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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27696?offset=450</link>
	<atom:link href="https://bioinformaticsonline.com/related/27696?offset=450" rel="self" type="application/rss+xml" />
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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/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</guid>
	<pubDate>Thu, 14 Nov 2013 13:36:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</link>
	<title><![CDATA[Hidden Markov Models, Viterbi Algorithm, Markov Chain Exploration with script]]></title>
	<description><![CDATA[<p><strong>Hidden Markov Models, the Viterbi Algorithm, and CpG Islands (in VB6)</strong></p><p><strong>Problem :</strong></p><p>The CG island is a stretch of DNA (usually longer than 200 bases) in which the frequency of the CG sequence is higher than other regions. It is also called the CpG island, where "p" simply indicates that "C" and "G" are connected by a phosphodiester bond.<br /><br />CpG islands are often located around the promoters of housekeeping genes (which are essential for general cell functions) or other genes frequently expressed in a cell. At these locations, the CG sequence is not methylated. By contrast, the CG sequences in inactive genes are usually methylated to suppress their expression. The methylated cytosine may be converted to thymine by accidental deamination. Unlike the cytosine to uracil mutation which is efficiently repaired, the cytosine to thymine mutation can be corrected only by the mismatch repair which is very inefficient. Hence, over evolutionary time scales, the methylated CG sequence will be converted to the TG sequence.</p><p>Find step wise explanationand implementation steps at <a href="http://dna.cs.byu.edu/bio465/Labs/hmm.shtml">http://dna.cs.byu.edu/bio465/Labs/hmm.shtml</a></p><p>Source code with explanation <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/</a></p><p>Fore detail understanding of HMM read this excellent tutorial <a href="http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf">http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf</a></p><p>Viterbi Algo at <a href="http://en.wikipedia.org/wiki/Viterbi_path">http://en.wikipedia.org/wiki/Viterbi_path</a></p><p>For firther reading Wiki page <a href="http://en.wikipedia.org/wiki/Hidden_Markov_model">http://en.wikipedia.org/wiki/Hidden_Markov_model</a></p><p>On CpG island paper and for indepth understanding <a href="http://www.biomedcentral.com/1471-2164/12/S2/S10">http://www.biomedcentral.com/1471-2164/12/S2/S10</a></p><p>&nbsp;</p><p>If you are more interested in exploring&nbsp;Markov Chain Exploration and understand it with graphical version please visit <a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1</a></p><p>Reference:</p><p>1.<a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com</a></p><p>2. <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com</a></p>]]></description>
	<dc:creator>Manisha Mishra</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/6562/molecular-bioinformatics-lab-mbl</guid>
  <pubDate>Tue, 19 Nov 2013 18:23:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Molecular Bioinformatics Lab (MBL)]]></title>
  <description><![CDATA[
<p>The main subject of interest in our laboratory is the study of the relationship among sequence, structure, and function in proteins and nucleic acids. Our research can be divided in two major topics:</p>

<p>the study of the sequence-structure relationship<br />(application -&gt; structure prediction)<br />the study of the structure-function relationship<br />(application -&gt; function prediction)</p>

<p>Therefore, anything related to the configuration (sequence) and conformation (structure) in atomic systems of proteins and nucleic acids, and the interaction of these with other elements (function) is of our major interest.</p>

<p>Lab page @ http://melolab.org/mbl/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/40566/the-el-sherif-group-chair-of-developmental-biology-department-of-biology-phd-position</guid>
  <pubDate>Sun, 19 Jan 2020 10:06:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[The El-Sherif Group, Chair of Developmental Biology, Department of Biology - PhD Position]]></title>
  <description><![CDATA[
<p>El-Sherif lab studies how genes are regulated to mediate patterning in Development. We use live and super-resolution imaging in addition to computational modeling to understand transcription dynamics at the single-cell level in three model systems: the fruit fly Drosophila melanogaster, the beetle Tribolium castaneum, and embryonic bodies derived from embryonic mouse stem cells.</p>

<p>In this project, you will use single-molecule techniques to label mRNA and DNA in (live and fixed) Drosophila embryos and fixed embryonic bodies. You will also use super-resolution microscopy to visualize protein condensates. Co-localization dynamics reflecting DNA-protein bindings and DNA looping events will be detected, analyzed, and used to test computational models of gene transcription.</p>

<p>Qualification:<br />MSc degree (or equivalent) in Biology, Biophysics, or Bioengineering</p>

<p>Experience in one or more of these areas: (1) molecular cloning, (2) imaging, (3) image analysis (using Matlab/Python/Java), (4) microfluidics, and (5) computational modeling.</p>

<p>How to Apply?<br />Send (1) your CV, (2) summary of research experience, and (3) email addresses of at least 2 references to ezzat.el-sherif@fau.de. Title your email ‘Transcription PhD Position’.</p>

<p>salary Grade.: E13<br />Total Time: 3 Jahre<br />Start: 01.01.2020.<br />End: 31.3.2020.</p>

<p>Address:<br />Dr. El-Sherif, Ezzat<br />Department Biologie<br />Professur für Zoologie (Entwicklungsbiologie) (Prof. Dr. Klingler)<br />Telefon 09131/85-28068, Fax 09131/85-28040, E-Mail: ezzat.el-sherif@fau.de</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6818/scientist-positions-gujarat-state-biotechnology-mission</guid>
  <pubDate>Mon, 25 Nov 2013 10:26:39 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist Positions @ Gujarat State Biotechnology Mission]]></title>
  <description><![CDATA[
<p>Gujarat State Biotechnology Mission invite applications [Online Only] under various projects* namely Gujarat Biodiversity Gene Bank (BioGene), Gujarat Institute of Genomics (GIG), Gujarat Institute of Bioinformatics [GIBS] and Gujarat Institute of Marine Biotechnology. Eligible candidates can Apply through online application portal.</p>

