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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32011?offset=400</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</guid>
	<pubDate>Fri, 04 Oct 2024 02:45:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</link>
	<title><![CDATA[Libraries or management tools for high throughput sequencing data]]></title>
	<description><![CDATA[<ul>
<li><a href="http://gatb.inria.fr/"><span>GATB</span></a>&nbsp;Library.&nbsp;The&nbsp;<span>Genome Analysis Toolbox with de-Bruijn graph.&nbsp;</span>A large part of tools developed by the GenScale team are based on this library.<br />These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (<em>e.g.</em>&nbsp;metagenomes). Among them are (the full is available here:&nbsp;<a href="https://gatb.inria.fr/software/">https://gatb.inria.fr/software/</a>):</li>
<li><a href="https://github.com/morispi/LRez"><span>LRez</span></a>: C++ Library and toolkit for the barcode-based management and indexation of linked-read datasets.</li>
</ul><h2>Variant calling and/or genotyping</h2><ul>
<li><a href="https://gatb.inria.fr/software/discosnp/" title="DiscoSNP">DiscoSNP++ and&nbsp;discoSnpRAD</a>: Reference-free small variant discovery (SNPs and indels)</li>
<li><a href="https://gatb.inria.fr/software/mind-the-gap/" title="MindTheGap">MindTheGap</a>: Detection and assembly of large insertion variants</li>
<li><a href="https://gatb.inria.fr/software/takeabreak/" title="TakeABreak">TakeABreak</a>:&nbsp;reference-free inversion discovery tool</li>
<li><a href="https://github.com/llecompte/SVJedi">SVJedi</a>: Structural Variant genotyper with long read data</li>
<li><a href="https://github.com/SandraLouise/SVJedi-graph">SVJedi-graph</a>: Structural Variant genotyper with long read data using a variation graph</li>
</ul><h2>Sequence assembly</h2><ul>
<li><a href="https://github.com/cguyomar/MinYS">MinYS</a>: reference-guided genome assembly in metagenomics data</li>
<li><a href="https://github.com/anne-gcd/MTG-Link">MTG-link</a>: local assembly tool for linked-read data</li>
<li><a href="https://gatb.inria.fr/software/minia/" title="Minia">Minia</a>: De novo short read assembler</li>
<li><a href="https://gatb.inria.fr/de-novo-genome-assembly/">de-novo pipeline</a>:&nbsp;<em>de-novo</em>&nbsp;assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes</li>
<li><a href="https://gatb.inria.fr/software/mapsembler/" title="Mapsembler2">Mapsembler2</a>: Targeted assembly (not maintained)</li>
</ul><h2>Managing k-mers &amp; indexation</h2><ul>
<li><a href="https://github.com/lrobidou/findere">findere</a>:&nbsp;simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
<ul>
<li><a href="https://github.com/lrobidou/fimpera">fimpera</a>&nbsp;extends findere adding the abundance information.</li>
</ul>
</li>
<li><a href="https://github.com/tlemane/kmtricks">kmtricks</a>:&nbsp;modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.</li>
<li><a href="https://github.com/tlemane/kmindex">kmindex&nbsp;</a>is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.</li>
<li><a href="https://github.com/pierrepeterlongo/back_to_sequences">back to sequences</a>: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.</li>
<li><a href="https://github.com/vicLeva/bqf">Backpack Quotient Filter</a>:&nbsp;k-mer indexing data structure with abundance</li>
<li><a href="http://github.com/GATB/rconnector">short read connector</a>:&nbsp;Detect similar reads from potentially large read set</li>
<li><a href="https://gatb.inria.fr/software/dsk/" title="DSK">DSK</a>:&nbsp;Count K-mer in sequences</li>
</ul><h2>Pangenome graph manipulation</h2><ul>
<li><a href="https://github.com/Tharos-ux/pancat">Pancat</a>: Pangenome Comparison and Analysis Toolkit</li>
<li><a href="https://pypi.org/project/gfagraphs/">GFAGraphs</a>: a Python library to handle pangenome graph files in GFA format.</li>
</ul><h2>Comparative metagenomics with k-mers</h2><ul>
<li><a href="https://github.com/GATB/simka">Simka and SimkaMin</a>:&nbsp;Comparative metagenomics for large-scale datasets</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/compreads-metagenomic-data-analysis/">Comparead &amp; Commet</a>:&nbsp;comparison of metagenomic datasets</li>
</ul><h2>Species and bacterial strains identification</h2><ul>
<li><a href="https://github.com/gsiekaniec/ORI">ORI</a>: software using long nanopore reads to identify bacteria present in a sample at the strain level</li>
