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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29282?offset=980</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4761/dna-is-packaged-in-a-chromosome-experiment</guid>
	<pubDate>Mon, 23 Sep 2013 18:01:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4761/dna-is-packaged-in-a-chromosome-experiment</link>
	<title><![CDATA[DNA is packaged in a chromosome experiment]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fecfROFrp_c" frameborder="0" allowfullscreen></iframe>For more information, log on to-
http://shomusbiology.weebly.com/
Download the study materials here-
http://shomusbiology.weebly.com/bio-materials.html
A nucleosome is the basic unit of DNA packaging in eukaryotes, consisting of a segment of DNA wound in sequence around four histone protein cores.[1] This structure is often compared to thread wrapped around a spool.[2]

Nucleosomes form the fundamental repeating units of eukaryotic chromatin,[3] which is used to pack the large eukaryotic genomes into the nucleus while still ensuring appropriate access to it (in mammalian cells approximately 2 m of linear DNA have to be packed into a nucleus of roughly 10 µm diameter). Nucleosomes are folded through a series of successively higher order structures to eventually form a chromosome; this both compacts DNA and creates an added layer of regulatory control, which ensures correct gene expression. Nucleosomes are thought to carry epigenetically inherited information in the form of covalent modifications of their core histones. Nucleosomes were observed as particles in the electron microscope by Don and Ada Olins [4] and their existence and structure (as histone octamers surrounded by approximately 200 base pairs of DNA) were proposed by Roger Kornberg.[5][6] The role of the nucleosome as a general gene repressor was demonstrated by Lorch et al. in vitro [7] and by Han and Grunstein in vivo.]]></description>
	
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11494/postdoc-position-at-centre-mediterraneen-de-medecine-moleculaire-nice-france</guid>
  <pubDate>Wed, 04 Jun 2014 07:20:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Centre Méditerranéen de Médecine Moléculaire - Nice - France]]></title>
  <description><![CDATA[
<p>The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).<br />The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ). </p>

<p>The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.<br /> <br />Candidates should hold a Ph.D. degree and have strong background in bioinformatics.<br />The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.</p>

<p>Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )</p>

<p>Homepage: http://www.unice.fr/c3m/EN/Equipe10.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38634/eyechrom-visualizing-chromosome-count-data-from-plants</guid>
	<pubDate>Tue, 08 Jan 2019 10:20:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38634/eyechrom-visualizing-chromosome-count-data-from-plants</link>
	<title><![CDATA[EyeChrom: Visualizing Chromosome Count Data From Plants]]></title>
	<description><![CDATA[<p><span>It's goal is to show chromosmal data per genus. Select the genus, and the plot will show the records found for it in the Chromosome Counts Database. note: Report an issue via Gihub: github.com/roszenil/CCDBcurator and github.com/RodrigoRivero/EyeChrom</span></p>
<p>https://bsapubs.onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.1207</p><p>Address of the bookmark: <a href="http://eyechrom.com:3838/EyeChrom/" rel="nofollow">http://eyechrom.com:3838/EyeChrom/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41485/chromosight-computer-vision-based-program-for-pattern-recognition-in-chromosome-hi-c-contact-maps</guid>
	<pubDate>Mon, 23 Mar 2020 06:20:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41485/chromosight-computer-vision-based-program-for-pattern-recognition-in-chromosome-hi-c-contact-maps</link>
	<title><![CDATA[chromosight: Computer vision based program for pattern recognition in chromosome (Hi-C) contact maps]]></title>
	<description><![CDATA[<p>Python package to detect chromatin loops (and other patterns) in Hi-C contact maps.</p>
<p>Stable version with pip:</p>
<div>
<pre>pip3 install --user chromosight</pre>
</div>
<p>Stable version with conda:</p>
<div>
<pre>conda install -c bioconda -c conda-forge chromosight</pre>
</div>
<p>or, if you want to get the latest development version:</p>
<pre><code>pip3 install --user -e git+https://github.com/koszullab/chromosight.git@master#egg=chromosight</code></pre><p>Address of the bookmark: <a href="https://github.com/koszullab/Chromosight" rel="nofollow">https://github.com/koszullab/Chromosight</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12206/bioinformatics-algorithms-tutorials</guid>
	<pubDate>Tue, 24 Jun 2014 00:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12206/bioinformatics-algorithms-tutorials</link>
	<title><![CDATA[Bioinformatics algorithms tutorials]]></title>
	<description><![CDATA[<p>Useful bioinformatics tutorial, such as</p>
<p>De Bruijn Graphs for NGS Assembly<br>Algorithms for PacBio Reads<br>Software and Hardware Concepts for Bioinformatics<br>Finding us in Homolog.us (Search Algorithms)<br>NGS Genome and RNAseq Assembly - a Hands on Primer<br>Introduction to PERL, Python, R and C/C++ for Bioinformatics</p><p>Address of the bookmark: <a href="http://www.homolog.us/Tutorials/" rel="nofollow">http://www.homolog.us/Tutorials/</a></p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</guid>
	<pubDate>Tue, 05 May 2020 10:37:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</link>
	<title><![CDATA[Synteny and Rearrangement Identifier (SyRI)]]></title>
	<description><![CDATA[<p>SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.</p><p>Address of the bookmark: <a href="https://schneebergerlab.github.io/syri/" rel="nofollow">https://schneebergerlab.github.io/syri/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12567/workshop-on-molecular-modeling-and-dynamics-simulation-analyses</guid>
  <pubDate>Fri, 04 Jul 2014 13:38:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Workshop On Molecular Modeling and Dynamics Simulation Analyses]]></title>
  <description><![CDATA[
<p>Workshop On Molecular Modeling and Dynamics Simulation Analyses</p>

