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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34328?offset=390</link>
	<atom:link href="https://bioinformaticsonline.com/related/34328?offset=390" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41675/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Thu, 14 May 2020 15:13:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41675/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>gapFinisher to process SSPACE-LongRead output to fill gaps after the scaffolding. gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines.</p>
<p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733440/</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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Mon, 17 Aug 2020 05:25:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p>SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol>
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43353/judi-just-do-it</guid>
	<pubDate>Mon, 06 Sep 2021 02:44:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43353/judi-just-do-it</link>
	<title><![CDATA[JUDI: Just Do It]]></title>
	<description><![CDATA[<p><em>judi</em><span>&nbsp;comes from the idea of bringing the power and efficiency of&nbsp;</span><em>doit</em><span>&nbsp;to execute any kind of task under many combinations of parameter settings.</span></p>
<p><span>https://github.com/ncbi/JUDI</span></p><p>Address of the bookmark: <a href="https://github.com/ncbi/JUDI" rel="nofollow">https://github.com/ncbi/JUDI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44597/imagine-in-silico-metagenomics-pipeline</guid>
	<pubDate>Sat, 06 Jul 2024 04:32:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44597/imagine-in-silico-metagenomics-pipeline</link>
	<title><![CDATA[iMAGine - in silico MetAGenomics pipeline]]></title>
	<description><![CDATA[<p dir="auto"><span>iMAGine</span>&nbsp;is a metagenomic workflow which includes filtering, assembling, and binning.</p>
<p dir="auto">This workflow includes the following tools which are needed to be installed in the system.</p>
<ol dir="auto">
<li><a href="https://github.com/OpenGene/fastp">fastp</a></li>
<li><a href="https://github.com/ablab/spades">spades assembler</a></li>
<li><a href="https://github.com/ablab/quast">QUAST</a></li>
<li><a href="https://github.com/lh3/bwa">bwa</a></li>
<li><a href="https://github.com/samtools/samtools">samtools</a></li>
<li><a href="https://bitbucket.org/berkeleylab/metabat/src/master/">metabat2</a></li>
<li><a href="https://github.com/Ecogenomics/CheckM">CheckM</a></li>
</ol><p>Address of the bookmark: <a href="https://github.com/avishekdutta14/iMAGine" rel="nofollow">https://github.com/avishekdutta14/iMAGine</a></p>]]></description>
	<dc:creator>BioStar</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/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26363/flo</guid>
	<pubDate>Wed, 10 Feb 2016 10:52:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26363/flo</link>
	<title><![CDATA[flo]]></title>
	<description><![CDATA[<p>flo - same species annotations lift over pipeline</p>
<p>Lift over is the process of transferring annotations from one genome assembly to another. Usually lift over is done because there is a new, improved genome assembly for the species and good quality annotations (maybe manually curated or experimentally verified) are available on the old assembly.</p>
<p>The idea is simple: align the new assembly with the old one (e.g., with BLAT), process the alignment data to define how a coordinate or coordinate range on the old assembly should be transformed to the new assembly (e.g., as a chain file), transform the coordinates (e.g., with liftOver).</p>
<p>&nbsp;</p>
<p>https://github.com/wurmlab/flo</p><p>Address of the bookmark: <a href="https://github.com/wurmlab/flo" rel="nofollow">https://github.com/wurmlab/flo</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34862/pasa-gene-structure-annotation-and-analysis</guid>
	<pubDate>Tue, 26 Dec 2017 21:14:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34862/pasa-gene-structure-annotation-and-analysis</link>
	<title><![CDATA[PASA: Gene Structure Annotation and Analysis]]></title>
	<description><![CDATA[<p><span>PASA, acronym for Program to Assemble Spliced Alignments, is a eukaryotic genome annotation tool that exploits spliced alignments of expressed transcript sequences to automatically model gene structures, and to maintain gene structure annotation consistent with the most recently available experimental sequence data. PASA also identifies and classifies all splicing variations supported by the transcript alignments.</span></p><p>Address of the bookmark: <a href="http://pasapipeline.github.io/" rel="nofollow">http://pasapipeline.github.io/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Sat, 07 Sep 2019 10:45:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]></title>
	<description><![CDATA[<p><code>chromoMap</code>&nbsp;provides interactive, configurable and elegant graphics visualization of chromosomes or chromosomal regions allowing users to map chromosome elements (like genes,SNPs etc.) on the chromosome plot.Each chromosome is composed of loci(representing a specific range determined based on chromosome length) that, on hover, shows details about the annotations in that locus range. The plots can be saved as HTML documents that can be shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>
<p>Some of the prominent features of the package are:</p>
<ul>
<li>visualizing polyploidy simultaneously on the same plot.</li>
<li>annotating groups of elements as distinct colors.</li>
<li>creating chromosome heatmaps.</li>
<li>adjusting chromosome range or visualizing chromosome regions such as genes</li>
<li>adding labels to the plot</li>
<li>adding hyperlinks to each element</li>
</ul><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html" rel="nofollow">https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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