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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31566?offset=480</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7088/gabi</guid>
  <pubDate>Fri, 06 Dec 2013 16:43:01 -0600</pubDate>
  <link></link>
  <title><![CDATA[GABi]]></title>
  <description><![CDATA[
<p>GABi Research<br />The major researching fields defined as the GABi scope are described next:<br />    Sequence Analysis<br />    Protein Structure Prediction<br />    Comparative Genomics<br />    Functional Analysis of Residues on Protein Families<br />    Gene/Protein Networks<br />    Genome structure &amp; base composition<br />    Highthroughput data analysis from NGS</p>

<p>Lab Page http://gabi.cidbio.org/index/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8504/update-genome-workbench-2715-released</guid>
	<pubDate>Wed, 26 Feb 2014 16:12:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8504/update-genome-workbench-2715-released</link>
	<title><![CDATA[Update Genome Workbench 2.7.15 released]]></title>
	<description><![CDATA[<p>NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. With Genome Workbench, you can view data in publically available sequence databases at NCBI, and mix this data with your own private data.</p><p><img src="http://www.ncbi.nlm.nih.gov/core/assets/gbench/images/firstscreen_still.gif" alt="Introductory screen shot" style="border: 0px; border: 0px;"></p><p>Genome Workbench can display sequence data in many ways, including graphical sequence views, various alignment views, phylogenetic tree views, and tabular views of data. It can also align your private data to data in public databases, display your data in the context of public data, and retrieve BLAST results.</p><p>Genome Workbench is built on the NCBI C++ ToolKit and uses cross-platform APIs for graphics. It runs on your local machine, and is available for Windows 2000/XP, Linux, MacOS X, and various flavors of Unix.</p><p>NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. Genome Workbench was developed entirely in-house at NCBI and makes use of the NCBI C++ ToolKit. The C++ ToolKit provides a convenient and flexible cross-platform API for managing system internals, database connections, network sockets, and the NCBI data model. In addition, the C++ ToolKit provides the Object Manager, which abstracts handling of sequences and sequence-related objects.</p><p>&nbsp;New Features in Genome Workbench 2.7.15 <br /><br /></p><ul>
<li>Multiple Alignment View: implemented adaptive feature display when zooming in</li>
<li>Active Objects Inspector replaces Selection Inspector. New View should offer an improved selection context examination. See Using Active Objects Inspector tutorial for more details.</li>
<li>Binary packages for Linux OpenSUSE 13.1 are now available</li>
</ul><p><br />Bug Fixes and Improvements in Genome Workbench 2.7.15 <br /><br /></p><ul>
<li>Fixed major issue with OpenGL overlay/scrolling. Could cause crashes or view scrolling irregularities</li>
<li>Multiple Pane View: fixed crash on loading BLAST results</li>
<li>Graphical Sequence View: fixed crash on zooming in and out, related to SNP track</li>
<li>Graphical Sequence View: fixed Go To Position dialog to give better diagnostics in case of a user error</li>
<li>Graphical Sequence View: PDF export fixed rendering of Markers with commas in the name</li>
<li>Text View / Flat File: fixed Mac OS rendering issues</li>
<li>Text View / Flat File: performance optimization, extended capabilities of real-time rendering of molecules to tens of thousands</li>
<li>File Import: optimization improvement to speed up load of files containing multiple project items</li>
<li>File Import: remapping stage now shows accession.version and description of molecules, instead of plain GI numbers</li>
<li>Mac OS: improved tooltips for toolbar buttons</li>
<li>Phylogenetic Tree Builder Tool: improved diagnostics of errors</li>
<li>Multiple Alignment View: optimizations to avoid main GUI freezes</li>
<li>Open Dialog: removed duplicate elements in table of genomes (load Genome)</li>
<li>PDF export: fixed issue with XREF table errors</li>
<li>Tree View: fixed issues with showing Force Layout progress on Mac OS</li>
<li>Tree View: PDF export fixed issues for showing labels of collapsed nodes</li>
<li>Tree View: added an option to stop layout</li>
<li>Tree View: broadcasting mechanism fixed not to accumulate selected nodes</li>
</ul><p>Reference:</p><p>NCBI news</p><p>http://www.ncbi.nlm.nih.gov/tools/gbench/</p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40204/iitm-tokyo-tech-joint-symposium</guid>
	<pubDate>Thu, 24 Oct 2019 10:30:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40204/iitm-tokyo-tech-joint-symposium</link>
	<title><![CDATA[IITM-Tokyo Tech Joint Symposium]]></title>
