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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30304?offset=1500</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33912/mesquite-a-modular-system-for-evolutionary-analysis</guid>
	<pubDate>Tue, 18 Jul 2017 07:42:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33912/mesquite-a-modular-system-for-evolutionary-analysis</link>
	<title><![CDATA[Mesquite: A modular system for evolutionary analysis]]></title>
	<description><![CDATA[<p><span>Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.</span></p>
<p><span>http://mesquiteproject.wikispaces.com/</span></p><p>Address of the bookmark: <a href="https://github.com/MesquiteProject/MesquiteCore/releases" rel="nofollow">https://github.com/MesquiteProject/MesquiteCore/releases</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34465/rnaseq-data-analysis-links</guid>
	<pubDate>Mon, 27 Nov 2017 16:28:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34465/rnaseq-data-analysis-links</link>
	<title><![CDATA[RNAseq data analysis links !]]></title>
	<description><![CDATA[<p>RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728800/" target="_blank">A survey of best practices for RNA-seq data analysis</a></p><p><a href="http://www.bioconductor.org/help/workflows/rnaseqGene/" target="_blank">RNA-seq workflow: gene-level exploratory analysis and DE</a></p><p><a href="https://github.com/crazyhottommy/RNA-seq-analysis" target="_blank">RNAseq analysis notes from Tommy Tang</a></p><p><a href="http://web.stanford.edu/group/wonglab/doc/RNA-seq-talk-JSM2010.pdf" target="_blank">Analysis of RNA ‐ Seq Data</a></p><p><a href="https://f1000research.com/articles/5-1408/v2" target="_blank">RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR</a></p><p><a href="http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html" target="_blank">Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.</a></p><p><a href="https://www.ebi.ac.uk/training/online/course/ebi-next-generation-sequencing-practical-course/rna-sequencing/rna-seq-analysis-transcriptome" target="_blank">EBI RNA-Seq exercise</a></p><p><a href="https://f1000research.com/articles/5-1574/v1" target="_blank">An open RNA-Seq data analysis pipeline tutorial with an example</a></p><p><a href="https://ycl6.gitbooks.io/rna-seq-data-analysis/rna-seq_analysis_workflow.html" target="_blank">RNA-Seq Analysis Workflow</a></p><p><a href="http://www.nature.com/nprot/journal/v11/n9/full/nprot.2016.095.html" target="_blank">Transcript-level expression analysis of RNA-seq experiments</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40489/machine-learning-training-and-courses-in-bioinformatics</guid>
	<pubDate>Tue, 31 Dec 2019 19:33:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40489/machine-learning-training-and-courses-in-bioinformatics</link>
	<title><![CDATA[Machine learning training and courses in bioinformatics !]]></title>
	<description><![CDATA[<p>Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden Markov models, and Bayesian networks) for biological sequence analysis and systems biology. Other machine learning techniques, such as Naive bayes, neural networks and SVMs will only be covered briefly.</p>
<p>More at&nbsp;http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/</p>
<p>More tutorial at&nbsp;</p>
<p><a href="http://calla.rnet.missouri.edu/cheng_courses/mlbioinfo/mlbioinfo.htm">http://calla.rnet.missouri.edu/cheng_courses/mlbioinfo/mlbioinfo.htm</a></p>
<p><a href="http://www.raetschlab.org/lectures/MLBioinformatics">http://www.raetschlab.org/lectures/MLBioinformatics</a></p>
<p><a href="http://www.raetschlab.org/lectures/bertinoro08">http://www.raetschlab.org/lectures/bertinoro08</a></p>
<p>Book at&nbsp;</p>
<p><a href="https://personal.utdallas.edu/~pradiptaray/teaching/7_deep_learning_bioinfo.pdf">https://personal.utdallas.edu/~pradiptaray/teaching/7_deep_learning_bioinfo.pdf</a></p><p>Address of the bookmark: <a href="http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/" rel="nofollow">http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/42877/bioinformatician-on-valentines-day</guid>
	<pubDate>Sun, 14 Feb 2021 11:36:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/42877/bioinformatician-on-valentines-day</link>
	<title><![CDATA[Bioinformatician on Valentine's Day]]></title>
	<description><![CDATA[<p>Once asked to a bioinformatician "How is ur Valentine's Day?"</p><blockquote><p>Bioinformatician replied:</p><p>if ($date == "Valentine's Day" &amp;&amp; $me =! Bioinformatician) {</p><p>rose_day(); promise_day(); kiss_day();</p><p>}</p><p>else {</p><p>hack_genome(); ko-fi(); youtube(); do_scripting(); sleep();</p><p>)</p></blockquote>]]></description>
	<dc:creator>BioQueen</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42141/dbt-biotechnology-eligibility-test-bet-2020</guid>
	<pubDate>Fri, 21 Aug 2020 09:17:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42141/dbt-biotechnology-eligibility-test-bet-2020</link>
	<title><![CDATA[DBT BIOTECHNOLOGY ELIGIBILITY TEST (BET) 2020]]></title>