<p>1 Scientist E 3</p>

<p>50,000/-</p>

<p>M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject.</p>

<p>Minimum 8 Yrs. of experience after M.Sc. or 5 Yrs. of experience after Ph.D. in responsible position of work in R &amp; D in the area of genomics/ conservation biotechnology/bioinformatics/Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 40yrs.</p>

<p>2 Scientist B 6</p>

<p>30,000/-</p>

<p>M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject shall be preferred.</p>

<p>Minimum 3 Yrs. of experience after M.Sc. in responsible position of work in R &amp; D in the area of genomics/ conservation biotechnology/ bioinformatics /Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 35yrs.</p>

<p>The positions are purely on contractual basis for 11 months. Interested candidates can apply online in specified format available at "http://leogen.in/recruit/" The last date of applying is 24th December, 2013. Applications must be submitted online only. Applications submitted in any other format except online prescribed performa will be rejected. Candidates in service must apply through proper channel. Candidates will be required to provide original documents along with duly filled and signed application Performa, as and when called for interview.</p>

<p>For more details please visit the website URL : http://leogen.in/recruit</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41825/hnadock-a-nucleic-acid-docking-server-for-modeling-rnadna%E2%80%93rnadna-3d-complex-structures</guid>
	<pubDate>Thu, 04 Jun 2020 23:19:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41825/hnadock-a-nucleic-acid-docking-server-for-modeling-rnadna%E2%80%93rnadna-3d-complex-structures</link>
	<title><![CDATA[HNADOCK: a nucleic acid docking server for modeling RNA/DNA–RNA/DNA 3D complex structures]]></title>
	<description><![CDATA[<p><span>The HNADOCK server is to predict the binding complex structure between two nucleic acid molecules through a hierarchical docking algorihtm of an FFT-based global search strategy and an intrinsic scoring function for nucleic acid interactions. Users are required to provide the three-dimensional (3D) structures of the two molecules to be docked.&nbsp;</span></p><p>Address of the bookmark: <a href="http://huanglab.phys.hust.edu.cn/hnadock/" rel="nofollow">http://huanglab.phys.hust.edu.cn/hnadock/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
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	<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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7214/lapti-lab</guid>
  <pubDate>Thu, 12 Dec 2013 18:19:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[LAPTI Lab]]></title>
  <description><![CDATA[
<p>The main theme of our research is the understanding of how genetic information is decoded from DNA into RNA and proteins. Someone may find this topic a little strange and argue that we already know how this is happening.</p>

<p>Translational recoding. </p>

<p>RNA editing. </p>

<p>Evolution of the genetic code and translation.</p>

<p>More at http://lapti.ucc.ie/research.html</p>

<p>Lab page http://lapti.ucc.ie/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45244/the-ghost-ancestors-hidden-in-our-dna</guid>
	<pubDate>Tue, 18 Aug 2026 22:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45244/the-ghost-ancestors-hidden-in-our-dna</link>
	<title><![CDATA[The Ghost Ancestors Hidden in Our DNA]]></title>
	<description><![CDATA[<p>Imagine standing in a museum of human evolution.</p><p>There are Neanderthal bones. Denisovan remains. Fossils from ancient relatives of our species. Each specimen gives us another piece of the story of how Homo sapiens came to be.</p><p>But now imagine that one of the most important characters in that story has left behind no fossil, no skull, no bone, and no genome.</p><p>Nothing that a paleontologist could put behind glass.</p><p>And yet, somehow, that ancient population is still speaking.</p><p>It is speaking through us.</p><p>A fascinating new study published in Science (https://www.science.org/doi/10.1126/science.aef8874?) introduces a computational method called TRACE, which allows scientists to search modern human genomes for genetic traces of ancient populations that have never been directly identified.</p><p>For years, scientists have known that our ancestors interacted with Neanderthals and Denisovans. Their DNA still survives in modern human populations. But these may not have been the only ancient humans who crossed paths with our ancestors.</p><p>Using TRACE, researchers found evidence of an unknown archaic population that contributed DNA to the ancestors of modern humans before humans spread beyond Africa.</p><p>Even more surprisingly, they found evidence of a much older lineage&mdash;possibly around 1.8 million years old&mdash;whose genetic legacy may have reached some modern humans indirectly through Denisovans.</p><p>The extraordinary part is that researchers did not need DNA from these mysterious populations to detect them. Instead, they studied the ancestry of modern genomes and looked for genetic patterns that revealed unusually ancient branches of our family history.</p><p>It is almost like finding the footprints of someone who disappeared thousands of years ago&mdash;without ever finding the person themselves.</p><p>These discoveries suggest that human evolution was far more complicated than a simple family tree. Ancient human populations repeatedly separated, migrated, met and exchanged genes. Some eventually disappeared, but pieces of their genetic legacy survived.</p><p>And that means our DNA is more than a biological instruction manual.</p><p>It is also an archive of human history.</p><p>Some of the people recorded in that archive may never have a name or a fossil. But thanks to methods like TRACE, their genetic echoes are finally becoming visible.</p><p>The next big discovery about our ancient past may not come from a fossil in the ground.</p><p>It may already be inside us.</p><p>Reference: Zhang et al., &ldquo;Recovering signatures of archaic hominin introgression using ancestral recombination graphs,&rdquo; Science (2026), DOI: 10.1126/science.aef8874. Detail paper @&nbsp;https://www.science.org/doi/10.1126/science.aef8874?</p><p><br />The TRACE repository (https://github.com/YulinZhang9806/trace) contains the Python package and command-line tools used to infer archaic admixture tracts from ancestral recombination graphs.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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