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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34931?offset=320</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</guid>
	<pubDate>Thu, 29 Jan 2015 05:31:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</link>
	<title><![CDATA[DNA Transcription (Advanced)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/SMtWvDbfHLo" frameborder="0" allowfullscreen></iframe><p>Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.</p>]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</guid>
	<pubDate>Mon, 06 Feb 2017 04:26:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</link>
	<title><![CDATA[FSA: Fast Statistical Alignment]]></title>
	<description><![CDATA[<p><span>FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz in&nbsp;</span><a href="http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-39.html">"Posterior Decoding Methods for Optimization and Control of Multiple Alignments</a><span>."</span></p>
<p>FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:</p>
<ul>
<li>FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.</li>
<li>FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.</li>
<li>FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.</li>
<li>The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and&nbsp;<a href="http://fsa.sourceforge.net/images/Suchard_SIV.fsa.mov">movie</a>&nbsp;at the top of the page).</li>
</ul>
<p><span>You can see more information on the&nbsp;</span><a href="http://fsa.sourceforge.net/FAQ.html">FAQ</a><span>.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://fsa.sourceforge.net/" rel="nofollow">http://fsa.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</guid>
	<pubDate>Thu, 04 May 2017 05:07:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</link>
	<title><![CDATA[Tetra-Nucleotide Analysis]]></title>
	<description><![CDATA[<p>A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride&nbsp;<em>et al.</em>&nbsp;(2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as&nbsp;<a href="https://chunlab.wordpress.com/orthoani/">OrthoANI</a>&nbsp;or&nbsp;16S rRNA phylogeny. However, TNA can be useful for&nbsp;phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling&nbsp;<em>et al.</em>, 2004). TNA is also fast enough that it can be&nbsp;used&nbsp;as a search engine against a large genome database.</p><p>Address of the bookmark: <a href="https://chunlab.wordpress.com/tetra-nucleotide-analysis/" rel="nofollow">https://chunlab.wordpress.com/tetra-nucleotide-analysis/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</guid>
	<pubDate>Wed, 06 Dec 2017 09:45:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</link>
	<title><![CDATA[ACANA: An accurate and consistent alignment tool for DNA sequences]]></title>
	<description><![CDATA[<p><span>ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.</span></p><p>Address of the bookmark: <a href="https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm" rel="nofollow">https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</guid>
	<pubDate>Tue, 15 May 2018 02:53:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</link>
	<title><![CDATA[TAREAN: A computational tool for identification and characterization of satellite DNA from unassembled short reads]]></title>
	<description><![CDATA[<p><strong>TA</strong>ndem&nbsp;<strong>RE</strong>peat&nbsp;<strong>AN</strong>alyzer -TAREAN &ndash; is a computational pipeline for&nbsp;<strong>unsupervised identification of satellite repeats</strong>&nbsp;from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their graph-based clustering. Resulting clusters, representing all types of repeats, are then examined for the presence of circular structures and putative satellite repeats are reported.</p>
<p><em><strong>How to use TAREAN</strong></em>:</p>
<ul>
<li>Install a local instance of the pipeline using its source code available from&nbsp;<a href="https://bitbucket.org/petrnovak/repex_tarean" target="_blank" title="TAREAN source code">bitbucket repository</a>.</li>
<li>Use&nbsp; public Galaxy-based server at&nbsp;<a href="https://repeatexplorer-elixir.cerit-sc.cz/" target="_blank">https://repeatexplorer-elixir.cerit-sc.cz/</a>. The server is provided in frame of the&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank">Elixir CZ project</a>&nbsp;and is maintained by&nbsp;<a href="https://www.cesnet.cz/" target="_blank">CESNET</a>&nbsp;and&nbsp;<a href="https://www.cerit-sc.cz/en/index.html" target="_blank">CERIT-SC</a>. Simple registration is required to use this service.</li>
</ul>
<p>Development of TAREAN was supported by&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank" title="ELIXIR-CZ">ELIXIR CZ</a>&nbsp;research infrastructure project (MEYS Grant No: LM2015047).</p>
<p><strong><em>References</em></strong></p>
<p>Novak, P., Avila Robledillo, L., Koblizkova, A., Vrbova, I., Neumann, P., Macas, J. (2017) &ndash;&nbsp;<a href="https://academic.oup.com/nar/article/3574061/" target="_blank">TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads</a>.&nbsp;<em>Nucleic Acids Res.</em>, doi:10.1093/nar/gkx257</p><p>Address of the bookmark: <a href="https://bitbucket.org/petrnovak/repex_tarean" rel="nofollow">https://bitbucket.org/petrnovak/repex_tarean</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37987/ropebwt2-incremental-construction-of-fm-index-for-dna-sequences</guid>