	<description><![CDATA[<p><span>Ministry of Science &amp;Technology, Govt. of India</span></p><p><span>DBT-Junior Research Fellowship (DBT-JRF) in Biotechnology (2020)</span></p><p><span><span>BIOTECHNOLOGY ELIGIBILITY TEST (BET) 2020</span></span></p><p>Applications are invited from bonafide Indian citizens, residing in India for award of &ldquo;DBT-Junior Research Fellowship&rdquo; (DBT-JRF) for pursuing research in frontier areas of Biotechnology and Life Sciences. The candidates will be selected through &ldquo;Biotechnology Eligibility Test (BET)&rdquo;. Based on the performance in BET, two categories of merit list will be prepared (Category-I and Category-II). Government of India norms for reservation will be followed for selection. Candidates selected under category-I will be eligible to avail fellowship under the programme. These will be tenable at any University/Institute in India where the selected candidate registers for PhD Programme. Candidates selected under Category-II will be eligible to be appointed in any DBT sponsored project and avail fellowship from the project equivalent to NET/GATE, subject to selection through institutional selection process. There will be no binding on Principal Investigators of DBT sponsored projects to select JRF for their project from category-II list. Selection in category-II will not entitle student for any fellowship from DBT-JRF programme.</p><p><span>ELIGIBILITY</span></p><p><span>Qualification</span>: M.Sc./ M.Tech./ M.V.Sc. or equivalent degree/ Integrated BS-MS/ B.E./ B.Tech. in any discipline of&nbsp;<a href="https://www.biotecnika.org/category/jobs/biotech-jobs/">Biotechnology</a>, M.Sc./ M.Tech. Bioinformatics/ Computational Biology, students admitted under DBT supported Postgraduate Teaching Programs. M.Sc. Life Science/ Bioscience/ Zoology/ Botany/ Microbiology/ Biochemistry/ Biophysics and Masters in Allied areas of Biology/Life Sciences. Candidates appearing in the final year examination are also eligible to apply.</p><p><span>Marks</span>: Minimum 60% marks for General, EWS &amp; OBC category and 55% for SC/ ST/ Differently abled in aggregate (or equivalent grade).</p><p><span>Age Limit</span>: Upto 28 years as on the last date of application for General &amp; EWS category. Age relaxation of up to 5 years (33 years) for SC/ ST/ Differently Abled/ women candidates and upto 3 years (31 years) for OBC (Non-Creamy Layer) candidates.</p><p>For detailed procedure for filling the application form, payment of application fee and uploading of required documents/ certificates in the prescribed format, please visit:&nbsp;<span><a href="http://rcb.res.in/BET2020" target="_blank">http://rcb.res.in/BET2020</a></span>. A non-refundable and non-transferable application fee of Rs. 1000/-is payable online by General/ OBC/ EWS candidates and Rs 250/- by SC/ ST/ Differently abled candidates.</p><p><span>IMPORTANT DATES</span></p><table width="691">
<tbody>
<tr>
<td>Online Registration Start</td>
<td><span>April 20, 2020</span></td>
</tr>
<tr>
<td>Online Registration Close</td>
<td><span>May 18, 2020</span></td>
</tr>
<tr>
<td>BET 2020</td>
<td><span>June 30, 2020 (Tuesday)* Tentative</span></td>
</tr>
<tr>
<td>Display of question paper and answer key on website</td>
<td><span>June 30, 2020</span></td>
</tr>
<tr>
<td>Last date of accepting representation of any discrepancy in Question paper &amp; Answer key</td>
<td><span>July 03, 2020</span></td>
</tr>
<tr>
<td>Declaration of BET 2020 Result</td>
<td><span>July 20, 2020</span></td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38462/egad-ultra-fast-functional-analysis-of-gene-networks</guid>
	<pubDate>Fri, 14 Dec 2018 04:10:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38462/egad-ultra-fast-functional-analysis-of-gene-networks</link>
	<title><![CDATA[EGAD: Ultra-fast functional analysis of gene networks]]></title>
	<description><![CDATA[<p><span>With the EGAD (Extending &lsquo;Guilt-by-Association&rsquo; by Degree) package, we present a series of highly efficient tools to calculate functional properties in networks based on the guilt-by-association principle. These allow rapid controlled comparisons and analyses. Two of the core features are: a function prediction algorithm which is fully vectorized (neighbor_voting), allowing network characterization across even thousands of functional groups to be accomplished in minutes in cross-validation and an analytic determination of the optimal prior to guess candidates genes across multiple functional sets (calculate_multifunc, auc_multifunc).</span></p><p>Address of the bookmark: <a href="https://github.com/sarbal/EGAD" rel="nofollow">https://github.com/sarbal/EGAD</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42187/scientist-b-at-aiims-new-delhi-delhi</guid>
  <pubDate>Thu, 03 Sep 2020 07:04:11 -0500</pubDate>
  <link></link>
  <title><![CDATA[Scientist B at AIIMS, New Delhi, Delhi]]></title>
  <description><![CDATA[
<p>Scientist B at AIIMS, New Delhi, Delhi</p>

