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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27850?offset=10</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27847/anvio</guid>
	<pubDate>Thu, 16 Jun 2016 18:15:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27847/anvio</link>
	<title><![CDATA[Anvio]]></title>
	<description><![CDATA[<p>In a nutshell</p>
<p>Anvi&rsquo;o is an analysis and visualization platform for &lsquo;omics data.</p>
<p>Please find the methods paper here: https://peerj.com/articles/1319/</p>
<p>Anvi&rsquo;o would not have been possible without the help of many people who directly or indirectly contributed to its development. Here is the acknowledgements section of our methods paper</p>
<p><span>An analysis and visualization platform for 'omics data</span><span>&nbsp;</span><span><a href="http://merenlab.org/projects/anvio">http://merenlab.org/projects/anvio</a></span></p>
<p><span>Paper&nbsp;https://peerj.com/articles/1839/</span></p><p>Address of the bookmark: <a href="https://github.com/meren/anvio" rel="nofollow">https://github.com/meren/anvio</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28997/braker-pipeline-for-fully-automated-prediction-of-protein-coding-genes-with-genemark-eset-and-augustus-in-novel-eukaryotic-genomes</guid>
	<pubDate>Thu, 01 Sep 2016 08:02:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28997/braker-pipeline-for-fully-automated-prediction-of-protein-coding-genes-with-genemark-eset-and-augustus-in-novel-eukaryotic-genomes</link>
	<title><![CDATA[BRAKER: pipeline for fully automated prediction of protein coding genes with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.</span></p>
<p>http://www.ncbi.nlm.nih.gov/pubmed/26559507</p><p>Address of the bookmark: <a href="http://bioinf.uni-greifswald.de/bioinf/braker/" rel="nofollow">http://bioinf.uni-greifswald.de/bioinf/braker/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot</guid>
	<pubDate>Mon, 13 Feb 2017 09:47:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot</link>
	<title><![CDATA[Ideoplot]]></title>
	<description><![CDATA[<p>Simple ideogram plotting and annotation in R.</p>
<p>Basic usage:</p>
<p>Rscript Ideoplot.R --heatmap hm.bed --annotate annotations.bed --out ideogram.pdf<br> -or-<br> Rscript Ideoplot.R --annotate annotations.bed</p>
<pre>Options
  --ideobed, i      A bed file of reference contig lengths/chromosome names
  --heatmap, -h     Fill chromosomes with normalized heatmap
                   (described below)
  --annotate, -a    Add character annotations.
  --out, -o         PDF output name.
  --stripes, -s     Specify a file containing the layout of the
                    annotations (description below)
  --bars, -b        Add track annotations
  --reference, -f   Either hg19, or hg38
  --topdown, r      Flag, when set, flips the orientation (P arms
                    drawn on top).
</pre><p>Address of the bookmark: <a href="https://github.com/mchaisso/Ideoplot" rel="nofollow">https://github.com/mchaisso/Ideoplot</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 08:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</link>
	<title><![CDATA[R and Bioconductor Tutorial]]></title>
	<description><![CDATA[<p>This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that &nbsp;biologists need to perform &nbsp;some basic analysis: &nbsp;load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).</p>
<p>You can add more tutorial links in comments if found new pages.</p><p>Address of the bookmark: <a href="http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual" rel="nofollow">http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43292/bioinformatics-scientist-production-bioinformatics-south-san-francisco-ca</guid>
  <pubDate>Thu, 19 Aug 2021 08:45:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA]]></title>
  <description><![CDATA[
<p>wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.</p>

<p>More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4728/3-days-intensive-course-on-understanding-omics-data-in-basel-switzerland-19-21st-november</guid>
  <pubDate>Mon, 23 Sep 2013 10:46:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[3 days intensive course on Understanding 'omics data in Basel, Switzerland, 19-21st November]]></title>
  <description><![CDATA[
<p>Benefits for the participants</p>

<p>- Plan more efficient experiments<br />- Correctly interpret results<br />- Communicate results in publications more effectively</p>

<p>The course focus is on methodologies, not on particular software tools. After the course participants should be able to apply the methods in their respective environment. However, during the course, hands-on sessions will be performed using the Genedata Expressionist® software, which enables participants to quickly apply the discussed methods and visualize results. No previous knowledge on Expressionist® is required; access to the software is free of charge during the course.</p>

<p>More @ http://www.dixa-fp7.eu/dixa-training/dixa-training-agenda/genedata-academy#!</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35800/scikit-bio%E2%84%A2-is-an-open-source-bsd-licensed-python-package-providing-data-structures-algorithms-and-educational-resources-for-bioinformatics</guid>
	<pubDate>Fri, 02 Mar 2018 04:29:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35800/scikit-bio%E2%84%A2-is-an-open-source-bsd-licensed-python-package-providing-data-structures-algorithms-and-educational-resources-for-bioinformatics</link>
	<title><![CDATA[scikit-bio™ is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics.]]></title>
	<description><![CDATA[<p><span>scikit-bio is currently in beta. We are very actively developing it, and&nbsp;</span><strong>backward-incompatible interface changes can and will arise</strong><span>. To avoid these types of changes being a surprise to our users, our public APIs are decorated to make it clear to users when an API can be relied upon (stable) and when it may be subject to change (experimental). See the&nbsp;</span><a href="https://github.com/biocore/scikit-bio/blob/master/doc/source/user/api_stability.rst">API stability docs</a><span>&nbsp;for more details, including what we mean by&nbsp;</span><em>stable</em><span>&nbsp;and&nbsp;</span><em>experimental</em><span>&nbsp;in this context.</span></p><p>Address of the bookmark: <a href="http://scikit-bio.org/" rel="nofollow">http://scikit-bio.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/40957/multiple-phd-positions</guid>
  <pubDate>Sun, 09 Feb 2020 03:10:28 -0600</pubDate>
  <link></link>
  <title><![CDATA[Multiple PhD positions]]></title>
  <description><![CDATA[
<p>14 PhD positions in the EU Horizon 2020 Marie Skłodowska-Curie Project PRECODE:<br />International training network which sets a joint research programme to train a new generation of leading scientists in model systems and methods for the development of new therapies for pancreatic cancer (PaCa)</p>

<p>http://precode-project.eu/jobs-board/#1572451761376-39d75f63-c6fb</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/10739/science-for-life-laboratory-scilifelab-sweden</guid>
  <pubDate>Sat, 10 May 2014 06:22:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Science for Life Laboratory (SciLifeLab)-Sweden]]></title>
  <description><![CDATA[
<p>Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.</p>

<p>Webpage : https://www.scilifelab.se/about-us/<br />Opportunity: https://www.scilifelab.se/about-us/career/</p>
]]></description>
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