	<pubDate>Thu, 25 Oct 2018 04:48:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37987/ropebwt2-incremental-construction-of-fm-index-for-dna-sequences</link>
	<title><![CDATA[RopeBWT2: Incremental construction of FM-index for DNA sequences]]></title>
	<description><![CDATA[<p><span>RopeBWT2 is an tool for constructing the FM-index for a collection of DNA sequences. It works by incrementally inserting one or multiple sequences into an existing pseudo-BWT position by position, starting from the end of the sequences. This algorithm can be largely considered a mixture of&nbsp;</span><a href="http://dx.doi.org/10.1007/978-3-642-21458-5_20">BCR</a><span>&nbsp;and&nbsp;</span><a href="http://dfmi.sourceforge.net/">dynamic FM-index</a><span>. Nonetheless, ropeBWT2 is unique in that it may&nbsp;</span><em>implicitly</em><span>sort the input into reverse lexicographical order (RLO) or reverse-complement lexicographical order (RCLO) while building the index.</span></p><p>Address of the bookmark: <a href="https://github.com/lh3/ropebwt2" rel="nofollow">https://github.com/lh3/ropebwt2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44495/exrec-exclusion-of-recombined-dna</guid>
	<pubDate>Wed, 27 Mar 2024 20:48:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44495/exrec-exclusion-of-recombined-dna</link>
	<title><![CDATA[ExRec: Exclusion of Recombined DNA]]></title>
	<description><![CDATA[<p><span>ExRec (Exclusion of Recombined DNA) is a Python pipeline that implements the four-gamete test to filter out recombined DNA sites from up to thousands of DNA sequence loci. The pipeline consists of five standalone applications: the first two convert folders of NEXUS or PHYLIP files into the standard input file for the main program that conducts the four-gamete filtering procedures. The pipeline outputs recombination-filtered data in concatenated NEXUS and PHYLIP formats and a tab-delimited table containing descriptive statistics for all loci and the results. This software also allows the user to output the longest non-recombined sequence blocks from loci (current best practice) or randomly select non-recombined blocks from loci (a newer approach). Two other applications in the package convert the recombination-filtered data into single-locus NEXUS or PHYLIP files. The ExRec package can thus facilitate species delimitation, species tree, and historical demography studies by providing loci that better meet the no-recombination assumption in coalescent-based analyses.</span></p>
<p><span>Link to the article:&nbsp;</span><a href="https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad174/7455250?searchresult=1" target="_blank">https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad174/7455250?searchresult=1</a><br><br><span>Link to the software:</span><br><a href="https://github.com/Sammccarthypotter/ExRec" target="_blank">https://github.com/Sammccarthypotter/ExRec</a></p><p>Address of the bookmark: <a href="https://github.com/Sammccarthypotter/ExRec" rel="nofollow">https://github.com/Sammccarthypotter/ExRec</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/42693/dna-rna-meme</guid>
	<pubDate>Thu, 28 Jan 2021 11:23:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/42693/dna-rna-meme</link>
	<title><![CDATA[DNA RNA MEME]]></title>
	<description><![CDATA[<p>Explain the DNA and RNA with picture ...</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/42693" length="41627" type="image/jpeg" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27432/gkno</guid>
	<pubDate>Fri, 20 May 2016 18:56:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27432/gkno</link>
	<title><![CDATA[GKNO]]></title>
	<description><![CDATA[<p><span>gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.</span></p>
<p><span>http://gkno.me/how-to/install.html</span></p>
<p><span>http://gkno.me/software.html</span></p><p>Address of the bookmark: <a href="http://gkno.me/" rel="nofollow">http://gkno.me/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34394/tulip-the-uncorrected-long-read-itegration-pipeline</guid>
	<pubDate>Thu, 23 Nov 2017 09:30:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34394/tulip-the-uncorrected-long-read-itegration-pipeline</link>
	<title><![CDATA[TULIP - The Uncorrected Long read Itegration Pipeline]]></title>
	<description><![CDATA[<p>#Running TULIP (The Uncorrected Long-read Integration Process), version 0.4 late 2016 (European eel)</p>
<p>TULIP currently consists of to Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow.&nbsp;<br>Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures. Tulipbulb adds long read sequencing data to these.</p>
<p>&nbsp;</p>
<p>https://github.com/Generade-nl/TULIP</p><p>Address of the bookmark: <a href="https://github.com/Generade-nl/TULIP" rel="nofollow">https://github.com/Generade-nl/TULIP</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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