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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38445?offset=50</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43676/vcf2poptree-a-client-side-software-to-construct-population-phylogeny-from-genome-wide-snps</guid>
	<pubDate>Sat, 25 Dec 2021 00:13:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43676/vcf2poptree-a-client-side-software-to-construct-population-phylogeny-from-genome-wide-snps</link>
	<title><![CDATA[VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs]]></title>
	<description><![CDATA[<p>VCF2PopTree is a client-side software written in Javascript and it runs purely within the user&rsquo;s computer/browser.&nbsp; VCF2PopTree is compatible with all population browsers including Chrome, Opera, Edge and Firefox and works equally efficient in Mac, Windows and Linux (Ubuntu).&nbsp;</p>
<p>Furthermore, it displays the tree in a mobile phone (iPhone and Android) if the input file size is small.&nbsp; CITATION: Subramanian, S., Ramasamy, U. and Chen, D. (2019).&nbsp; VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs.&nbsp; Peer J. x:yy.</p><p>Address of the bookmark: <a href="https://github.com/sansubs/vcf2pop" rel="nofollow">https://github.com/sansubs/vcf2pop</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</guid>
	<pubDate>Wed, 13 Aug 2025 19:56:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</link>
	<title><![CDATA[dna2bit: an ultra-fast and accurate genomic distance estimation software]]></title>
	<description><![CDATA[<p dir="auto">dna2bit: an ultra-fast and accurate genomic distance estimation software</p>
<div dir="auto"><a href="https://github.com/lijuzeng/dna2bit#compilation"></a></div>
<p dir="auto">dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/lijuzeng/dna2bit" rel="nofollow">https://github.com/lijuzeng/dna2bit</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</guid>
	<pubDate>Fri, 08 Jun 2018 10:47:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</link>
	<title><![CDATA[HALC: High throughput algorithm for long read error correction]]></title>
	<description><![CDATA[HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach)

HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.<p>Address of the bookmark: <a href="https://github.com/lanl001/halc" rel="nofollow">https://github.com/lanl001/halc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38452/silix-implements-an-ultra-efficient-algorithm-for-the-clustering-of-homologous-sequences</guid>
	<pubDate>Wed, 12 Dec 2018 09:22:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38452/silix-implements-an-ultra-efficient-algorithm-for-the-clustering-of-homologous-sequences</link>
	<title><![CDATA[SiLiX: implements an ultra-efficient algorithm for the clustering of homologous sequences]]></title>
	<description><![CDATA[<p>The software package SiLiX implements<strong>&nbsp;an ultra-efficient algorithm for the clustering of homologous sequences</strong>, based on single transitive links (<em>single linkage</em>) with alignment coverage constraints.</p>
<p>SiLiX adopts a graph-theoretical framework to interpret similarity pairs as edges of a network. A very efficient algorithm, based on the&nbsp;<em>Disjoint Sets Data Structure</em>, allows the computation of sequence families with&nbsp;<strong>low time and space requirements</strong>.</p>
<p><strong>A parallel version</strong>&nbsp;of SiLiX, based on MPI, is also available in this package and has been proved to be scalable, so that its allows the study of&nbsp;<strong>very large datasets</strong>.</p>
<p>SiLiX is already included in the analysis pipeline for&nbsp;<a href="http://pbil.univ-lyon1.fr/databases/hogenom/acceuil.php">HOGENOM</a>.</p><p>Address of the bookmark: <a href="http://lbbe.univ-lyon1.fr/SiLiX?lang=fr" rel="nofollow">http://lbbe.univ-lyon1.fr/SiLiX?lang=fr</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</guid>
	<pubDate>Thu, 28 Aug 2025 02:56:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</link>
	<title><![CDATA[AlfaPang: alignment free algorithm for pangenome graph construction]]></title>
	<description><![CDATA[<p><span>AlfaPang constructs variation graphs, leveraging its alignment-free and reference-free approach, based solely on intrinsic sequence properties. This design allows AlfaPang's runtime and memory usage to scale linearly with the size of input sequences, enabling it to handle significantly larger genome sets compared to other methods.</span></p><p>Address of the bookmark: <a href="https://github.com/AdamCicherski/AlfaPang" rel="nofollow">https://github.com/AdamCicherski/AlfaPang</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38563/hecil-a-hybrid-error-correction-algorithm-for-long-reads-with-iterative-learning</guid>
	<pubDate>Tue, 01 Jan 2019 12:01:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38563/hecil-a-hybrid-error-correction-algorithm-for-long-reads-with-iterative-learning</link>
	<title><![CDATA[HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning]]></title>
	<description><![CDATA[<p><span>HECIL&mdash;Hybrid Error Correction with Iterative Learning&mdash;a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments.&nbsp;</span></p>
<p><span><span>HECIL&rsquo;s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.</span></span></p><p>Address of the bookmark: <a href="https://github.com/NDBL/HECIL" rel="nofollow">https://github.com/NDBL/HECIL</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36752/minmax-a-versatile-tool-for-calculating-and-comparing-synonymous-codon-usage-and-its-impact-on-protein-folding</guid>
	<pubDate>Thu, 24 May 2018 02:53:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36752/minmax-a-versatile-tool-for-calculating-and-comparing-synonymous-codon-usage-and-its-impact-on-protein-folding</link>
	<title><![CDATA[%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding.]]></title>
	<description><![CDATA[%MM calculates whether a given gene sequence encodes amino acids using the most common codons possible, the least common codons possible, or (most typically) some combination of these extremes. See our PLoS ONE paper for more details on how the %MinMax algorithm works. 