<li><a href="https://github.com/kevsilva/StrainFLAIR">StrainFLAIR</a>:&nbsp;STRAIN-level proFiLing using vArIation gRaph</li>
</ul><h2>General-purpose sequencing data manipulation</h2><ul>
<li><a href="https://team.inria.fr/genscale/ngs-software/gassst/">GASSST</a>:&nbsp;long read mapper</li>
<li><a href="https://gatb.inria.fr/software/leon/" title="Leon">Leon</a>: short read compressor (now included in GATB-core)</li>
<li><a href="https://gatb.inria.fr/software/bloocoo/" title="Bloocoo">Bloocoo</a>:&nbsp;short read corrector</li>
<li><a href="https://github.com/GATB/bcalm">BCALM</a>:&nbsp;Construct compacted de Bruijn graphs (unitigs)</li>
</ul><h2>&nbsp;Protein Structure</h2><ul>
<li><a href="https://team.inria.fr/genscale/protein-structure/a-purva-contact-map-overlap-solver/">A_Purva</a>:&nbsp;Contact Map Overlap solver</li>
<li><a href="https://team.inria.fr/genscale/protein-structure/md-jeep-distance-geomtry-solver/">MD-Jeep</a>:&nbsp;Distance Geometry solver</li>
<li><a href="https://team.inria.fr/genscale/csa-comparative-structural-alignment/">CSA</a>:&nbsp;Comparative Structural Alignment</li>
</ul><h2>Workflow</h2><ul>
<li><a href="https://team.inria.fr/genscale/workflows/slicee/">SLICEE</a>:&nbsp;parallel execution of bioinformatics workflows</li>
</ul><h3>Comparative Genomics</h3><ul>
<li><a href="https://team.inria.fr/genscale/comparative-genomics/cassis/">CASSIS</a>:&nbsp;detection of rearrangement breakpoints</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/plast-intensive-sequence-comparison/">PLAST</a>:&nbsp;intensive bank-to-bank sequence comparison</li>
<li><a href="https://github.com/stephanierobin/DrjBreakpointFinder">DRJBreakpointFinder</a>: detection and precise localization of excision sites in proviral segments</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</guid>
	<pubDate>Wed, 13 Aug 2014 18:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</link>
	<title><![CDATA[Dynamic chromosome breakpoints !!!]]></title>
	<description><![CDATA[<p>Cell division involves the distribution of identical genetic material, DNA, to two daughters&rsquo; cells. During this process, duplicated deoxyribonucleic acid (DNA) goes through a condensation and decondensation process. This is followed by nuclear envelope dissolution, mitotic spindle assembly, migration of the sister chromatid pairs to the metaphase plate, division and segregation of identical sets of chromosomes into daughter nuclei and nuclear envelope reformation.</p><p>The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo <strong>recombination </strong>which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.</p><p><img src="http://www.sciencelearn.org.nz/var/sciencelearn/storage/images/contexts/uniquely-me/sci-media/images/chromosomes-crossing-over/464438-1-eng-NZ/Chromosomes-crossing-over.jpg" alt="image" width="504" height="342" style="border: 0px; border: 0px;"></p><p>During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The &ldquo;<strong>chromosomal breakpoints</strong>&rdquo; refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this &ldquo;break and sealing/ break and reattach&rdquo; process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities &nbsp;where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.</p><p>&nbsp;</p><p>&nbsp;</p><p><img src="http://upload.wikimedia.org/wikipedia/commons/4/4a/Chromosomal_translocations.svg" alt="image" width="424" height="331" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>Apart from certain chromosome abnormalities, these &ldquo;crossing over&rdquo; of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.</p><p>I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/&nbsp; in my next blog.</p><p><strong>Software for recombination detection:</strong></p><p><strong>RAT</strong> http://cbr.jic.ac.uk/dicks/software/RAT/</p><p><strong>Breakpointer</strong> https://github.com/ruping/Breakpointer</p><p><strong>DRP</strong> http://web.cbio.uct.ac.za/~darren/rdp.html</p><p><strong>RB-finder</strong> http://www.ncbi.nlm.nih.gov/pubmed/18707535</p><p><strong>LDhat2.0</strong> http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml</p><p><strong>Reference:</strong></p><p>http://www.nature.com/scitable/topicpage/genetic-recombination-514#</p><p>Image: Wikipedia , sciencelearn.org.nz</p><p><strong>Recommended Articles:</strong></p><p>http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/</p><p>http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf</p><p>http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/</p><p>http://learn.genetics.utah.edu/content/disorders/chromosomal/</p><p>http://www.ncert.nic.in/html/learning_basket/biology/cc&amp;cd.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</guid>
