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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32633?offset=120</link>
	<atom:link href="https://bioinformaticsonline.com/related/32633?offset=120" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40945/the-clark-lab</guid>
  <pubDate>Fri, 07 Feb 2020 13:57:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Clark Lab]]></title>
  <description><![CDATA[
<p>Study the process of Adaptive Evolution, during which species adopt novel traits to overcome challenges. We retrace the evolutionary histories of genomic elements to determine the changes underlying adaptation and to discover previously unknown genetic networks. These discoveries have already led to advances in human health, species conservation, and molecular biology. </p>

<p>More at http://clark.genetics.utah.edu/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit</guid>
	<pubDate>Thu, 16 Dec 2021 02:50:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit</link>
	<title><![CDATA[Peregrine &amp; SHIMMER Genome Assembly Toolkit]]></title>
	<description><![CDATA[<p><span>Peregrine is a fast genome assembler for accurate long reads (length &gt; 10kb, accuracy &gt; 99%). It can assemble a human genome from 30x reads within 20 cpu hours from reads to polished consensus. It uses Sparse HIereachical MimiMizER (SHIMMER) for fast read-to-read overlaping without quadratic comparisions used in other OLC assemblers.</span></p><p>Address of the bookmark: <a href="https://github.com/cschin/Peregrine" rel="nofollow">https://github.com/cschin/Peregrine</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44474/claw-chloroplast-long-read-assembly-workflow</guid>
	<pubDate>Wed, 21 Feb 2024 12:37:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44474/claw-chloroplast-long-read-assembly-workflow</link>
	<title><![CDATA[CLAW: Chloroplast Long-read Assembly Workflow]]></title>
	<description><![CDATA[<p dir="auto">CLAW (Chloroplast Long-read Assembly Workflow) is an mostly-automated Snakemake-based workflow for the assembly of chloroplast genomes. CLAW uses chloroplast long-reads, which are baited out of larger read libraries (e.g., an Oxford Nanopore Technologies MinION read library derived from photosynthetic tissue), for assembly with Flye and/or Unicycler. CLAW was designed with the novice bioinformatician in mind - it is easy to install and easy to use, requiring only minimal user input.</p><p>Address of the bookmark: <a href="https://github.com/aaronphillips7493/CLAW" rel="nofollow">https://github.com/aaronphillips7493/CLAW</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42164/postdoctoral-researcher-in-statistical-bioinformatics-at-orebro-university</guid>
  <pubDate>Wed, 26 Aug 2020 10:20:11 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Researcher in Statistical Bioinformatics at Örebro University]]></title>
  <description><![CDATA[
<p>The position is in Medical Sciences, with special focus on Statistical Bioinformatics.</p>

<p>The position is a full-time position for a fixed term of two years. The salary depends on the successful candidate’s qualifications and experience.</p>

<p>For more information, please contact Prof. Dirk Repsilber,This is an email address, Prof. Hugo Hesser, This is an email addressor Prof. Allan Sirsjö, allan.This is an email address, or Prof. Robert Brummer,This is an email address.</p>

<p>Örebro University actively pursues an equal work environment and values the qualities that diversity adds to our operations.</p>

<p>More detail at https://www.oru.se/english/working-at-orebro-university/jobs-and-vacancies/job/?jid=20200286/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/92/genomic-impact</guid>
	<pubDate>Wed, 10 Jul 2013 01:33:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/92/genomic-impact</link>
	<title><![CDATA[Genomic Impact]]></title>
	<description><![CDATA[<p>The ongoing genomic research in USA&nbsp;<span>contributed $31 billion to the U.S. gross national product and helped support 152,000 jobs.&nbsp;</span></p><p><span>Reference:&nbsp;<a href="http://www.unitedformedicalresearch.com/wp-content/uploads/2013/06/The-Impact-of-Genomics-on-the-US-Economy.pdf">http://www.unitedformedicalresearch.com/wp-content/uploads/2013/06/The-Impact-of-Genomics-on-the-US-Economy.pdf</a></span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42206/pollard-lab</guid>
  <pubDate>Fri, 25 Sep 2020 20:20:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pollard Lab]]></title>
  <description><![CDATA[
<p>We are a bioinformatics research lab focused on developing novel methods and using them to study genome evolution, organization, and regulation. Our mission is to decode biomedical knowledge that is missed without rigorous statistical approaches.</p>

