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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28805?offset=1250</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</guid>
	<pubDate>Fri, 14 Apr 2017 06:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</link>
	<title><![CDATA[DeCoSTAR - Detection of Co-evolution]]></title>
	<description><![CDATA[<p><span>DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.</span><br><span>Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the&nbsp;</span><a href="http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA">ecceTERA package</a><span>, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.&nbsp;</span><br><span>DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.</span></p><p>Address of the bookmark: <a href="http://pbil.univ-lyon1.fr/software/DeCoSTAR/" rel="nofollow">http://pbil.univ-lyon1.fr/software/DeCoSTAR/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/32358/list-of-goi-approved-peer-reviewed-bioinformatics-and-computational-biology-journals</guid>
	<pubDate>Tue, 25 Apr 2017 05:03:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/32358/list-of-goi-approved-peer-reviewed-bioinformatics-and-computational-biology-journals</link>
	<title><![CDATA[List of GOI approved peer reviewed bioinformatics and computational biology journals]]></title>
	<description><![CDATA[<p>Unfortunately, we now live in a world where the integrity of peer-reviewed journals is being threatened by the rise of the academic version of fake news &ndash; something many call &ldquo;predatory publishing". &nbsp;Mostly in academic publishing world, "predatory open access publishing" is an exploitative open-access publishing business model that involves charging publication fees to authors without providing the editorial and publishing services associated with legitimate journals (open access or not).</p><p>Nearly 20% of the such journals have a flashy impact factor and quick publication time, which are quick give-aways. Interestingly, under contact address, some journal websites do not even provide any address to contact. All of this has led to the emergence of a new and dark market of deceptive publishers that exploit the concept of open access and provide channels for &ldquo;scientific journal&rdquo; publication with little or no peer review. For a fee, they will publish almost anything &ndash; even if the study was fatally flawed. And these journals provide a forum that can be used as a channel to publish fraudulent &ldquo;advocacy research.&rdquo; You can find list of certain such publishers at "Beall's List" http://beallslist.weebly.com/</p><p>Keeping all these in mind, Government of India (GOI) decided to approved certain bioinformatics and computational biology journals for your research publication.<br /> <br />Following are the list of GOI validated and peer reviewed bioinformatics and computational biology journals:</p><p><strong>NOTE:Each journal details are in following order Tittle\nSource\nSubject. </strong><br /><strong>Point to remember: The list of journals are NOT sorted in any ascending or descending order.</strong></p><p><em>If I missed any other GOI validated bioinformatics journal, then please report me in comment section.</em></p><p><strong>Open Bioinformatics Journal</strong> <br />Scopus <br />Computer Science; Engineering; Medicine</p><p><strong>PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS</strong> <br />WoS <br />BIOLOGY &amp; BIOCHEMISTRY</p><p><strong>Advances and Applications in Bioinformatics and Chemistry</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology Chemistry; Computer Science</p><p><strong>Advances in Bioinformatics</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science; Engineering</p><p><strong>Applied Bioinformatics</strong><br />Scopus<br />Agricultural and Biological Sciences; Computer Science</p><p><strong>BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Bioinformatics and Biology Insights</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science; Mathematics</p><p><strong>BMC BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>BRIEFINGS IN BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Computational systems bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference</strong> <br />Scopus <br />Medicine</p><p><strong>Current Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Current Protocols in Bioinformatics</strong> <br />Scopus <br />Biochemistry, Genetics and Molecular Biology</p><p><strong>JOURNAL OF COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS</strong> <br />ICI <br />BIOLOGICAL SCIENCE</p><p><strong>Journal of integrative bioinformatics</strong> <br />Scopus <br />Medicine</p><p><strong>Journal of Proteomics and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science</p><p><strong>Mathematical Biology and Bioinformatics</strong> <br />Scopus <br />Engineering; Mathematics</p><p><strong>Trends in Bioinfprmatics</strong><br />Scopus <br />Computer Science</p><p><strong>Eurasip Journal on Bioinformatics and Systems Biology</strong> <br />Scopus<br />General; Computer Science; Mathematics; Medicine</p><p><strong>Evolutionary Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Genomics, Proteomics and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Mathematics</p><p><strong>IEEE/ACM