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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37737?offset=160</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/14036/introduction-to-programming-write-short-programs-that-generate-graphics-and-animation</guid>
	<pubDate>Thu, 14 Aug 2014 23:29:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/14036/introduction-to-programming-write-short-programs-that-generate-graphics-and-animation</link>
	<title><![CDATA[Introduction to programming. Write short programs that generate graphics and animation.]]></title>
	<description><![CDATA[<p>Introduction to programming. Write short programs that generate graphics and animation.</p><p>http://funprogramming.org/</p>]]></description>
	<dc:creator>Ram Yash Pal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38501/fgenesh-program-for-predicting-multiple-genes-in-genomic-dna-sequences</guid>
	<pubDate>Thu, 20 Dec 2018 11:55:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38501/fgenesh-program-for-predicting-multiple-genes-in-genomic-dna-sequences</link>
	<title><![CDATA[FGENESH - Program for predicting multiple genes in genomic DNA sequences]]></title>
	<description><![CDATA[<p>FGENESH is the fastest (50-100 times faster than GenScan) and most accurate gene finder available - see the figure and the table below. In recent rice genome sequencing projects, it was cited "the most successful (gene finding) program (Yu&nbsp;<em>et al</em>. (2002) Science 296:79) and was used to produce 87% of all high-evidence predicted genes (Goff&nbsp;<em>et al</em>. (2002) Science 296:79).</p><p>Address of the bookmark: <a href="http://www.softberry.com/berry.phtml?topic=fgenesh&amp;group=help&amp;subgroup=gfind" rel="nofollow">http://www.softberry.com/berry.phtml?topic=fgenesh&amp;group=help&amp;subgroup=gfind</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33223/tbl2asn-a-command-line-program-that-automates-the-creation-of-sequence-records-for-submission-to-genbank</guid>
	<pubDate>Mon, 29 May 2017 07:37:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33223/tbl2asn-a-command-line-program-that-automates-the-creation-of-sequence-records-for-submission-to-genbank</link>
	<title><![CDATA[Tbl2asn: a command-line program that automates the creation of sequence records for submission to GenBank]]></title>
	<description><![CDATA[<p>Tbl2asn is a command-line program that automates the creation of sequence records for submission to GenBank. It uses many of the same functions as Sequin but is driven generally by data files. Tbl2asn generates .sqn files for submission to GenBank. Additional manual editing is not required before submission.</p>
<p>Tbl2asn is available by anonymous&nbsp;<a href="ftp://ftp.ncbi.nih.gov/toolbox/ncbi_tools/converters/by_program/tbl2asn/">FTP</a>. Copy the right version for your platform, then uncompress the file, rename it to "tbl2asn", and set the permissions, as necessary for the platform.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genbank/tbl2asn2/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genbank/tbl2asn2/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36830/crossmap-a-program-for-convenient-conversion-of-genome-coordinates</guid>
	<pubDate>Thu, 31 May 2018 06:00:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36830/crossmap-a-program-for-convenient-conversion-of-genome-coordinates</link>
	<title><![CDATA[CrossMap: a program for convenient conversion of genome coordinates]]></title>
	<description><![CDATA[CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) &lt;&gt; hg19 (GRCh37), Mouse mm9 (MGSCv37) &lt;&gt; mm10 (GRCm38)).

It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

CrossMap is designed to liftover genome coordinates between assemblies. 

It’s not a program for aligning sequences to reference genome.

We do not recommend using CrossMap to convert genome coordinates between species.<p>Address of the bookmark: <a href="http://crossmap.sourceforge.net" rel="nofollow">http://crossmap.sourceforge.net</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38623/kallisto-a-program-for-quantifying-abundances-of-transcripts-from-bulk-and-single-cell-rna-seq-data</guid>
	<pubDate>Mon, 07 Jan 2019 10:35:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38623/kallisto-a-program-for-quantifying-abundances-of-transcripts-from-bulk-and-single-cell-rna-seq-data</link>
	<title><![CDATA[kallisto: a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data]]></title>
	<description><![CDATA[<p><strong>kallisto</strong>&nbsp;is a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of&nbsp;<em>pseudoalignment</em>&nbsp;for rapidly determining the compatibility of reads with targets, without the need for alignment. On benchmarks with standard RNA-Seq data,&nbsp;<strong>kallisto</strong>&nbsp;can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build. Pseudoalignment of reads preserves the key information needed for quantification, and&nbsp;<strong>kallisto</strong>&nbsp;is therefore not only fast, but also as accurate as existing quantification tools. In fact, because the pseudoalignment procedure is robust to errors in the reads, in many benchmarks&nbsp;<strong>kallisto</strong>&nbsp;significantly outperforms existing tools.&nbsp;<strong>kallisto</strong>&nbsp;is described in detail in:</p>
<p>Nicolas L Bray, Harold Pimentel, P&aacute;ll Melsted and Lior Pachter,&nbsp;<a href="http://www.nature.com/nbt/journal/v34/n5/full/nbt.3519.html">Near-optimal probabilistic RNA-seq quantification</a>, Nature Biotechnology&nbsp;<strong>34</strong>, 525&ndash;527 (2016), doi:10.1038/nbt.3519</p><p>Address of the bookmark: <a href="https://pachterlab.github.io/kallisto/about" rel="nofollow">https://pachterlab.github.io/kallisto/about</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39837/cactus-a-reference-free-whole-genome-multiple-alignment-program</guid>
	<pubDate>Mon, 12 Aug 2019 07:52:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39837/cactus-a-reference-free-whole-genome-multiple-alignment-program</link>
	<title><![CDATA[Cactus: a reference-free whole-genome multiple alignment program]]></title>
	<description><![CDATA[<p>Cactus is a reference-free whole-genome multiple alignment program. The principal algorithms are described here:&nbsp;<a href="https://doi.org/10.1101/gr.123356.111">https://doi.org/10.1101/gr.123356.111</a></p>
<p><span>Cactus uses substantial resources. For primate-sized genomes (3 gigabases each), you should expect Cactus to use approximately 120 CPU-days of compute per genome, with about 120 GB of RAM used at peak. The requirements scale roughly quadratically, so aligning two 1-megabase bacterial genomes takes only 1.5 CPU-hours and 14 GB RAM.</span>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/ComparativeGenomicsToolkit/cactus" rel="nofollow">https://github.com/ComparativeGenomicsToolkit/cactus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41872/autodock-vina-an-open-source-program-for-doing-molecular-docking</guid>
	<pubDate>Sat, 13 Jun 2020 07:55:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41872/autodock-vina-an-open-source-program-for-doing-molecular-docking</link>
	<title><![CDATA[AutoDock Vina: an open-source program for doing molecular docking.]]></title>
	<description><![CDATA[<p><span>AutoDock Vina is an open-source program for doing&nbsp;</span><a href="http://en.wikipedia.org/wiki/Docking_(molecular)">molecular docking</a><span>. It was designed and implemented by&nbsp;</span><a href="http://olegtrott.com/">Dr. Oleg Trott</a><span>&nbsp;in the Molecular Graphics Lab at The Scripps Research Institute.</span>&nbsp;It is especially effective for protein-ligand docking. AutoDock 4 is available under the GNU General Public License. AutoDock is one of the most cited docking software applications in the research community.</p>
<p><img src="http://vina.scripps.edu/img/accuracy.png" width="352" height="264" alt="image" style="border: 0px;"></p>
<p><a href="http://vina.scripps.edu/">http://vina.scripps.edu/</a></p><p>Address of the bookmark: <a href="http://vina.scripps.edu/" rel="nofollow">http://vina.scripps.edu/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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