<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32465?offset=930</link>
	<atom:link href="https://bioinformaticsonline.com/related/32465?offset=930" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7815/post-doc-in-systems-genetics</guid>
  <pubDate>Wed, 08 Jan 2014 19:23:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post-doc in Systems Genetics]]></title>
  <description><![CDATA[
<p>Gagneur lab at Gene Center, Ludwig-Maximilians-Universitaet, Munich, Germany</p>

<p>Deadline for applications : January 15, 2014.</p>

<p>Description :</p>

<p>We seek a talented and motivated post-doc to develop computational methods for inferring the molecular basis of genetic diseases by integration of personal omics data. Research topics include: identifying causal mutations of rare disease patients by meta-analysis; inferring disease-causing molecular pathways from genotype, human phenotypes, and omics profile of patient-derived cell lines; and causal inference from longitudinal omics studies of patients. The developed methods will be applied to analyze data from our medical collaborators.</p>

<p>Candidates must either hold a PhD in computational biology or bioinformatics, or hold a PhD in physics, statistics, or applied mathematics with practical experience with high-dimensional data analysis. Experience in quantitative genetics is a plus. Applicants must have a proven publication record and an interest for translational research.</p>

<p>The Gagneur lab is a young, lively and multidisciplinary group with a research focus on systems genetics and gene regulation. It is located at the Gene Center of the LMU (University of Munich), an interdisciplinary institution whose 16 independent research groups investigate the regulation of gene expression at all levels - from the underlying molecular mechanisms to the biological system. The institute is located on the biomedical research campus Munich-Grosshadern, offering a dynamic, interactive and internationally oriented research environment. The dynamism of Munich and the proximity of the Alps provide an excellent quality of life.</p>

<p>The salary is according to the TV-L (German academic salary scale).<br />Applications including a cover letter, CV, and references must be sent by January 15th 2014 to Julien Gagneur (gagneur@genzentrum.lmu.de)</p>

<p>About the lab: http://www.gagneur.genzentrum.lmu.de</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44329/metabuli-%EB%B6%84%EB%A6%AC-improves-metagenomic-read-classification</guid>
	<pubDate>Sat, 03 Jun 2023 20:15:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44329/metabuli-%EB%B6%84%EB%A6%AC-improves-metagenomic-read-classification</link>
	<title><![CDATA[Metabuli 분리 improves metagenomic read classification]]></title>
	<description><![CDATA[<p><span>Metabuli 분리 improves metagenomic read classification through metamers, DNA-AA k-mers, to be sensitive and specific, recovering 99% and 98% of DNA or AA classifiers.</span></p>
<p>&nbsp;</p>
<p><span><span>Metabuli is metagenomic classifier that jointly analyze both DNA and amino acid (AA) sequences. DNA-based classifiers can make specific classifications, exploiting point mutations to distinguish close taxa. AA-based classifiers have higher sensitivity in detecting homology between query and reference sequences, leverageing higher conservation of AA sequences. Metabuli combines the information of both sequence types using a novel k-mer structure,&nbsp;</span><em>metamer</em><span>, to enable both specific and sensitive characterization of metagenomic samples. In addition, it can classify reads against a database of any size as long as it fits in the hard disk.</span> </span></p><p>Address of the bookmark: <a href="https://github.com/steineggerlab/Metabuli" rel="nofollow">https://github.com/steineggerlab/Metabuli</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/7032/computer-experts-in-biotechnology-laboratory</guid>
	<pubDate>Wed, 04 Dec 2013 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/7032/computer-experts-in-biotechnology-laboratory</link>
	<title><![CDATA[Computer experts in biotechnology laboratory]]></title>
	<description><![CDATA[<p>Only bioinformatician can understand that <strong>multiplication</strong> and <strong>division</strong> are different but same thing :)</p><p><span>Disclaimer:</span>&nbsp;This cartoon is solely designed to create humour and fun, not to offend any computer experts.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/7032" length="35726" type="image/gif" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</guid>
	<pubDate>Tue, 17 Sep 2024 02:34:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</link>
	<title><![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]></title>
	<description><![CDATA[<p dir="auto">R Package to visualize alignments between two or multiple DNA sequences including<br>a number of functionalities to facilitate processing of alignments in PAF format.</p>
<p dir="auto"><span>SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.</span></p>
<p dir="auto">Author: David Porubsky</p><p>Address of the bookmark: <a href="https://github.com/daewoooo/SVbyEye" rel="nofollow">https://github.com/daewoooo/SVbyEye</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<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>
</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/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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43548/upgma-worked-example</guid>
	<pubDate>Wed, 13 Oct 2021 06:13:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43548/upgma-worked-example</link>
	<title><![CDATA[UPGMA Worked Example]]></title>
	<description><![CDATA[<p><span>The tabs below include a walkthrough of clustering 7 biological sequences (A-G) using the Unweighted Pair-Group Method with Arithmetic mean (UPGMA) method. Note that UPGMA is actually a generic method and thus the walkthrough could apply to any objects A-G for which pairwise distances can be calculated. A small CGI site for generating a UPGMA tree from a distance matrix can be found&nbsp;</span><a href="http://bioware.soton.ac.uk/upgma.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="http://www.slimsuite.unsw.edu.au/teaching/upgma/" rel="nofollow">http://www.slimsuite.unsw.edu.au/teaching/upgma/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40476/libsdyogen-libibrary-for-comparative-genomics</guid>
	<pubDate>Wed, 25 Dec 2019 01:32:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40476/libsdyogen-libibrary-for-comparative-genomics</link>
	<title><![CDATA[LibsDyogen: Libibrary for comparative genomics]]></title>
	<description><![CDATA[<p>Library of usual classes and functions written in python and used in the Dyogen team for comparative genomics applications.</p>
<p>Collaborative python library used in the<span>&nbsp;</span><a href="http://www.ibens.ens.fr/?rubrique43&amp;lang=fr">DYOGEN team</a>for studying the evolution of gene order in vertebrates.</p>
<p><a href="http://www.ibens.ens.fr/?rubrique43&amp;lang=fr">http://www.ibens.ens.fr/?rubrique43&amp;lang=fr</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/DyogenIBENS/LibsDyogen" rel="nofollow">https://github.com/DyogenIBENS/LibsDyogen</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>