	<pubDate>Thu, 26 Jul 2018 04:51:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</link>
	<title><![CDATA[Nanopolis: polish a genome assembly]]></title>
	<description><![CDATA[<p><span>Software package for signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more (see Nanopolish modules, below).</span></p>
<p>Quickstart</p>
<p>http://nanopolish.readthedocs.io/en/latest/quickstart_consensus.html</p>
<p>Algorithms</p>
<p>http://simpsonlab.github.io/2017/06/30/nanopolish-v0.7.0/</p><p>Address of the bookmark: <a href="https://github.com/jts/nanopolish" rel="nofollow">https://github.com/jts/nanopolish</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14183/guest-faculty-at-pondicherry-university</guid>
  <pubDate>Wed, 20 Aug 2014 00:37:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Faculty at Pondicherry University]]></title>
  <description><![CDATA[
<p>Pondicherry University, India</p>

<p>Walk in interview for guest faculty in Pondicherry University, India. For more information please visit http://www.bicpu.edu.in/bioinfor140814.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers</guid>
	<pubDate>Mon, 25 Aug 2014 01:26:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers</link>
	<title><![CDATA[Apps for Busy Bioinformatics Researchers !!!]]></title>
	<description><![CDATA[<h3>DNAApp:</h3><h4><strong>DNAApp: for </strong><a href="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8" target="_blank"><strong>iPhone/iPad</strong></a></h4><p>This is an <a href="http://www.apple.com/ios/" target="_blank" title="IOS">iOS</a> app that allows for the opening and analysis of <a href="http://en.wikipedia.org/wiki/DNA_sequencing" target="_blank" title="DNA sequencing">DNA sequencing</a> files - ab1. It includes handy tools such as "<a href="http://en.wikipedia.org/wiki/Complementarity_%28molecular_biology%29" target="_blank" title="Complementarity (molecular biology)">Reverse Complement</a>", "Jump to", "<a href="http://en.wikipedia.org/wiki/Cut%2C_copy%2C_and_paste" target="_blank" title="Cut, copy, and paste">Copy and Paste</a> sequences", fast and end scrolling, "<a href="http://en.wikipedia.org/wiki/Chromatography" target="_blank" title="Chromatography">Chromatogram</a> adjustments", and "Searching for segments" functions. <br /> When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files. <br /> This app works with cloud storage access like Dropbox to your sequencing files. <br /> This is now compatible with the new update for iOS 7.1. <br /> Demo video can be found at:<strong> https://www.youtube.com/watch?v=mXeo9hXdZgM&nbsp;</strong></p><p><strong>More @ </strong><a href="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8" target="_blank" title="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8"><strong>https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8</strong></a></p><h4><a href="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en" target="_blank"><strong>DNAApp: For android</strong></a></h4><p>This is the first android app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", fast and end scrolling, "Chromatogram adjustments", amino acid translations, "export to fasta", and "searching for segment" function.</p><ul>
<li>When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.</li>
<li>This app works with cloud storage access like Dropbox to your sequencing files.</li>
<li>This is now compatible with the new update for <a href="http://code.google.com/android/" target="_blank" title="Android">Android</a> 4.4.2.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en"><strong>https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en</strong></a></p><h3>BioGene:iPhone/iPad</h3><p>BioGene is an information tool for biological research. Use BioGene to learn about gene function. Enter a gene symbol or gene name, for example "CDK4" or "cyclin dependent kinase 4" and BioGene will retrieve its gene function and references into its function (<a href="http://en.wikipedia.org/wiki/GeneRIF" target="_blank" title="GeneRIF">GeneRIF</a>).</p><ul>