Transactions on Computational Biology and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Mathematics</p><p><strong>IEEE-ACM Transactions on Computational Biology and Bioinformatics</strong> <br />WoS <br />COMPUTER SCIENCE</p><p><strong>International Journal of Bioinformatics Research and Application</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Medicine, Health</p><p><strong>International Journal o f Data M ining and Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>IPSJ Transactions on Bioinformatics</strong> <br />Scopus <br />Biochemistry, Genetics and Molecular Biology;Computer Science</p><p><strong>Journal of Bioinformatics and Computational Biology</strong> <br />WoS &amp; Scopus<br />COMPUTER SCIENCE</p><p><strong>Journal of Clinical Bioinformatics</strong> <br />Scopus <br />Medicine</p><p><strong>PLoS Computational Biology</strong> <br />WoS &amp; Scopus <br />BIOLOGY &amp; BIOCHEMISTRY</p><p><strong>Reviews in Computational Chemistry</strong> <br />WoS &amp; Scopus <br />CHEMISTRY</p><p><strong>RSC Theoretical and Computational Chemistry Series</strong><br />Scopus <br />Chemistry; Computer Science</p><p><strong>Annual Reports in Computational Chemistry</strong> <br />Scopus <br />Chemistry; Mathematics</p><p><strong>Computational and Structural Biotechnology Journal</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science</p><p><strong>Computational and Theoretical Chemistry</strong> <br />WoS &amp; Scopus <br />CHEMISTRY</p><p><strong>COMPUTATIONAL BIOLOGY AND CHEMISTRY</strong> <br />WoS &amp; Scopus<br />COMPUTER SCIENCE</p><p><strong>COMPUTATIONAL CHEMISTRY</strong> <br />WoS <br />CHEMISTRY</p><p><strong>Journal of Theoretical and Computational Chemistry</strong> <br />Scopus<br />Chemistry; Computer Science</p><p><strong>Theoretical and Computational Chemistry</strong> <br />Scopus <br />Chemistry</p><p><strong>Wiley Interdisciplinary Reviews: Computational Molecular Science</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Chemistry; Computer Science; Materials Science; Mathematics</p><p><strong>Wiley Interdisciplinary Reviews- Computational Molecular Science</strong> <br />WoS <br />CHEMISTRY</p><p><strong>Interdisciplinary sciences, computational life sciences</strong><br />Scopus<br />Medicine</p><p><strong>Interdisciplinary Sciences-Computational Life Science</strong><br />WoS<br />Biology and Biochemistry</p><p><strong>International Journal of Computational Biology and Drug Design</strong><br />Scopus<br />Computer Science; Pharmacology, Toxicology and Pharmaceutics</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32420/fastq-format</guid>
	<pubDate>Wed, 03 May 2017 04:23:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32420/fastq-format</link>
	<title><![CDATA[Fastq format]]></title>
	<description><![CDATA[<p><strong>FASTQ format</strong>&nbsp;is a text-based&nbsp;<a href="https://en.wikipedia.org/wiki/File_format" title="File format">format</a>&nbsp;for storing both a biological sequence (usually&nbsp;<a href="https://en.wikipedia.org/wiki/Nucleotide_sequence" title="Nucleotide sequence">nucleotide sequence</a>) and its corresponding quality scores. Both the sequence letter and quality score are each encoded with a single&nbsp;<a href="https://en.wikipedia.org/wiki/ASCII" title="ASCII">ASCII</a>&nbsp;character for brevity.</p>
<p>It was originally developed at the&nbsp;<a href="https://en.wikipedia.org/wiki/Wellcome_Trust_Sanger_Institute" title="Wellcome Trust Sanger Institute">Wellcome Trust Sanger Institute</a>&nbsp;to bundle a&nbsp;<a href="https://en.wikipedia.org/wiki/FASTA_format" title="FASTA format">FASTA</a>&nbsp;sequence and its quality data, but has recently become the&nbsp;<em>de facto</em>&nbsp;standard for storing the output of high-throughput sequencing instruments such as the&nbsp;<a href="https://en.wikipedia.org/wiki/Illumina_(company)" title="Illumina (company)">Illumina</a>&nbsp;Genome Analyzer.<sup id="cite_ref-Cock2009_1-0"><a href="https://en.wikipedia.org/wiki/FASTQ_format#cite_note-Cock2009-1">[1]</a></sup></p><p>Address of the bookmark: <a href="https://en.wikipedia.org/wiki/FASTQ_format" rel="nofollow">https://en.wikipedia.org/wiki/FASTQ_format</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</guid>
	<pubDate>Tue, 07 Nov 2017 04:36:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</link>
	<title><![CDATA[Meraculous: De Novo Genome Assembly with Short Paired-End Reads]]></title>
	<description><![CDATA[<p><span>We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast&nbsp;</span><em>Pichia stipitis</em><span>. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the&nbsp;</span><em>k</em><span>-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by &sim;280 bp or &sim;3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32496/bioinformatician-at-23andme</guid>
  <pubDate>Sat, 06 May 2017 17:57:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician at 23andMe]]></title>
  <description><![CDATA[
<p>23andMe’s mission is to help people access, understand, and benefit<br />from the human genome. We are a group of passionate individuals excited<br />to push the boundaries of what’s possible to help turn genetic insight<br />into better health and personal understanding.</p>

