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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32465?offset=170</link>
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<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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</guid>
	<pubDate>Mon, 17 Aug 2020 05:21:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</link>
	<title><![CDATA[SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis]]></title>
	<description><![CDATA[<p><span>SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, &hellip;).</span><br><span>The bioinformatics treatment is based on Vsearch [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/27781170">Rognes 2016</a><span>] which showed to be both accurate and fast [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/26664811">Wescott 2015</a><span>].The statistical analysis is based on DESeq2 R package [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/20979621">Anders and Huber 2010</a><span>] which robustly identifies the differential abundant features as suggested in [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/">McMurdie and Holmes 2014</a><span>] and [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/">Jonsson2016</a><span>]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/25516281">Love 2014</a><span>].</span><br><span>SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_presentation.pdf">here</a><span>&nbsp;and a poster&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_poster.pdf">here</a><span>.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4</a></span></p><p>Address of the bookmark: <a href="https://github.com/aghozlane/shaman" rel="nofollow">https://github.com/aghozlane/shaman</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2423/cancers-origins-revealed</guid>
	<pubDate>Thu, 15 Aug 2013 13:06:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2423/cancers-origins-revealed</link>
	<title><![CDATA[Cancer's origins revealed]]></title>
	<description><![CDATA[<p>Researchers have provided the first comprehensive compendium of mutational processes that drive tumour development. Together, these mutational processes explain most mutations found in 30 of the most common cancer types. This new understanding of cancer development could help to treat and prevent a wide-range of cancers.<br /><br />More at &gt;&gt; http://www.sanger.ac.uk/about/press/2013/130814.html</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7212/bioinformatics-group-at-boku-university</guid>
  <pubDate>Thu, 12 Dec 2013 17:53:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics group at Boku University]]></title>
  <description><![CDATA[
<p>The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine</p>

<p>1. Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and<br />2. Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)</p>