<li>BioGene was produced in affiliation with the Computational Biology Center at <a href="http://maps.google.com/maps?ll=40.764096,-73.956842&amp;spn=0.01,0.01&amp;q=40.764096,-73.956842%20%28Memorial%20Sloan%E2%80%93Kettering%20Cancer%20Center%29&amp;t=h" target="_blank" title="Memorial Sloan&ndash;Kettering Cancer Center">Memorial Sloan-Kettering Cancer Center</a> with primary information from Entrez Gene at the <a href="http://maps.google.com/maps?ll=38.994994,-77.099339&amp;spn=0.01,0.01&amp;q=38.994994,-77.099339%20%28National%20Center%20for%20Biotechnology%20Information%29&amp;t=h" target="_blank" title="National Center for Biotechnology Information">NCBI</a>.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/biogene/id333180084?mt=8" target="_blank" title="https://itunes.apple.com/us/app/biogene/id333180084?mt=8"><strong>https://itunes.apple.com/us/app/biogene/id333180084?mt=8</strong></a></p><h3>Mentha - the interactome browser: Android</h3><p>About: mentha - the interactome browser, is a project that offers protein-protein physical/enzymatic interaction information from various sources. For more details about mentha, visit mentha's website. This client application is an independent project. This application is designed to allow you to search proteins on the go.</p><h4><strong>Key features (Also in website):</strong></h4><ul>
<li>Search proteins by <a href="http://en.wikipedia.org/wiki/UniProt" target="_blank" title="UniProt">UniProt</a> IDs, gene name or keywords</li>
<li>Collect proteins from different queries.</li>
<li>Spot common interactors in clusters.</li>
<li>Easily distinguish between proteins from Homo sapiens and other organisms (Yellow rounded rectangles)</li>
<li>Click on edges(links) to get scientific evidence.</li>
<li>Click on proteins to see descriptions.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en"><strong>https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en</strong></a></p><h3>GeneIndex: iPhone/iPad</h3><p>GeneIndex quickly provides information about genes from various sources. It also includes a RSS reader for journal feeds as well as a PubMed viewer.</p><h4><strong>Key Features:</strong></h4><ul>
<li>Look up genes by symbol or description.</li>
<li>Gene indexes for many mammals, plants, invertebrates, and bacteria.</li>
<li>Link to gene info on websites.</li>
<li>Download files for offline use. (.pdf, .mp3, .m4v, .doc, .ppt, .xls )</li>
<li>transfer files via open in, email, or iTunes file sharing</li>
<li>View RSS feeds for journals</li>
<li>Query GeneRIF interactions, COSMIC mutations, and CNV data for cell lines.</li>
<li>Does not require a network connection for local databases.</li>
<li>View and search PubMed in table view.</li>
</ul><p><br /> GeneIndex provides a convenient and portable way to lookup gene symbols while at a seminar, conference, or lab meeting. Genes are linked to common life science websites such as NCBI, COSMIC, KEGG, PubMed, SymAtlas, UCSC genome browser, Pathway Commons, Genatlas, Wikipedia, HUGO, and OMIM. GeneRIF gene interactions can also be queried.</p><ul>
<li>Keep current on the scientific literature. GeneIndex includes a RSS reader and web browser for browsing popular journals like Nature, Science, and Cell. You can also add your own RSS feeds. PDFs and podcasts can be saved as files that you can view on the device or email as attachments.</li>
<li>Examine the status of genes in common cell lines. A subset of COSMIC containing cell lines can be queried for mutations. Copy Number Variation (CNV) plots from cell lines profiled by GSK and Sanger are also linked to genes.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/geneindex/id319769866?mt=8" target="_blank" title="https://itunes.apple.com/us/app/geneindex/id319769866?mt=8"><strong>https://itunes.apple.com/us/app/geneindex/id319769866?mt=8</strong></a></p><h3>Genome Voyager: iPad</h3><p>Gain first hand experience identifying the genomic basis of disease by analyzing cases with whole genome sequencing data that have been published for research and learning purposes.</p><ul>
<li>Visualize whole human genome sequencing data including small variations, copy number variations (CNVs), and loss of heterozygosity (LOH) events</li>
<li>Quickly find variants of interest by filtering variants based on associated genes, functional impact, allele frequency in data sets, and cross-references with various genomic databases.</li>
