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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23892?offset=1130</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44213/bioinformatics-tools-to-explore-ssrs-in-genomes</guid>
	<pubDate>Tue, 07 Mar 2023 13:06:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44213/bioinformatics-tools-to-explore-ssrs-in-genomes</link>
	<title><![CDATA[Bioinformatics tools to explore SSRs in genomes !]]></title>
	<description><![CDATA[<p>There are several bioinformatics tools that can be used to explore Simple Sequence Repeats (SSRs), which are also known as microsatellites. Here are a few examples:</p><ol>
<li>
<p>MISA: MISA (MIcroSAtellite) is a web-based tool that can identify SSRs in DNA sequences. It can be used to analyze nucleotide sequences from various organisms and can identify perfect, compound, and imperfect SSRs.</p>
</li>
<li>
<p>SSR Locator: SSR Locator is a web-based tool that identifies SSRs in both DNA and RNA sequences. It can identify perfect, compound, and imperfect SSRs, and can also filter out low complexity regions.</p>
</li>
<li>
<p>SciRoKo: SciRoKo is a software tool that can identify SSRs in DNA sequences. It can be used to analyze genomic and transcriptomic sequences from various organisms and can identify perfect, compound, and imperfect SSRs.</p>
</li>
<li>
<p>Primer3: Primer3 is a web-based tool that designs PCR primers for SSRs. It can design primers for perfect and imperfect SSRs, and can be used to design primers for SSRs in various organisms.</p>
</li>
<li>
<p>QDD: QDD (Quick Detection of Duplication) is a software tool that can identify SSRs in DNA sequences and can also identify duplicate loci. It can be used to analyze genomic and transcriptomic sequences from various organisms.</p>
</li>
</ol><p>These are just a few examples of the many bioinformatics tools available for exploring SSRs. Depending on your specific needs and research questions, you may find that other tools are more appropriate for your analysis.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38248/how-to-set-up-ssh-on-ubuntu-1804</guid>
	<pubDate>Thu, 22 Nov 2018 10:12:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38248/how-to-set-up-ssh-on-ubuntu-1804</link>
	<title><![CDATA[How to set up SSH on Ubuntu 18.04]]></title>
	<description><![CDATA[<p>SSH, also known as Secure Shell or Secure Socket Shell, is a network protocol that gives users, particularly system administrators, a secure way to access a computer over an unsecured network. SSH also refers to the suite of utilities that implement the SSH protocol.</p><p>Here are the commands used to connect by Secure SHell:</p><p>On the server side</p><blockquote><p><span style="font-size: 12.8px;">sudo apt-get install ssh</span></p><p><span style="font-size: 12.8px;">sudo apt-get install openssh-server</span></p><p><span style="font-size: 12.8px;">sudo /etc/init.d/ssh start</span></p><p>sudo nano /etc/ssh/sshd_config</p><p>Uncomment port 22<br />Uncomment HostKey /etc/ssh/ssh_host_rsa_key<br />Uncomment AuthorizedKeysFile .ssh/authorized_keys .ssh/authorized_keys2<br />Set pubkey authentication to "yes"</p></blockquote><p>sudo systemctl restart sshd.service # or sudo /etc/init.d/ssh reload</p><p><br />On the client side:<br />in ~/.ssh</p><blockquote><p>ssh-keygen -t rsa # set passphrase or not<br />ssh-copy-id -i ~/.ssh/id_rsa user@100.100.10.100</p></blockquote><p>--&gt; write "yes" then password in</p><blockquote><p><br />ssh user@100.100.10.100</p></blockquote><p>--&gt; write password --&gt; you should be in</p><p>--&gt; in /home/user/.ssh/config type:<br /><strong>Host WhateverName</strong><br /><strong> HostName 100.100.10.100</strong><br /><strong> User username</strong><br /><strong> ForwardX11 yes</strong><br /><strong> ForwardAgent yes</strong><br /><strong> IdentityFile ~/.ssh/id_rsa</strong></p><p>--&gt; you should now be able to connect with :</p><blockquote><p>ssh WhateverName</p></blockquote>]]></description>
	<dc:creator>AnHo</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41565/csar-web-a-web-server-of-contig-scaffolding-using-algebraic-rearrangements</guid>
	<pubDate>Fri, 10 Apr 2020 04:39:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41565/csar-web-a-web-server-of-contig-scaffolding-using-algebraic-rearrangements</link>
	<title><![CDATA[CSAR-web: a web server of contig scaffolding using algebraic rearrangements]]></title>
	<description><![CDATA[<p><span>CSAR-web is a web-based tool that allows the users to efficiently and accurately scaffold (i.e. order and orient) the contigs of a target draft genome based on a complete or incomplete reference genome from a related organism.&nbsp;</span></p>
<p><span><span>CSAR-web can serve as a convenient and useful scaffolding tool allowing the users to efficiently and accurately scaffold their draft genomes according to a complete or incomplete reference genome.&nbsp;</span></span></p><p>Address of the bookmark: <a href="http://genome.cs.nthu.edu.tw/CSAR-web" rel="nofollow">http://genome.cs.nthu.edu.tw/CSAR-web</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43907/htop-explained</guid>
	<pubDate>Wed, 06 Jul 2022 01:28:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43907/htop-explained</link>