<p>Overview<br />Applications are invited from eligible candidates for the following position under Meity funded research project entitled: Artifical Intelligence in Oncology, Harnsessing big data and advanced computing to provide personalized diganosis and treatment for cancer patients purely on contractual basis</p>

<p>Scientist B</p>

<p>Salary: Rs.80,000/-</p>

<p>Qualification: 1st Class Masters Degree in Bioinformatics/ Computer Science/ Statistics with Ph.D in relevant subject from a recognized University with experience in Machine learning/ AI project plus two years research experience</p>

<p>Age: Upto 40 years</p>

<p>Details<br />Experience:2 Years<br />Location:New Delhi<br />Education:1st Class Masters Degree<br />SALARY: Rs.80,000/-<br />Key Skills: Research Fellowship<br />Desired Profile<br />Two years research experience</p>

<p>Company: AIIMS<br />All India Institute of Medical Sciences, New Delhi is a medical school, hospital and public medical research university</p>

<p>More at https://www.aiims.edu/en/notices/recruitment/aiims-recruitment.html?id=10844<br />PDF https://www.aiims.edu/images/pdf/recruitment/advertisement/Post_BioChem_22_08_20.PDF</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42265/doctoral-researcher-phd-in-computational-biology-biostatistics-at-luxembourg-centre-for-systems-biomedicine-lcsb</guid>
  <pubDate>Sun, 25 Oct 2020 22:59:54 -0500</pubDate>
  <link></link>
  <title><![CDATA[Doctoral researcher (PhD) in Computational Biology / Biostatistics at Luxembourg Centre for Systems Biomedicine (LCSB)]]></title>
  <description><![CDATA[
<p>Contract Type: Fixed Term Contract<br />Work Hours: Full Time 40.0 Hours per Week<br />Location: Belval<br />Student and employee status (36 months studies programme, as per university standards) with project funding available for up to 48 months<br />36 months fixed-term contract (renewable depending on thesis progress evaluation)<br />Job Reference: UOL03604<br />Further Information<br />Applications should be submitted online and include:</p>