<p>August1-2, 2014</p>

<p>Organised By</p>

<p>Centre of Excellence in Bioinformatics<br />Bioinformatics Infrastructure Facility<br />Department of Biochemistry<br />University of Lucknow<br />Lucknow-226007</p>

<p>Course Contents</p>

<p>Molecular Modeling<br /> Homology Modeling<br />Molecular Docking<br />Post-structural Analyses</p>

<p>Molecular Dynamics (MD)<br />Simulation<br />Linux Introduction<br />Gromacs Installation</p>

<p>MD Simulation of Protein ligand complex<br />Analyses of MD<br />Trajectories<br />Visualization of Dynamic<br />complexes</p>

<p>Important Dates</p>

<p>Registration Begins June 25, 2014<br />Registration Closes July 25, 2014</p>

<p>Brochure : www.lkouniv.ac.in/conference/Brochure_August,%202014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35899/reference-free-prediction-of-rearrangement-breakpoint-reads</guid>
	<pubDate>Thu, 08 Mar 2018 05:05:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35899/reference-free-prediction-of-rearrangement-breakpoint-reads</link>
	<title><![CDATA[Reference-free prediction of rearrangement breakpoint reads]]></title>
	<description><![CDATA[<p><span>lideSort-BPR (&nbsp;</span><span>b</span><span>&nbsp;reak&nbsp;</span><span>p</span><span>&nbsp;oint&nbsp;</span><span>r</span><span>&nbsp;eads) is based on a fast algorithm for all-against-all comparisons of short reads and theoretical analyses of the number of neighboring reads. When applied to a dataset with a sequencing depth of 100&times;, it finds &sim;88% of the breakpoints correctly with no false-positive reads. Moreover, evaluation on a real prostate cancer dataset shows that the proposed method predicts more fusion transcripts correctly than previous approaches, and yet produces fewer false-positive reads. To our knowledge, this is the first method to detect breakpoint reads without using a reference genome.</span></p>
<p><span>https://github.com/ewijaya/slidesort-bpr</span></p><p>Address of the bookmark: <a href="https://code.google.com/archive/p/slidesort-bpr/" rel="nofollow">https://code.google.com/archive/p/slidesort-bpr/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</guid>
	<pubDate>Wed, 23 Jul 2014 06:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</link>
	<title><![CDATA[Orione – a web-based framework for NGS analysis in microbiology]]></title>
	<description><![CDATA[<p>End-to-end NGS microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult due to a lack of interoperability, reproducibility, and transparency. To overcome these limitations researchers at <a href="http://www.crs4.it/" target="_blank">CRS4</a>, Italy have developed Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for NGS microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.</p>
<p>Reference</p>
<p>Cuccuru G1, Orsini M, Pinna A, Sbardellati A, Soranzo N, Travaglione A, Uva P, Zanetti G, Fotia G. (2014)<strong> Orione, a web-based framework for NGS analysis in microbiology.</strong> <em>Bioinformatics</em> [Epub ahead of print]. [<a href="http://bioinformatics.oxfordjournals.org/content/early/2014/03/10/bioinformatics.btu135.long" target="_blank">article</a>]</p><p>Address of the bookmark: <a href="http://orione.crs4.it/" rel="nofollow">http://orione.crs4.it/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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