	<description><![CDATA[<p>The IITM-Tokyo Tech Joint Symposium is a biannual international symposium held in Indian Institute of Technology Madras (IITM), India in collaboration with Tokyo Institute of Technology (Tokyo-Tech), Japan. During the symposium, experts in various domains of Bioinformatics gather from India and Japan under one roof to discuss and present their works. This provides an unique opportunity to the researchers and students to learn the frontiers and interact with eminent scientists in Bioinformatics. The 5th IITM - Tokyo Tech Joint Symposium titled "Current trends in Bioinformatics: Big data analysis, machine learning and drug design", will be held on 6th - 7th March 2020 in IITM, Chennai, India.</p><p>The symposium will focus on topics in the below mentioned areas.</p><p>Topics: Algorithms for biomolecular sequences / structures Bioinformatics databases and tools Protein function Structure based drug design Machine learning Deep learning Large scale data analysis Big Data NGS Analysis Protein interactions/network Molecular modelling/docking/screening Biomolecular structure and function More</p><p>Info: https://web.iitm.ac.in/bioinfo2/symposium2020/home</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</guid>
	<pubDate>Tue, 27 Oct 2020 19:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</link>
	<title><![CDATA[Frequent parameters for bioinformatics tools !]]></title>
	<description><![CDATA[<div><div>Third party executable parameters and options.</div><div>&nbsp;</div><div>Trimmomatic</div><div>&nbsp;</div><div>&ldquo;ILLUMINACLIP:...:2:30:10&rdquo;</div><div>&ldquo;LEADING:15&rdquo;</div><div>&ldquo;TRAILING:15&rdquo;</div><div>&ldquo;SLIDINGWINDOW:4:20&rdquo;</div><div>&ldquo;MINLEN:20&rdquo;</div><div>&ldquo;TOPHRED33&rdquo;</div><div>&nbsp;</div><div>Filtlong</div><div>--min_length 500</div><div>--min_mean_q 85</div><div>--min_window_q 65</div><div>&nbsp;</div><div>FastQ Screen</div><div>--aligner bowtie2' (bwa for PacBio)</div><div>--subset 1000 (for PacBio)</div><div>&nbsp;</div><div>SPAdes</div><div>--careful</div><div>--disable-gzip-output</div><div>--cov-cutoff auto</div><div>--phred-offset 33</div><div>&nbsp;</div><div>HGAP</div><div>Pbalign.task_options.min_accuracy: 70</div><div>Pbalign.task_options.no_split_subreads: false</div><div>Genomic_consensus.task_options.min_confidence: 40</div><div>falcon_ns.task_options.HGAP_GenomeLength_str:</div><div>6000000</div><div>Pbcoretools.task_options.read_length: 0</div><div>Genomic_consensus.task_options.use_score: 0</div><div>Pbalign.task_options.min_length: 50</div><div>Pbalign.task_options.algorithm_options: --minMatch 12</div><div>--bestn 10 --minPctSimilarity 70.0</div><div>Pbalign.task_options.hit_policy: randombest</div><div>Pbcoretools.task_options.other_filters: rq &gt;= 0.7</div><div>Pbalign.task_options.concordant: false</div><div>Genomic_consensus.task_options.min_coverage: 5</div><div>falcon_ns.task_options.HGAP_SeedCoverage_str: 30</div><div>falcon_ns.task_options.HGAP_AggressiveAsm_bool: false</div><div>Genomic_consensus.task_options.algorithm: best</div><div>falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1</div><div>Genomic_consensus.task_options.diploid: false</div><div>&nbsp;</div><div>MeDuSa</div><div>-random 100</div><div>&nbsp;</div><div>Prokka</div><div>--usegenus</div><div>--force</div><div>--addgenes</div><div>--rfam</div><div>--rawproduct</div><div>&nbsp;</div><div>cmsearch (taxonomy, 16S)</div><div>--rfam</div><div>--noali</div><div>&nbsp;</div><div>blastn (taxonomy, 16S)</div><div>-evalue 1E-10</div><div>&nbsp;</div><div>blastn (MLST)</div><div>-ungapped</div></div><div><div>-dust no</div><div>-evalue 1E-20</div><div>-word_size 32</div><div>-culling_limit 2</div><div>-perc_identity 95</div><div>&nbsp;</div><div>blastp (VF)</div><div>-culling_limit 2</div><div>&nbsp;</div><div>RGI (ABR)</div><div>--input_type contig</div><div>&nbsp;</div><div>bowtie2 (mapping)</div><div>--sensitive</div><div>&nbsp;</div><div>minimap2 (mapping)</div><div>-a</div><div>-x map-ont</div><div>&nbsp;</div><div>samtools mpileup (SNP&nbsp;detection)</div><div>-uRI</div><div>&nbsp;</div><div>bcftools call (SNP detection)</div><div>--variants-only</div><div>--skip-variants indels</div><div>--output-type v</div><div>--ploidy 1</div><div>-c</div><div>&nbsp;</div><div>SNPsift filter (SNP detection)</div><div>"( QUAL &gt;= 30 ) &amp; (( na FILTER ) | (FILTER = 'PASS')) &amp;</div><div>( DP &gt;= 20 ) &amp; ( MQ &gt;= 20 )"</div><div>&nbsp;</div><div>SNPeff ann (SNP detection)</div><div>-nodownload</div><div>-no-intron</div><div>-no-downstream</div><div>-no SPLICE_SITE_REGION</div><div>-upDownStreamLen 250</div><div>&nbsp;</div><div>bcftools consensus</div><div>(phylogenetic tree)</div><div>--haplotype 1</div><div>&nbsp;</div><div>fasttreemp</div><div>-nt</div><div>-boot 100</div><div>&nbsp;</div><div>roary</div><div>-e</div><div>-n</div><div>-cd 100</div><div>-g 100000</div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3917/the-story-of-you-encode-and-the-human-genome</guid>