<li>Collaborate on variant assessments with other researchers and academics to improve knowledge of both pathogenic and benign variants. <br /> To use Genome Voyager, users must join Genome Voyager&rsquo;s community of researchers and academics. Visit <strong>http://voyager.completegenomics.com to signup.</strong></li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8" target="_blank" title="https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8"><strong>https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8</strong></a></p><h3>YeastGenome: iPhone/iPad</h3><p>Use YeastGenome to quickly find fundamental information about Saccharomyces cerevisae genes and chromosomal features. Search gene names, gene descriptions or browse the database to find information about your favorite gene, as well as more detailed information such as Gene Ontology, mutant phenotype, and protein and genetic interaction data. <br /> YeastGenome contains the latest from the Saccharomyces Genome Database (www.yeastgenome.org) in an on bound app database. As more detailed information is presented the app switches to web services access to SGD, and then for even more details provides complete information via hyperlinks to the appropriate SGD database pages.</p><h4><strong>Key features:</strong></h4><ul>
<li>Search using gene name or keywords</li>
<li>Browse by feature type</li>
<li>Save your favorite features</li>
<li>Can be used in airplane mode</li>
<li>Email information about features to collaborators</li>
</ul><h4><strong>What's New in Version 1.8.1</strong></h4><ul>
<li>This update is required to provide continued functionality. Some of the data provided by this app accesses the SGD service using a method that is changing in May 2013. This version provides changes to allow access to continue. The on board database of yeast gene information has also been updated to March 2013.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8" target="_blank" title="https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8"><strong>https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8</strong></a></p><h3>SNPdbe: iPhone/iPad</h3><p>SNPdbe &mdash; SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from &gt;2600 organisms; &lsquo;human&rsquo; being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt.</p><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8" target="_blank" title="https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8"><strong>https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8</strong></a></p><h3>SimGene: iPhone/iPad / Android</h3><h4><strong>SimGene: for iPhone/iPad </strong></h4><p>SimGene is an iPhone/iPad/iPod touch application designed for molecular biologists, bioinformaticians and medical researchers. The application interfaces with Simbiot, Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations and many other databases to retrieve up-to-date annotation information for over 30 species, based on gene symbol search. The application provides gene and transcript cross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene also contains an integrated genome browser with information on genes, transcripts, exons and SNPs.</p><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/simgene/id427772349?mt=8" target="_blank" title="https://itunes.apple.com/us/app/simgene/id427772349?mt=8"><strong>https://itunes.apple.com/us/app/simgene/id427772349?mt=8</strong></a></p><h4><strong>SimGene: for Android</strong></h4><p>bioinformaticians and medical researchers. The application interfaces with Simbiot,Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations andmany other databases to retrieve up-to-date annotation information for over 30species, based on gene symbol search. The application provides gene and transcriptcross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene alsocontains an integrated genome browser with information on genes, transcripts,exons and SNPs.</p><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=com.japanbioinformatics.simgene&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=com.japanbioinformatics.simgene&amp;hl=en"><strong>https://play.google.com/store/apps/details?</strong></a></p><h3>TimeTree: iPhone/iPad</h3><p>TimeTree is a public knowledge-base for information on the evolutionary timescale of life. This application allows easy exploration of the thousands of divergence times among organisms in the scientific literature. A tree-based (hierarchical) system is used to identify all published molecular time estimates bearing on the divergence of two chosen organisms, such as species, compute summary statistics, and present the results. Names of two taxa to be compared are entered in the search window and the results are presented on a set of self-explanatory tabs.</p><ul>
