>Taxonomic assignment in metagenome analysis by exact&nbsp;<em>k</em>-mer search; LCA assignment of short reads based on a comprehensive sequence database</p><p>Software (C++)</p><p><a href="https://ccb.jhu.edu/software/kraken/">https://ccb.jhu.edu/software/kraken/</a></p><p>LMAT</p><p>Assignment of taxonomic labels to reads by&nbsp;<em>k</em>-mers searches in precomputed database</p><p>Software (C++/Python)</p><p><a href="https://sourceforge.net/projects/lmat/">https://sourceforge.net/projects/lmat/</a></p><p>stringMLST</p><p><em>k</em>-mer-based tool for MLST directly from the genome sequencing reads</p><p>Software (Python)</p><p><a href="http://jordan.biology.gatech.edu/page/software/stringMLST">http://jordan.biology.gatech.edu/page/software/stringMLST</a></p><p>Taxonomer</p><p><em>k</em>-mer-based ultrafast metagenomics tool for assigning taxonomy to sequencing reads from clinical and environmental samples</p><p>Web service</p><p><a href="http://taxonomer.iobio.io/">http://taxonomer.iobio.io/</a></p><p>Other</p><p>d2-tools</p><p>Word-based (<em>k</em>-tuple) comparison (pairwise dissimilarity matrix using d2S measure) of metatranscriptomic samples from NGS reads</p><p>Software (Python/R)</p><p><a href="https://code.google.com/p/d2-tools/">https://code.google.com/p/d2-tools/</a></p><p>VirHostMatcher</p><p>Prediction of hosts from metagenomic viral sequences based on ONF using various distance measures (e.g., d2)</p><p>Software (C++)</p><p><a href="https://github.com/jessieren/VirHostMatcher">https://github.com/jessieren/VirHostMatcher</a></p><p>MetaFast</p><p>Statistics calculation of metagenome sequences and the distances between them based on assembly using de Bruijn graphs and Bray&ndash;Curtis dissimilarity measure</p><p>Software (Java)</p><p><a href="https://github.com/ctlab/metafast">https://github.com/ctlab/metafast</a></p></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/25400/arraygen-next-generation-genome-browser-coming-soon</guid>
	<pubDate>Thu, 03 Dec 2015 05:52:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/25400/arraygen-next-generation-genome-browser-coming-soon</link>
	<title><![CDATA[ArrayGen Next Generation Genome Browser Coming Soon !!!]]></title>
	<description><![CDATA[<p>The ANG genome browser is a visualization tool, developed by ArrayGen Technologies. This is a fast and an efficient genome browser, built with Javafx and Java swing. ANG genome browser was built for latest next generation sequencing data analysis. It is platform independent and much simpler to use.</p><p>The main features are, it supports many standard file formats such as GFF, BED, GTF, FASTA, VCF, BAM and it can be integrated with other browsers or tools for analysis of genome.</p>]]></description>
	<dc:creator>ArrayGen Technologies</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36974/many-to-many-pairwise-alignments-of-two-sequence-sets</guid>
	<pubDate>Tue, 19 Jun 2018 08:34:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36974/many-to-many-pairwise-alignments-of-two-sequence-sets</link>
	<title><![CDATA[Many-to-many pairwise alignments of two sequence sets]]></title>
	<description><![CDATA[needleall reads a set of input sequences and compares them all to one or more sequences, writing their optimal global sequence alignments to file. It uses the Needleman-Wunsch alignment algorithm to find the optimum alignment (including gaps) of two sequences along their entire length. The algorithm uses a dynamic programming method to ensure the alignment is optimum, by exploring all possible alignments and choosing the best. A scoring matrix is read that contains values for every possible residue or nucleotide match. Needleall finds the alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix, minus penalties arising from opening and extending gaps in the aligned sequences. The substitution matrix and gap opening and extension penalties are user-specified.<p>Address of the bookmark: <a href="http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html" rel="nofollow">http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25410/srfjrf-bioinformatics-at-ciari</guid>
  <pubDate>Fri, 04 Dec 2015 00:10:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF/JRF Bioinformatics at CIARI]]></title>
  <description><![CDATA[
<p>Realizing the importance of Island Agriculture to meet the requirements of local population and tourists, Indian Council of Agricultural research (ICAR) established Central Island Agricultural Research Institute, Port Blair on June 23rd, 1978 by merging different regional research stations of ICAR institutes located in Islands. The ultimate aim of CIARI is the developments of island agricultural production technologies which utilizes the strengths of the island and convert the constraints in opportunities, without causing any ill effect to the fragile ecosystem of the island.The institute has made tremendous progress in the Agriculture development of the islands during the last three decades. Keeping in view the natural resources of the islands diversity, fragile ecosystem, research program would be designed to maximize the productivity without disturbing to the islands ecosystem to provide better and decent livelihood and as a source of revenue and resource generation. Research and development in Agriculture sector should cover all disciplines in order to have a balanced progress in all disciplines for the overall benefits of the farmers of these islands.</p>

