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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43799?offset=160</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41948/predict-gene-ontology-with-sequences</guid>
	<pubDate>Wed, 08 Jul 2020 04:59:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41948/predict-gene-ontology-with-sequences</link>
	<title><![CDATA[Predict Gene Ontology with sequences !]]></title>
	<description><![CDATA[<p><strong>PANNZER</strong>&nbsp;(Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.</p>
<p>PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use&nbsp;<a href="http://ekhidna2.biocenter.helsinki.fi/AAI/">AAI-profiler</a>&nbsp;to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.</p>
<p>http://ekhidna2.biocenter.helsinki.fi/sanspanz/</p>
<p>IterPro is for the beginners</p>
<p><a href="https://www.ebi.ac.uk/interpro/">h</a><a href="https://www.ebi.ac.uk/interpro/">ttps://www.ebi.ac.uk/interpro/</a></p>
<p>You can find other comparative info at&nbsp;<a href="https://academic.oup.com/view-large/118391389">https://academic.oup.com/view-large/118391389</a></p><p>Address of the bookmark: <a href="http://ekhidna2.biocenter.helsinki.fi/sanspanz/" rel="nofollow">http://ekhidna2.biocenter.helsinki.fi/sanspanz/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</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/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</guid>
	<pubDate>Sun, 09 Dec 2018 19:06:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</link>
	<title><![CDATA[DECIPHER; a software toolset for deciphering and managing biological sequences efficiently using the R]]></title>
	<description><![CDATA[<p><span>DECIPHER is a software toolset that can be used for deciphering and managing biological sequences efficiently using the&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;programming language. The&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;package is distributed as platform independent source code under the&nbsp;</span><a href="http://www.gnu.org/copyleft/gpl.html">GPL version 3 license</a><span>. Some functionality of the program is accessible online through web tools.</span></p>
<p><span style="font-size: medium; text-align: justify;">&nbsp;</span></p><p>Address of the bookmark: <a href="http://www2.decipher.codes/" rel="nofollow">http://www2.decipher.codes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39867/gepard-allows-the-calculation-of-dotplots-even-for-large-sequences-like-chromosomes-or-bacterial-genomes</guid>
	<pubDate>Mon, 26 Aug 2019 11:38:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39867/gepard-allows-the-calculation-of-dotplots-even-for-large-sequences-like-chromosomes-or-bacterial-genomes</link>
	<title><![CDATA[Gepard: allows the calculation of dotplots even for large sequences like chromosomes or bacterial genomes]]></title>
	<description><![CDATA[<p>Gepard (German: "cheetah", Backronym for "GEnome PAir - Rapid Dotter") allows the calculation of dotplots even for large sequences like chromosomes or bacterial genomes. Reference: Krumsiek J, Arnold R, Rattei T. Gepard: A rapid and sensitive tool for creating dotplots on genome scale. Bioinformatics 2007; 23(8): 1026-8. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17309896" target="_blank">17309896</a></p>
<p><a href="http://cube.univie.ac.at/gepard">http://cube.univie.ac.at/gepard</a></p><p>Address of the bookmark: <a href="https://github.com/univieCUBE/gepard" rel="nofollow">https://github.com/univieCUBE/gepard</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41602/nucdiff-in-depth-characterization-and-annotation-of-differences-between-two-sets-of-dna-sequences</guid>
	<pubDate>Tue, 05 May 2020 10:35:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41602/nucdiff-in-depth-characterization-and-annotation-of-differences-between-two-sets-of-dna-sequences</link>
	<title><![CDATA[NucDiff: In-depth characterization and annotation of differences between two sets of DNA sequences]]></title>
	<description><![CDATA[<p>NucDiff locates and categorizes differences between two closely related nucleotide sequences. It is able to deal with very fragmented genomes, structural rearrangements and various local differences. These features make NucDiff to be perfectly suitable to compare assemblies with each other or with available reference genomes.</p>
<p>NucDiff provides information about the types of differences and their locations. It is possible to upload the results into genome browser for visualization and further inspection. It was written in Python and uses the NUCmer package from MUMmer[1] for sequence comparison.</p>
<p><br><br></p><p>Address of the bookmark: <a href="https://github.com/uio-cels/NucDiff" rel="nofollow">https://github.com/uio-cels/NucDiff</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</guid>
	<pubDate>Thu, 09 Mar 2023 02:56:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</link>