<li>TimeTree 3.0 was released September 27, 2011 with new data from 1209 studies including 25342 time nodes. We will be adding more data in the future as it comes in from researchers.</li>
<li>TimeTree is jointly directed by Blair Hedges (Pennsylvania State University) and Sudhir Kumar (Arizona State University). This project has been supported, in part, by grants from the National Science Foundation, National Institutes of Health, NASA Astrobiology Institute, and Science Foundation of Arizona.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/timetree/id372842500?mt=8" target="_blank" title="https://itunes.apple.com/us/app/timetree/id372842500?mt=8"><strong>https://itunes.apple.com/us/app/timetree/id372842500?mt=8</strong></a></p><h3><strong>GeneGroove: iPhone/iPad </strong></h3><p>GeneGroove is the first application to create a music melody from DTC-Genomics data. If you own 23andMe (Mountain View, CA) personal genomic results, GeneGroove will create for you a unique melody intimately based on your 23andMe genome informations. The music in you.</p><ul>
<li>After uploading your 23andMe raw data onto your iPhone via iTunes, GeneGroove will analyze your genome informations and generate a unique identifier key. This key, called the GeNumber, will embed the uniqueness of your genome data while keeping your privacy safe, and will be used by GeneGroove to generate your music melody.</li>
<li>The GeNumber doesn't contain anymore genomic information but it is based on your genome and it is unique, it is yours. It will be used in upcoming Portable Genomics applications to mix and remix music, manipulate sounds and share your art with your friends and family.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/genegroove/id492247404?mt=8" target="_blank" title="https://itunes.apple.com/us/app/genegroove/id492247404?mt=8"><strong>https://itunes.apple.com/us/app/genegroove/id492247404?mt=8</strong></a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39213/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Tue, 02 Apr 2019 21:54:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39213/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14899/post-doc-positions-at-the-institute-of-evolution-university-of-haifa-haifa-israel</guid>
  <pubDate>Thu, 04 Sep 2014 03:59:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Post-Doc Positions at the Institute of Evolution, University of Haifa, Haifa, Israel]]></title>
  <description><![CDATA[
<p>We are looking for independent, motivated, diligent, laborious, dedicated Bioinformaticians as post-doctorate fellows for a project aimed at revealing the mechanisms of cancer-resistance and anti-cancer activity of the hypoxia-tolerant subterranean, blind mole-rat, Spalax along its underground evolutionary adaptations. Our project has captured the interest of the scientific community and we have ample financial support for the studies. Generous fellowships ($30K to $40K according to qualifications and performance) are available, immediately, for Post-Docs experts in bioinformatics with a background of good understanding biological questions. That is that can independently handle raw output data of RNA-seq / miR seq/ Genomic, analyze it and can interpret intelligently the relevant biological background. Outstanding candidates for PhD experienced in Bioinformatics will also be considered. Familiarity with cancer research is an advantage. Experience of writing manuscripts for publication and a publication record in relevant journals are expected. English skills both oral and written are required. American, Western-European or Israeli education is a significant benefit. </p>

<p>Our present objectives is to identify and isolate the substances secreted by Spalax cells, resolve with which components they interact that are active only on cancer cells, in order to unravel the biological mechanisms and pathways that evolved in Spalax cell machinery and ultimately lead to the death of cancer-cells. The study could attest to be a breakthrough in cancer research, using the long lived, hypoxia- and cancer-tolerant Spalax as a significant biological resource for biomedical research that hopefully could open new horizons in treatment and prevention of cancer in humans. </p>

<p>Contact: The applications should be submitted, together with extended CV and bibliography, summary of past accomplishments, and contact information of 3 referees, to Prof of Research Aaron Avivi (aaron@research.haifa.ac.il) AND Dr. Imad Shams (imadshams@gmail.com). (http://bit.ly/1lywShk) aaron@research.haifa.ac.il </p>