<p>Position I</p>

<p>Job Title : Junior Research Fellow</p>

<p>No. of Posts : One</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : M.Sc in Basic Science with NET or B.Sc in professional course with NET or M.Sc in professional course</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 25000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>Position II</p>

<p>Job Title : Traineeship</p>

<p>No. of Posts : One</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : B.Sc Bioinformatics /Biotechnology / Life Science / Computer Science</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 8000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>Position III</p>

<p>Job Title : Studentship</p>

<p>No. of Posts : Two</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : B.Sc Bioinformatics /Biotechnology / Life Science / Computer Science</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 8000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>How to Apply : Candidates who meet the requirements can attend the walk in interview at CIARI,Port Blair on 09.12.2015 10.30AM.</p>

<p>http://icar-ciari.res.in/employment/9-12-15.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25674/post-doc-position-at-labgem-evry-france</guid>
  <pubDate>Fri, 11 Dec 2015 06:24:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post-doc position at LABGeM - Evry, France]]></title>
  <description><![CDATA[
<p>The LABGeM team (CEA/Genoscope, CNRS UMR 8030, France, Dir. Claudine Médigue) is developing integrated approaches which combines bioinformatics methods based (i) on genomic and metabolic contexts, (ii) on an orignal metabolic network representation and (iii) on a structural classification of active sites for the discovery of new metabolic enzymatic activities.</p>

<p>We are hiring a post-doctoral fellow for the development of innovative bioinformatics methods to explore metabolic networks and enzyme families. These methods will be based on protein family analysis and graph approaches combining genomic and metabolic contexts.</p>

<p>For more details, please see this link : http://goo.gl/tHQOqk</p>

<p>Qualifications:<br />PhD degree in bioinformatics or computational biology<br />- Previous experience in network or protein family analysis<br />- Programming skills (C/C++, Python, Java) and in common biostatistical analyses<br />- Team player, innovative and creative thinking, good oral and written communication skills</p>

<p>24 months, Post Doctoral position<br />Start: from March 2016<br />Place: CEA, Genoscope UMR8030, LABGeM (Laboratory of Bioinformatics Analyses for Genomics and Metabolism), Evry, France<br />Contact: David Vallenet, vallenet@genoscope.cns.fr<br />Publications: https://scholar.google.com/citations?user=rJNPLSAAAAAJ<br />Remuneration per month: from 2,850 €</p>

<p>Interested candidates should send their CV, statement of research interests, and contact information of at least 2 references to David Vallenet (vallenet@genoscope.cns.fr).</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment</guid>
	<pubDate>Tue, 09 Jul 2019 23:58:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment</link>
	<title><![CDATA[MSAProbs - Parallel and accurate multiple sequence alignment]]></title>
	<description><![CDATA[<p><strong>MSAProbs</strong><span>&nbsp;is a well-established state-of-the-art multiple sequence alignment algorithm for protein sequences. The design of MSAProbs is based on a combination of pair hidden Markov models and partition functions to calculate posterior probabilities. Assessed using the popular benchmarks: BAliBASE, PREFAB, SABmark and OXBENCH, MSAProbs achieves statistically significant accuracy improvements over the existing top performing aligners, including ClustalW, MAFFT, MUSCLE, ProbCons and Probalign. In addition, MSAProbs is optimized for shared-memory CPUs by employing a multi-threaded design, and further parallelized for distributed-memory systems using MPI to overcome high memory overhead barrier and achieve good parallel and data-size scalability.</span></p><p>Address of the bookmark: <a href="http://msaprobs.sourceforge.net/homepage.htm#latest" rel="nofollow">http://msaprobs.sourceforge.net/homepage.htm#latest</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26559/microscope</guid>
	<pubDate>Fri, 04 Mar 2016 05:26:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26559/microscope</link>
	<title><![CDATA[Microscope]]></title>
	<description><![CDATA[<p>Microscope Platform user documentation.</p>
<p>The MicroScope platform is available at this URL:</p>
<p><a href="https://www.genoscope.cns.fr/agc/microscope">https://www.genoscope.cns.fr/agc/microscope</a></p><p>Address of the bookmark: <a href="http://microscope.readthedocs.org/en/latest/index.html" rel="nofollow">http://microscope.readthedocs.org/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</guid>
	<pubDate>Mon, 04 Nov 2019 07:09:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</link>
	<title><![CDATA[Shouji: a fast and efficient pre-alignment filter for sequence alignment]]></title>
	<description><![CDATA[<p>The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.</p>
<p>&nbsp;<img src="https://github.com/BilkentCompGen/Shoji/raw/master/Figure1-GitHub.png" alt="image" style="border: 0px;"></p>
<p>We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.</p>
<p>More at <a href="https://github.com/CMU-SAFARI/Shouji">https://github.com/CMU-SAFARI/Shouji</a></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/Shouji" rel="nofollow">https://github.com/CMU-SAFARI/Shouji</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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