	<title><![CDATA[htop explained]]></title>
	<description><![CDATA[<p>For the longest time I did not know what everything meant in htop.</p>
<p>I thought that load average&nbsp;<code>1.0</code>&nbsp;on my two core machine means that the CPU usage is at 50%. That's not quite right. And also, why does it say&nbsp;<code>1.0</code>?</p>
<p>I decided to look everything up and document it here.</p><p>Address of the bookmark: <a href="https://peteris.rocks/blog/htop/" rel="nofollow">https://peteris.rocks/blog/htop/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</guid>
	<pubDate>Fri, 18 Jul 2014 05:42:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</link>
	<title><![CDATA[Breaking chromosomes to study cancer !!!]]></title>
	<description><![CDATA[<p>Chromosomes are present in every cell of our body and they contain the information the body needs to develop and function properly. This information is carried in genes that are arranged along the chromosomes. There are usually 46 chromosomes in every cell. These chromosomes come in pairs, one from our mother and one from our father. The chromosomes can be sorted into 23 pairs by looking at them down a microscope.</p><p>Most people who have a balanced translocation have the right amount of chromosome material but it has been rearranged in some way. This may happen if two chromosomes swap pieces (a reciprocal translocation). In other cases two whole chromosomes may become stuck together (a Robertsonian translocation). This page describes what happens when someone has a reciprocal translocation. <br /><br />Reciprocal chromosomal translocations occur following double-strand breaks (DSBs) in DNA when a section of one chromosome is exchanged with that of another, non-homologous chromosome. These exchanges may produce a dysfunctional fusion gene that disrupts cell growth and survival pathways, such as the translocations seen in leukemia and childhood sarcomas. <br /><br />Chromosomal translocations have been well studied in cancer cell lines which are associated with two types of cancer, acute myeloid leukemia and Ewing's sarcoma, but determining how they contribute to cancer development is complicated by additional mutations and altered gene expression profiles in these cultured cells. Now, Juan Carlos Ramirez, head of the Viral Vector Facility at the Fundacion Centro Nacional de Investigaciones Cardiovasculares (CNIC) and his colleagues Raul Torres at CNIC and Sandra Rodriguez-Peralez at the Spanish National Cancer Center (CNIO) in Madrid, Spain have used a new genome editing tool, CRISPR-Cas9, to induce chromosomal translocations for the first time in a human cell line and in primary cells. The study's authors conclude by stating that the use of this technology will allow for the clarification of how and why chromosomal translocation occurs, which without doubt will allow new anti-cancer therapeutic strategies to be tackled.</p><p>Using RNA-Guided Endonuclease (RGEN) technology or CRISPR/Cas9 genome engineering technology, CNIO and CNIC researchers have shown that it is possible to obtain such chromosomal translocations. The CRISPR-Cas9 system is extremely simple to introduce a cut at the desired locus, easier to design, and cheaper than many other systems. Using the CRISPR-Cas9 system, Ramirez and his colleagues reproduced the translocations observed in Ewing&rsquo;s Sarcoma (ES) and Acute Myeloid Leukemia (AML) patient cell lines in HEK293 cells and also generated the ES translocation in human mesenchymal stem cells and the AML translocation in umbilical cord blood cells.</p><p>By focusing on chromosomal translocation without the confounding characteristics of established cell lines, these new cells lines should help answer the fundamental question of what causes a cell to become cancerous. Ramirez and his team now look forward to modeling other chromosome translocations in a variety of cell types.</p><p>Reference:</p><p>http://en.wikipedia.org/wiki/Chromosomal_translocation</p><p>http://www.nature.com/ncomms/2014/140603/ncomms4964/abs/ncomms4964.html<br /><br /></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36019/ewas-epigenome-wide-association-study-software-20</guid>
	<pubDate>Wed, 21 Mar 2018 18:14:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36019/ewas-epigenome-wide-association-study-software-20</link>
	<title><![CDATA[EWAS: epigenome-wide association study software 2.0]]></title>
	<description><![CDATA[<p><span>EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our &ldquo;population epigenetic framework&rdquo; and can perform: (1) epigenome-wide single marker association study; (2) epigenome-wide methylation haplotype (meplotype) association study; and (3) epigenome-wide association meta-analysis.</span></p><p>Address of the bookmark: <a href="http://www.bioapp.org/ewas/" rel="nofollow">http://www.bioapp.org/ewas/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17504/postdoc-scientist-bioinformatics-at-ccmb</guid>
  <pubDate>Fri, 26 Sep 2014 19:58:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[PostDoc Scientist Bioinformatics at CCMB]]></title>
  <description><![CDATA[
<p>1. Project Assistant/Junior Research Fellow/ Project Fellow [PA_JRF_PF]</p>