<p>More at http://evolution.haifa.ac.il/index.php/29-people/personal-websites/77-personal-site-avivi</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Fri, 24 Jan 2020 04:09:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p><span>MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from&nbsp;</span><code>https://github.com/linzhi2013/MitoZ</code><span>.</span></p>
<p><span><a href="https://academic.oup.com/nar/article/47/11/e63/5377471">https://academic.oup.com/nar/article/47/11/e63/5377471</a></span></p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/15030/software-engineercomputational-biologist-equinome-ltd-dublin-ireland</guid>
  <pubDate>Thu, 04 Sep 2014 19:21:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[Software engineer/Computational Biologist - Equinome Ltd., Dublin, Ireland]]></title>
  <description><![CDATA[
<p>Equinome (www.equinome.com) is the world leader in the research and<br />development of state-of-the-art novel genomic tools to inform the breeding,<br />selection and training of Thoroughbred racehorses. Since its launch in 2010,<br />Equinome has successfully commercialised three performance-related genetic<br />tests, with a pipeline of further genetic tests in development. We work with<br />many of the world's leading racehorse trainers and breeders in Europe,<br />Australasia, USA and South Africa. The company has been featured on CNN,<br />Bloomberg, RTE, BBC, The Guardian, Discovery Channel and Channel 4, among<br />others.</p>

<p>The Role</p>

<p>We are looking for a Software Engineer - Computational Biologist with 3+<br />years' experience in a similar role to design and implement a backend system<br />to support an online individualised genomics interface. This position is a<br />great opportunity for an ambitious, self-motivated individual to work in a<br />demanding, challenging and interesting role.</p>

<p>Position Description:<br />. Participate in planning, design, and implementation of Equinome back<br />end systems and technologies.<br />. Implement interfaces and management tools for back end services.<br />. Manage, analyse, interpret and visualise large genomics data sets.<br />. Work closely with scientific team to develop new features and<br />application enhancements<br />. Design, develop and manage a genomics research database.</p>

<p>Qualification/Experience:<br />. Minimum MSc in Computer Science, Genetics, Bioinformatics or in a<br />related field (A Ph.D qualification would be an advantage).<br />. Proven 3+ years of experience in similar role.<br />. Highly proficient in Python, SQL, MySQL.<br />. Excellent knowledge of mammalian genomics, bioinformatics and<br />statistical/population genetics.<br />. Hands-on experience working with large data sets.<br />. Experience with front-end technologies (HTML/CSS/Javascript) an<br />advantage.<br />. Experience in rapid web application development: e.g. Django.<br />. Knowledge or experience of Unix Scripting and R statistical<br />programming language would be an advantage.<br />. Ability to work with minimum supervision to deliver high-quality<br />code on time.<br />. Fluency in English and good written and communication skills.<br />. Meticulous attention to detail.</p>

<p>Applications should be submitted before Friday, 26 September 2014 using the<br />following link:<br />http://bit.ly/WgbhxS</p>

<p>Note: Full information and application procedure is available at this link:<br />http://bit.ly/WgbhxS</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41009/genomics-public-data-links</guid>
	<pubDate>Thu, 13 Feb 2020 00:20:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41009/genomics-public-data-links</link>
	<title><![CDATA[genomics public data links !]]></title>
	<description><![CDATA[<p>List of publically available databases on google server.</p>
<p>More at <a href="https://software.broadinstitute.org/gatk/download/bundle">https://software.broadinstitute.org/gatk/download/bundle</a></p>
<p><a href="ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/">ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/</a>.</p>
<p><a href="ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/">ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/</a></p><p>Address of the bookmark: <a href="https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1" rel="nofollow">https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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