	<title><![CDATA[Steps to find palindrome in genomes !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Palindromes are sequences of nucleotides that read the same backward as forward. They can be present in genomes and have various biological functions. Here are some methods for discovering palindromes in genomes:</p><ol>
<li>
<p>Direct sequence search: One of the simplest ways to discover palindromes is to search the genome sequence directly for palindromic sequences using pattern matching tools, such as regular expressions or string algorithms. This approach can be useful for discovering simple palindromes, but may miss more complex palindromic structures.</p>
</li>
<li>
<p>Dot plot analysis: Dot plot analysis is a graphical method that can be used to identify palindromic regions in a genome. It involves plotting the genome sequence against itself and examining the diagonal patterns that emerge. Palindromic regions will appear as symmetrical patterns along the diagonal.</p>
</li>
<li>
<p>Restriction enzyme analysis: Some restriction enzymes, such as EcoRI and HindIII, recognize palindromic sequences and cleave DNA at these sites. By digesting the genome with these enzymes and examining the resulting fragments, palindromic regions can be identified.</p>
</li>
<li>
<p>Next-generation sequencing: High-throughput sequencing technologies, such as PacBio and Oxford Nanopore, can generate long reads that can span entire palindromic regions. By mapping these reads to the genome, palindromic regions can be identified and characterized.</p>
</li>
<li>
<p>Comparative genomics: Comparing the genomes of related species can also reveal palindromic regions that are conserved across evolutionarily divergent lineages. This approach can help identify functional palindromes that are under selective pressure.</p>
</li>
</ol><p>Overall, the discovery of palindromic sequences in genomes can be accomplished using a variety of methods, each with their own advantages and limitations. A combination of these methods can provide a comprehensive understanding of the palindromic landscape of a genome.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</guid>
	<pubDate>Sun, 31 Aug 2025 06:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</link>
	<title><![CDATA[Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences]]></title>
	<description><![CDATA[<p><span>Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.</span></p><p>Address of the bookmark: <a href="https://github.com/MGXlab/Jaeger" rel="nofollow">https://github.com/MGXlab/Jaeger</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2759/dynamic-programming-alignment</guid>
	<pubDate>Thu, 22 Aug 2013 09:38:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2759/dynamic-programming-alignment</link>
	<title><![CDATA[Dynamic Programming Alignment]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/EWJnDMKBEv0" frameborder="0" allowfullscreen></iframe>lecture 9, Chem. C100, Spring 2013, UCLA]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</guid>
	<pubDate>Fri, 13 May 2016 05:25:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</link>
	<title><![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]></title>
	<description><![CDATA[<p>Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.<br> <br> Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs. <br> <br> You can find the manual <a href="http://satsuma.sourceforge.net/manual.html">here</a>.<br> Download the latest source code from <a href="https://sourceforge.net/projects/satsuma/">here.</a><br> Stable versions can also be downloaded from the <a href="https://www.broadinstitute.org/science/programs/genome-biology/spines">Broad Institute's</a> web site.<br> <br> An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is <a href="http://satsuma.sourceforge.net/faq.html">here</a>.<br> <br> If you use Satsuma in your research, please cite:<br> <a href="http://bioinformatics.oxfordjournals.org/content/26/9/1145.long">Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alf&ouml;ldi, J., Di Palma, F., &amp; Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51</a>.</p>
<p><strong>Tutorial at http://evomics.org/learning/genomics/satsuma/</strong></p><p>Address of the bookmark: <a href="http://satsuma.sourceforge.net/" rel="nofollow">http://satsuma.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30555/yaha</guid>
	<pubDate>Fri, 20 Jan 2017 05:38:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30555/yaha</link>
	<title><![CDATA[YAHA]]></title>
	<description><![CDATA[<p>YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.</p>
<p><strong>Availability:</strong> YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from <a href="http://faculty.virginia.edu/irahall/YAHA" target="pmc_ext">http://faculty.virginia.edu/irahall/YAHA</a>.</p>
<p><strong>Contact:</strong></p>
<p>http://genome.wustl.edu/people/groups/detail/hall-lab/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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