<p>http://docpollard.org/</p>

<p>Tools</p>

<p>http://docpollard.org/resources/software/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/428/five-unique-traits-of-effective-computational-biologist</guid>
	<pubDate>Thu, 11 Jul 2013 13:12:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/428/five-unique-traits-of-effective-computational-biologist</link>
	<title><![CDATA[Five unique traits of effective computational biologist]]></title>
	<description><![CDATA[<p>Bioinformatics research is driven by large set of software, scripts, and tools to analyse gigantic biological data. Being a great biological programmer or bioinformatician involves more than writing code that works. The biological programmers who rise to the top ranks of their profession are not only good programmer but also expert in biological stuff. Moreover, In order to be a good and effective biological programmer, you need to possess a combination of traits that allow your computational as well as biological skill, experience, and knowledge to produce working code. There are some technically skilled biological programmers who will never be effective because they lack the other important traits needed. Here are top five traits that are necessary to become a great biological programmer.</p><p><strong>1. Learn and get updated</strong></p><p>Some of the bad biological programmers only learn new technical or non-technical things when it&rsquo;s absolutely necessary. The good biological programmers learn new technical skills proactively. But great biological programmers not only learn new technical skills on their own but also learn non-technical skills, and have an open mind to sources of knowledge that others may shut out.</p><p>In other concrete term, the bad biological programmer learn Perl's regular expression when they started a project on comparative genomics; the good biological programmer learned it a year before because it looked interesting; and the great biological programmer also read about the BioPerl packages, genomics, DNA string, genomic theories, or some similar course of study so that they could understand the results and explain it biologically.</p><p><strong>2. Not a merely coder!!!</strong></p><p>I often encountered with biological programmer who call themself a hard-core computer programmer and avoid biology. I can almost guarantee that if you are one of them then you are not doing research but merely writing "dry" codes.</p><p>According to my supervisor most of the computational biologist, don't know what they are doing biologically. Even they struggle to explain their own programs output and results. Therefore, It is highly advisable to learn basic of biology which can assist you to explain the result and understand your discovery. Always remember you are a researcher not a coder.</p><p><strong>3. Be Social with biologist</strong></p><p>The computational biologist spends most of the time in from of computers, writing codes. They always think their job is to produce working codes, not technical research perfections. But, they are completely wrong. You should not forget that apart from your computational skills you also need some biologist, other than your supervisor, to explain and make you understand the complex biological mechanism.</p><p>I highly recommend your to interact with biotech researchers and learn how do they explain their one graph (which they generally produce after one year of work) biologically. Remember, the origin of your research project is complex biological phenomenon, which is more complex than that of your limited programming rules.</p><p><strong>4. Do not search, research for answers</strong></p><p>Researching for answers means more than typing several keywords into a search engine or posting a question at Stack Overflow or the BioStars forums. I have entered problems into search engines that generate no results, and every question I posted on Stack Overflow or the BioStars forums never got anything resembling an answer, yet I solved the issues and moved on. I&rsquo;m not a magician &mdash; I just know how to find answers or discover root causes.</p><p>Many problems are situational, and if you depend on search engines and forums, you can waste a lot of time going down a rabbit hole and possibly never getting a solution. Learn to perform root cause analysis, learn enough about the underlying system to look for other clues and solutions, and learn to take a long distance view of an issue before deep diving into it.</p><p><strong>5. Love and defend your research</strong></p><p>You cannot rise to the top in this research profession without loving your work. There are some very good &ldquo;it&rsquo;s just a job&rdquo; biological programmers (I&rsquo;ve been one at times), but if that is your outlook, you won&rsquo;t be willing to do whatever it takes to succeed. This idea gets a lot of folks in a huff, because they feel it is a personal insult. &ldquo;I&rsquo;m a good programmer, but I have other priorities and can&rsquo;t make work my life.&rdquo; I understand completely; I have other priorities too. As much as I hate to say it, when I am passionate about my work, I am willing (though not eager) to abandon my other priorities to finish the job. It is not an insult to say that if you aren&rsquo;t willing to pull out all the stops you can&rsquo;t be the best, it is a fact.</p><p>You must be passionate about more than programming &mdash; you must also be excited about your research, the tools and technology you are using, and so on. I have seen very good and even great biological programmers operating at mediocre levels because something was not a good fit, such as they hated the project or were using a technology they disliked. Therefore, like your research project and get excited about your discoveries. You have not only to discover but also defend your finding with scientific words.</p><p>Thanks to all of you for reading.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42308/icmr-scientist-jobs-for-biotechlife-sciencebiology-bioinformatics</guid>
  <pubDate>Tue, 10 Nov 2020 18:45:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[ICMR Scientist Jobs For Biotech/Life Science/Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>CMR welcomes on-line applications up to 5th December 2020 till 5:30 PM to fill out the vacancies of 42 Scientist’ E’ (Medical), 01 Scientist ‘E’ (Non-Medical), 16 Scientist ‘D’ (Medical) and also 06 Scientist ‘D’ (Non-Medical) from Indian Citizens for appointment on regular basis under Direct Recruitment with all India transfer liability under the Council.</p>