<p>Lab page @ http://bioinf.boku.ac.at/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43548/upgma-worked-example</guid>
	<pubDate>Wed, 13 Oct 2021 06:13:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43548/upgma-worked-example</link>
	<title><![CDATA[UPGMA Worked Example]]></title>
	<description><![CDATA[<p><span>The tabs below include a walkthrough of clustering 7 biological sequences (A-G) using the Unweighted Pair-Group Method with Arithmetic mean (UPGMA) method. Note that UPGMA is actually a generic method and thus the walkthrough could apply to any objects A-G for which pairwise distances can be calculated. A small CGI site for generating a UPGMA tree from a distance matrix can be found&nbsp;</span><a href="http://bioware.soton.ac.uk/upgma.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="http://www.slimsuite.unsw.edu.au/teaching/upgma/" rel="nofollow">http://www.slimsuite.unsw.edu.au/teaching/upgma/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/7216/free-math-books</guid>
	<pubDate>Thu, 12 Dec 2013 19:38:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/7216/free-math-books</link>
	<title><![CDATA[Free math books]]></title>
	<description><![CDATA[<p>Bioinformatics require some match skills, therefore I decided to provide this wonderful math eBooks links to the BOL community.</p>
<p>Please add ur links/bookmarks in comment section.</p><p>Address of the bookmark: <a href="http://physicsdatabase.com/free-math-books/" rel="nofollow">http://physicsdatabase.com/free-math-books/</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33924/figtree</guid>
	<pubDate>Wed, 19 Jul 2017 08:06:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33924/figtree</link>
	<title><![CDATA[FigTree]]></title>
	<description><![CDATA[<p><span>FigTree is designed as a graphical viewer of phylogenetic trees and as a program for producing publication-ready figures. As with most of my programs, it was written for my own needs so may not be as polished and feature-complete as a commercial program. In particular it is designed to display summarized and annotated trees produced by BEAST.</span></p><p>Address of the bookmark: <a href="http://tree.bio.ed.ac.uk/software/figtree/" rel="nofollow">http://tree.bio.ed.ac.uk/software/figtree/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/7387/bioinformatics-software-for-biologists-in-the-genomics-era</guid>
	<pubDate>Sun, 22 Dec 2013 17:31:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/7387/bioinformatics-software-for-biologists-in-the-genomics-era</link>
	<title><![CDATA[Bioinformatics software for biologists in the genomics era]]></title>
	<description><![CDATA[<p>The genome sequencing revolution is approaching a landmark figure of 1000 completely sequenced genomes. Coupled with fast-declining, per-base sequencing costs, this influx of DNA sequence data has encouraged laboratory scientists to engage large datasets in comparative sequence analyses for making evolutionary, functional and translational inferences. However, the majority of the scientists at the forefront of experimental research are not bioinformaticians, so a gap exists between the user-friendly software needed and the scripting/programming infrastructure often employed for the analysis of large numbers of genes, long genomic segments and groups of sequences. We see an urgent need for the expansion of the fundamental paradigms under which biologist-friendly software tools are designed and developed to fulfill the needs of biologists to analyze large datasets by using sophisticated computational methods. We argue that the design principles need to be sensitive to the reality that comparatively small teams of biologists have historically developed some of the most popular biological software packages in molecular evolutionary analysis. Furthermore, biological intuitiveness and investigator empowerment need to take precedence over the current supposition that biologists should re-tool and become programmers when analyzing genome scale datasets.</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/23/14/1713.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/23/14/1713.full</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43683/genview-a-phylogeny-based-comparative-genomics-software-to-analyze-the-genetic-environment-of-genes</guid>
	<pubDate>Tue, 28 Dec 2021 01:49:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43683/genview-a-phylogeny-based-comparative-genomics-software-to-analyze-the-genetic-environment-of-genes</link>
	<title><![CDATA[GEnView: A phylogeny based comparative genomics software to analyze the genetic environment of genes]]></title>
	<description><![CDATA[<p><span>A phylogeny based comparative genomics software to analyze the genetic environment of genes. The user can select one or several taxa and provide one or several reference protein(s). Genomes and plasmids (based on user choice) will be downloaded from the NCBI Assembly/NR database and searched for the respective gene. Alternatively, custom genomes can be provided. User selected stretches (20kbp by default) of the genes genetic environment are extracted, annotated and aligned between all genomes. The sequences are then visualized, enabling comparison of synteny and gene content.</span></p>
<p><span>More at&nbsp;https://pubmed.ncbi.nlm.nih.gov/34951622/</span></p><p>Address of the bookmark: <a href="https://github.com/EbmeyerSt/GEnView" rel="nofollow">https://github.com/EbmeyerSt/GEnView</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7753/jrf-pondicherry-university</guid>
  <pubDate>Fri, 03 Jan 2014 16:48:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF @ PONDICHERRY UNIVERSITY]]></title>
  <description><![CDATA[
<p>PONDICHERRY UNIVERSITY</p>

<p>CENTRE FOR BIOINFORMATICS</p>

<p>PUDUCHERRY</p>

<p>Applications are invited for one Project Assistant to work in the UGC sponsored Research Award "Molecular Docking and Dynamics studies to understand the interacting mechanism of oncogenic 101 protein with its cellular proteins".</p>

<p>The duration for the fellowship is 12months only with consolidated pay ofRs. 5,000 per month.</p>

<p>Application on plain paper with following details: Name, Address, Data of Birth, Father's Name, Nationality, Educational Qualification (SSLC onwards-enclose attested copies of certificate) and Researcb Experience may be addressed to Dr. R. Krishna, Principle Investigator (PI), UGC Research Award, Centre for Bioinformatics, Pondicherry University, Pondicherry - 605 014.</p>

<p>Application should reach in January 261h , 2013.</p>

<p>Essential Qualification: M.Sc. in Bioinformatics/Biophysics with good academic record.</p>

<p>Qualification for Project Fellow:</p>

<p>M.Sc in Bioinformatics/Biophysics.</p>

<p>The person to be considered for appointment as Project Fellow must have second class master degree with a minimum of 55% marks in the subject concerned or a related subject.</p>

<p>The candidate to be appointed as Project Fellows should be below thc age of40 years at the time of appointment.</p>

<p>Desirable Qualification for this Project: Research Experience in Small/Macromolecule Crystallography and Structural Bioinformatics.</p>

<p>For more details, refer the web site: www.pondiuni.edu.in/sites/default/files/BIC-311213.pdf</p>
]]></description>
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