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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41825?offset=150</link>
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	<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/41504/quartataweb-user-friendly-server-developed-for-polypharmacological-and-chemogenomics-analyses</guid>
	<pubDate>Wed, 01 Apr 2020 10:30:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41504/quartataweb-user-friendly-server-developed-for-polypharmacological-and-chemogenomics-analyses</link>
	<title><![CDATA[QuartataWeb: user-friendly server developed for polypharmacological and chemogenomics analyses.]]></title>
	<description><![CDATA[<p><span>Data on protein-drug and protein-chemical interactions are rapidly accumulating in databases such as&nbsp;</span><a href="http://www.drugbank.ca/" target="_blank">DrugBank</a><span>&nbsp;and&nbsp;</span><a href="http://stitch.embl.de/" target="_blank">STITCH</a><span>. These data usually reflect observed interactions, while the lack of data for a given protein-drug/chemical pair does not necessarily mean the lack of interaction. Indeed, recent studies, both computational and experimental, highlighted the promiscuity of both proteins and small molecules: many drugs have side effects i.e. they target proteins other than those known in public databases; and many proteins bind chemicals other than those known, opening the way to design repurposable drugs, new chemicals, or polypharmacological treatments.</span></p>
<p><span><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa210/5813333">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa210/5813333</a></span></p><p>Address of the bookmark: <a href="http://quartata.csb.pitt.edu/" rel="nofollow">http://quartata.csb.pitt.edu/</a></p>]]></description>
	<dc:creator>Neel</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>
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