<p>Post I</p>

<p>Name of the Post: Scientist-E (Non-Medical)</p>

<p>Number of positions: One</p>

<p>Upper Age limit: 50 years</p>

<p>Post II</p>

<p>Name of the Post: Scientist-D (Non-Medical)</p>

<p>Number of positions: Six</p>

<p>Upper Age limit: 45 years</p>

<p>Fee:</p>

<p>Application Fee of Rs. 1500/- (Rupees one thousand five hundred only) is needed. SC / ST / Women/ PWD/ EWS applicants are exempted from application fee. Application Fee is to be paid by candidates through online web link given up the application. Application fees when paid will certainly not be reimbursed under any situations.</p>

<p>How to apply:</p>

<p>i) Candidates should apply online on https://recruit.icmr.org.in. A separate application needs to be submitted for every post, with the required application fee.</p>

<p>ii) Following self-attested documents are required to be uploaded together with the application:<br />a) Proof of Date of Birth.<br />b) Educational qualifications.<br />c) Experience.</p>

<p>More at https://recruit.icmr.org.in/assets/uploads/advertisement/ICMR_Advertisement_06112020.pdf</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/851/the-institute-for-molecular-bioscience-imb-bailey-lab</guid>
  <pubDate>Sun, 14 Jul 2013 11:53:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Institute for Molecular Bioscience (IMB), Bailey Lab]]></title>
  <description><![CDATA[
<p>Pattern recognition and computational biology</p>

<p>MEME Suite software development; gene expression; mathematical modelling; gene regulation and transcription</p>

<p>Specialization:<br />Pattern recognition and modelling in computational biology</p>

<p>Link @ http://www.imb.uq.edu.au/tim-bailey</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</guid>
	<pubDate>Sun, 27 Dec 2020 05:28:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</link>
	<title><![CDATA[Galaxy Training Resources !]]></title>
	<description><![CDATA[<p>Welcome to Galaxy Training!</p>
<p>Collection of tutorials developed and maintained by the worldwide Galaxy community</p>
<table>
<thead>
<tr><th>Topic</th><th>Tutorials</th></tr>
</thead>
<tbody>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/introduction/">Introduction to Galaxy Analyses</a></td>
<td>10</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/assembly/">Assembly</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/climate/">Climate</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/computational-chemistry/">Computational chemistry</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/ecology/">Ecology</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/epigenetics/">Epigenetics</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/genome-annotation/">Genome Annotation</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/imaging/">Imaging</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metabolomics/">Metabolomics</a></td>
<td>4</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metagenomics/">Metagenomics</a></td>
<td>7</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/proteomics/">Proteomics</a></td>
<td>18</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/sequence-analysis/">Sequence analysis</a></td>
<td>2</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/statistics/">Statistics and machine learning</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/transcriptomics/">Transcriptomics</a></td>
<td>23</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/">Variant Analysis</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/visualisation/">Visualisation</a></td>
<td>2</td>
</tr>
</tbody>
</table>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/" rel="nofollow">https://training.galaxyproject.org/training-material/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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