<p>a) M.Sc/or equivalent in biological sciences/related areas [Position Code: PA_JRF_PF_a]<br />b) B.E/B.Tech/ M.Sc in biotechnology/bioinformatics/computer science/Chemistry/Physics or MCA [Position Code: PA_JRF_PF_b]<br />c) M.Sc/or equivalent in wildlife sciences/ecology/environmental sciences or MBBS/BVSc/MVSc. [Position Code: PA_JRF_PF_c]</p>

<p>(Candidates with result awaited are NOT eligible to apply)</p>

<p>Upper Age limit 28years</p>

<p>Rs.12000 / Rs.16000 (as sanctioned by the funding agency)</p>

<p>2. Post Doctoral Fellow/Research Associate in multiple research areas [PDF_RA]</p>

<p>Ph.D. (submitted/awarded) in any branch of biological Sciences. Candidates with Ph.D. in other sciences are also encouraged to apply.</p>

<p>Experience in molecular biology, biochemistry, structural biology, cell biology, infectious disease, conservation genetics, veterinary science, reproductive biology, and molecular diagnostics is desired but not mandatory.</p>

<p>[Position Code: PDF_RA]</p>

<p>UpperAge limit 35years</p>

<p>Rs. 22000- 26000 (as sanctioned by the funding agency)</p>

<p>3. Post Doctoral Scientist Fellow [PDSF]</p>

<p>Ph.D in any of the following areas: bioinformatics, next generation sequencing, high throughput data analysis, proteomics, bio-statistics, computer science, information technology, computer hardware and networking/clustering, parallel processing.<br />[Position Code: PDSF]</p>

<p>Upper Age limit 40 years</p>

<p>Rs. 40000 consolidated (as sanctioned by the funding agency)</p>

<p>Download Application: Last date for apply online: 09th Oct 2014</p>

<p>Advertisement: www.ccmb.res.in//index.php?view=notifications&amp;mid=0&amp;id=71&amp;nid=38</p>

<p>Apply online http://www.ccmb.res.in/positions/temp_notif/online_form.html</p>

<p>More at http://www.ccmb.res.in//index.php?view=notifications&amp;mid=0&amp;id=71&amp;nid=38</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/17652/arraygen-bioinformatics-genomics-group</guid>
  <pubDate>Sun, 28 Sep 2014 14:09:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[ArrayGen Bioinformatics Genomics Group]]></title>
  <description><![CDATA[
<p>ArrayGen is a global bioinformatics company which is a one stop solution for microarray designing and genomics data analysis. Our novel Array Design Approach Strategy (ADAS) aims to condense the time lag between demands of scientific community and manufacture industry, thereby expediting research processes.</p>

<p>ArrayGen specializes in Genomics data analysis and research, as we believe in the level of precision, predictability, benchmark-ability, and data analysis capability of genomics data over other forms of biological data. ArrayGen constantly strives to develop new solutions, and plug the existing gaps in the technological advancement of the field.</p>

<p>More http://www.arraygen.com/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17873/postdoc-position-in-protein-annotation-and-machine-learning-paris-france</guid>
  <pubDate>Sat, 04 Oct 2014 08:10:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position in protein annotation and machine learning - Paris, France]]></title>
  <description><![CDATA[
<p>We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of Paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>The postdoc will be payed under a contract of Ingénieur de Recherche lasting 3.5 years and it is available from September 1st, 2014.</p>

<p>Group Web Page: http://www.lcqb.upmc.fr/AnalGenom/home.html</p>

<p>Ref. E-Mail: Alessandra Carbone alessandra.carbone@lip6.fr</p>
]]></description>
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