	<pubDate>Sat, 24 Aug 2013 18:49:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3917/the-story-of-you-encode-and-the-human-genome</link>
	<title><![CDATA[The Story of You: ENCODE and the human genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/TwXXgEz9o4w" frameborder="0" allowfullscreen></iframe><p>Ever since a monk called Mendel started breeding pea plants we've been learning about our genomes. In 1953, Watson, Crick and Franklin described the structure of the molecule that makes up our genomes: the DNA double helix. Then, in 2001, scientists wrote down the entire 3-billion letter code contained in the average human genome. Now they're trying to interpret that code; to work out how it's used to make different types of cells and different people. The ENCODE project, as it's called, is the latest chapter in the story of you. To read the ENCODE research papers and more, visit http://www.nature.com/ENCODE</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</guid>
	<pubDate>Tue, 26 Dec 2017 22:23:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</link>
	<title><![CDATA[Magic-BLAST: a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome.]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</guid>
	<pubDate>Mon, 30 Apr 2018 04:38:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</link>
	<title><![CDATA[ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.]]></title>
	<description><![CDATA[<p><span>ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.&nbsp;</span></p>
<p><span>Detail paper at&nbsp;https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8</span></p><p>Address of the bookmark: <a href="https://github.com/VicugnaPacos/ALPACA" rel="nofollow">https://github.com/VicugnaPacos/ALPACA</a></p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37915/dna-nucleotide-counter</guid>
	<pubDate>Fri, 12 Oct 2018 04:37:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37915/dna-nucleotide-counter</link>
	<title><![CDATA[DNA Nucleotide Counter]]></title>
	<description><![CDATA[<p style="margin: 2px 5px 4px 6px; color: #000011; font-size: 12px; font-style: normal; font-weight: 400; text-align: justify;">DNA Nucleotide Counter is delivered in a DNA Baser package together with other free molecular biology tools.<span>&nbsp;</span><a href="http://www.dnabaser.com/download/biology-tools-package-download-count.html">Download</a><span>&nbsp;</span>the package and double click it. The programs inside the package will be extracted to the destination folder (specified by you). Go to the destination folder&nbsp;and double click the program you want to use.</p>
<p style="margin: 2px 5px 4px 6px; color: #000011; font-size: 12px; font-style: normal; font-weight: 400; text-align: justify;">It<span>&nbsp;</span><a href="http://www.dnabaser.com/download/install-anywhere.html">installs in any computer</a><span>&nbsp;</span>even if you don't have administrator rights!</p><p>Address of the bookmark: <a href="http://www.dnabaser.com/download/DNA-Counter/index.html" rel="nofollow">http://www.dnabaser.com/download/DNA-Counter/index.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12870/nuclear-dynamics-lab</guid>
  <pubDate>Thu, 17 Jul 2014 15:03:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nuclear Dynamics Lab]]></title>
  <description><![CDATA[
<p>Lab focus is to elucidate fundamental principles, new mechanisms, machineries and emergent properties that are involved in maintaining the genome and gene expression programmes for improvements in lifelong health and well-being for all.</p>

<p>More at http://www.babraham.ac.uk/our-research/nuclear-dynamics/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35883/arcs-scaffolding-genome-drafts-with-linked-reads</guid>
	<pubDate>Tue, 06 Mar 2018 16:35:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35883/arcs-scaffolding-genome-drafts-with-linked-reads</link>
	<title><![CDATA[ARCS: scaffolding genome drafts with linked reads]]></title>
	<description><![CDATA[<p><span>ARCS, an application that utilizes the barcoding information contained in linked reads to further organize draft genomes into highly contiguous assemblies. We show how the contiguity of an ABySS&nbsp;</span><em>H.sapiens</em><span>genome assembly can be increased over six-fold, using moderate coverage (25-fold) Chromium data. We expect ARCS to have broad utility in harnessing the barcoding information contained in linked read data for connecting high-quality sequences in genome assembly drafts.</span></p><p>Address of the bookmark: <a href="https://github.com/bcgsc/ARCS/" rel="nofollow">https://github.com/bcgsc/ARCS/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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