<p>Our Research Team prides itself on driving cutting edge, industrial-scale<br />science to make an impact that belies the team’s size, in an environment<br />and culture that fosters creativity, innovation, collaboration, and fun.</p>

<p>More than 80% of our customers consent to participate in research, and as<br />a result of their participation, we have one of the largest recontactable,<br />genotyped, and phenotyped research cohorts in the world. The scope and<br />breadth of our vision means that most of the methods and tools necessary<br />to unlock the potential of this unique resource for discovery have yet<br />to be developed.</p>

<p>Our science has garnered the respect of many members of the<br />broader scientific community. For a list of our publications, see<br />www.23andme.com/publications/for-scientists/.</p>

<p>Join us! Visit our Careers page (www.23andMe.com/careers) to learn more<br />about these open positions:</p>

<p>•	Scientist, Research Communications<br />•	Bioinformaticist<br />•	Computational Biologist, Ancestry R&amp;D<br />•	Scientist/Senior Scientist, Statistical Genetics<br />•	Scientist/Senior Scientist, Survey Methodology<br />•	Scientist/Senior Scientist, Health R&amp;D<br />•	Senior Computational Biologist<br />•	Biostatistician</p>

<p>pfontanillas@23andme.com</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</guid>
	<pubDate>Wed, 07 Feb 2018 09:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</link>
	<title><![CDATA[HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution]]></title>
	<description><![CDATA[<p>Software accompanying "HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution"</p>
<ul>
<li>
<p>Preprint:&nbsp;<a href="http://biorxiv.org/content/early/2016/08/01/062117">http://biorxiv.org/content/early/2016/08/01/062117</a></p>
</li>
<li>
<p>Paper:&nbsp;<a href="http://genome.cshlp.org/content/27/5/747.full">http://genome.cshlp.org/content/27/5/747.full</a></p>
</li>
<li>
<p>An ipython notebook to reproduce results in the paper can be found in this&nbsp;<a href="https://github.com/govinda-kamath/HINGE-analyses">repository</a>.</p>
</li>
</ul>
<p>HINGE is an OLC(Overlap-Layout-Consensus) assembler. The idea of the pipeline is shown below.</p>
<p><a href="https://github.com/HingeAssembler/HINGE/blob/master/misc/High_level_overview.png" target="_blank"><img src="https://github.com/HingeAssembler/HINGE/raw/master/misc/High_level_overview.png" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/HingeAssembler/HINGE" rel="nofollow">https://github.com/HingeAssembler/HINGE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32716/jrfsrf-project-assistant-ii-recruitment-in-national-agri-food-biotechnology-institute-nabi</guid>
  <pubDate>Mon, 15 May 2017 05:37:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF / Project Assistant-II recruitment in National Agri-Food Biotechnology Institute (NABI)]]></title>
  <description><![CDATA[
<p>National Agri-Food Biotechnology Institute<br />ADVT. No: 2017-Researcher (02)</p>

<p>JRF/SRF / Project Assistant-II recruitment in National Agri-Food Biotechnology Institute (NABI)</p>

<p>Essential Qualification: According to the DST (DST OM No.SR/S9/Z-09/2012 dated 21.10.2014) Post Graduate degree in basic science(M.Sc) in Bioinformatics/Computational Biology/Systems Biology/Information Technology with NET or Graduate degree in professional course with NET or Post Graduate Degree (M.Tech) in professional course in Bioinformatics/Computational Biology/Systems Biology/Information Technology. Desirable qualification/skills: 1) Should be proficient in programming in Perl/Python/R language etc. 2) Should have knowledge and skills for data mining in biological sequence database . sequence analysis tools/packages, NGS Analysis . 3) Should have knowledge and skills to work in linux environment and write shell scripts.</p>

<p>Age : 28 years</p>

<p>Hiring Process : Written-test<br />Job Role : Research/JRF/SRF<br />How to apply</p>

<p>Application should be sent to Administrative officer, National Agri-Food Biotechnology Institute, Knowledge City, Sector-81, Mohali so as to reach latest by 30.05.2017 before 5:30 pm.</p>

<p>More at http://www.nabi.res.in/Vacancies/NABI/ResearchFellowships/JRFSRFRA/2017/ADVT.%20No%202017Researcher%20(02)/ApplicationForm.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab</guid>
	<pubDate>Fri, 30 Jun 2017 08:48:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab</link>
	<title><![CDATA[DIYA: a bacterial annotation pipeline for any genomics lab]]></title>
	<description><![CDATA[<p><span>DIY Genomics is an open source bioinformatics consortium intended to bring a collection of tools and libraries into the hands of small scale genomics labs for the process of sequence assembly and annotation. Projects include DIYA, MGAP, CRISPR, and DIYGV</span></p>
<p><span>http://gmod.org/wiki/Diya</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/diyg/" rel="nofollow">https://sourceforge.net/projects/diyg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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