%MinMax results are averaged over an 18-codon sliding window; hence the result for "codon window = 1" is the average codon usage for codons 1-18, codon window 2 = codons 2-19, etc.<p>Address of the bookmark: <a href="http://www.codons.org/" rel="nofollow">http://www.codons.org/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/18653/genetic-code-amino-acid</guid>
	<pubDate>Sun, 26 Oct 2014 07:45:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/18653/genetic-code-amino-acid</link>
	<title><![CDATA[Genetic code - Amino Acid]]></title>
	<description><![CDATA[<p>The genetic code consists of 64 triplets of nucleotides. These triplets are called codons.With three exceptions, each codon encodes for one of the 20 amino acids used in the synthesis of proteins. That produces some redundancy in the code: most of the amino acids being encoded by more than one codon.</p><p>The image summarise all in one.</p><p>More at http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/C/Codons.html</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/18653" length="226605" type="image/jpeg" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36994/minimap2-a-versatile-pairwise-aligner-for-genomic-and-spliced-nucleotide-sequences</guid>
	<pubDate>Wed, 20 Jun 2018 07:55:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36994/minimap2-a-versatile-pairwise-aligner-for-genomic-and-spliced-nucleotide-sequences</link>
	<title><![CDATA[minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences]]></title>
	<description><![CDATA[git clone https://github.com/lh3/minimap2
cd minimap2 &amp;&amp; make
# long sequences against a reference genome
./minimap2 -a test/MT-human.fa test/MT-orang.fa &gt; test.sam
# create an index first and then map
./minimap2 -d MT-human.mmi test/MT-human.fa
./minimap2 -a MT-human.mmi test/MT-orang.fa &gt; test.sam
# use presets (no test data)
./minimap2 -ax map-pb ref.fa pacbio.fq.gz &gt; aln.sam       # PacBio genomic reads
./minimap2 -ax map-ont ref.fa ont.fq.gz &gt; aln.sam         # Oxford Nanopore genomic reads
./minimap2 -ax sr ref.fa read1.fa read2.fa &gt; aln.sam      # short genomic paired-end reads
./minimap2 -ax splice ref.fa rna-reads.fa &gt; aln.sam       # spliced long reads
./minimap2 -ax splice -k14 -uf ref.fa reads.fa &gt; aln.sam  # Nanopore Direct RNA-seq
./minimap2 -cx asm5 asm1.fa asm2.fa &gt; aln.paf             # intra-species asm-to-asm alignment
./minimap2 -x ava-pb reads.fa reads.fa &gt; overlaps.paf     # PacBio read overlap
./minimap2 -x ava-ont reads.fa reads.fa &gt; overlaps.paf    # Nanopore read overlap
# man page for detailed command line options
man ./minimap2.1<p>Address of the bookmark: <a href="https://github.com/lh3/minimap2" rel="nofollow">https://github.com/lh3/minimap2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43656/special-nucleotide-characters-symbols</guid>
	<pubDate>Thu, 16 Dec 2021 23:37:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43656/special-nucleotide-characters-symbols</link>
	<title><![CDATA[Special Nucleotide Characters / Symbols !]]></title>
	<description><![CDATA[<h2 style="text-align: center;">Nucleotide symbols</h2><table style="margin: auto;" width="95%" border="1" cellpadding="5">
<tbody>
<tr>
<td align="center">Nucleotide symbol</td>
<td align="center">Full Name</td>
</tr>
<tr>
<td align="center">A</td>
<td align="center">Adenine</td>
</tr>
<tr>
<td align="center">C</td>
<td align="center">Cytosine</td>
</tr>
<tr>
<td align="center">G</td>
<td align="center">Guanine</td>
</tr>
<tr>
<td align="center">T</td>
<td align="center">Thymine</td>
</tr>
<tr>
<td align="center">U</td>
<td align="center">Uracil</td>
</tr>
<tr>
<td align="center">R</td>
<td align="center">Guanine / Adenine (purine)</td>
</tr>
<tr>
<td align="center">Y</td>
<td align="center">Cytosine / Thymine (pyrimidine)</td>
</tr>
<tr>
<td align="center">K</td>
<td align="center">Guanine / Thymine</td>
</tr>
<tr>
<td align="center">M</td>
<td align="center">Adenine / Cytosine</td>
</tr>
<tr>
<td align="center">S</td>
<td align="center">Guanine / Cytosine</td>
</tr>
<tr>
<td align="center">W</td>
<td align="center">Adenine / Thymine</td>
</tr>
<tr>
<td align="center">B</td>
<td align="center">Guanine / Thymine / Cytosine</td>
</tr>
<tr>
<td align="center">D</td>
<td align="center">Guanine / Adenine / Thymine</td>
</tr>
<tr>
<td align="center">H</td>
<td align="center">Adenine / Cytosine / Thymine</td>
</tr>
<tr>
<td align="center">V</td>
<td align="center">Guanine / Cytosine / Adenine</td>
</tr>
<tr>
<td align="center">N</td>
<td align="center">Adenine / Guanine / Cytosine / Thymine</td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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