<p>A detailed Curriculum vitae<br />A motivation letter, including a brief description of past research experience and future interests, as well as the earliest possible starting date<br />Copies of degree certificates and transcripts<br />Name and contact details of at least two referees<br />Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered.</p>

<p>*gn=gender neutral.</p>

<p>More at https://recruitment.uni.lu/en/details.html?id=QMUFK026203F3VBQB7V7VV4S8&amp;nPostingID=54876&amp;nPostingTargetID=74639&amp;mask=karriereseiten&amp;lg=UK</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41475/proteoclade-a-taxonomic-toolkit-for-multi-species-and-metaproteomic-analysis</guid>
	<pubDate>Wed, 18 Mar 2020 14:27:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41475/proteoclade-a-taxonomic-toolkit-for-multi-species-and-metaproteomic-analysis</link>
	<title><![CDATA[ProteoClade: A taxonomic toolkit for multi-species and metaproteomic analysis]]></title>
	<description><![CDATA[<p>ProteoClade is a Python library for&nbsp;<span>taxonomic-based annotation and quantification of bottom-up proteomics data</span>. It is designed to be user-friendly, and has been optimized for speed and storage requirements.</p>
<p>ProteoClade helps you analyze two general categories of experiments:</p>
<ol>
<li>
<p><span><em>Targeted Database</em>&nbsp;Searches:</span>&nbsp;Experiments in which a limited number of species are defined ahead of time, such as those involving Patient-Derived Xenografts (PDXs) or host-pathogen interactions. Reference protein sequence databases are used for targeted searches (ex: using Mascot, MaxQuant).</p>
</li>
<li>
<p><span><em>De Novo</em>&nbsp;Searches:</span>&nbsp;Experiments in which the organisms are unspecified ahead of time or involve samples of high taxonomic complexity. Mass spectra are analyzed in the absence of a reference database (ex: using PEAKS, PepNovo).</p>
</li>
</ol>
<p>ProteoClade scales from two organisms to every organism in UniProt. Please&nbsp;<a href="https://proteoclade.readthedocs.io/">refer to the complete documentation at proteoclade.readthedocs.io</a>&nbsp;for installation, a user's guide, and examples.</p>
<p><a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007741">https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007741</a></p><p>Address of the bookmark: <a href="https://github.com/HeldLab/ProteoClade" rel="nofollow">https://github.com/HeldLab/ProteoClade</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42402/two-postdoc-positions-to-study-multiscale-genome-evolution-and-cephalopod-gene-regulation-university-of-vienna-austria</guid>
  <pubDate>Thu, 17 Dec 2020 11:45:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[Two postdoc positions to study multiscale genome evolution and cephalopod gene regulation (University of Vienna, Austria)]]></title>
  <description><![CDATA[
<p>Vienna Biocenter are seeking two postdoctoral researchers to join our team and work on the ERC funded project "METASCALE: Modes of genome evolution during major metazoan transitions". The task of both positions will be to study co-evolutionary trends within animal genomes and their association with the emergence of new gene regulation. Our group employs methods of comparative and regulatory genomics to study the regulatory impact of transitions in animal genome architecture. More recently, we have identified a major genome reorganization in the "smart" coleoid cephalopod molluscs (squid, octopus, cuttlefish) that, together with other genomic changes, potentially comprises a unique path or mode of genome evolution among animals. We are thus interested in quantifying these modes of genome evolution across all available animal genomes and to test whether their shifts are associated with the emergence of novel regulation (e.g., in cephalopods). One of our main model species is the Hawaiian bobtail squid species Euprymna scolopes.  The tasks of the two candidates will be complimentary and highly collaborative with one position focusing on comparative genomics analyses across all metazoans and the other position on regulatory genomics in the squid. A solid background in in bioinformatics and comparative genomics is highly desired for the first position, whereas the second position will benefit from experience in molecular and regulatory genomics methods such as HiC, ATAC-seq, RNA-seq or single cell transcriptomics.</p>

<p>The postdocs will join an international group and network of researchers at the University of Vienna studying a diverse range of species and questions in molecular evolution, development, morphology and genomics. Our group is also part of the large evolVienna network of more than 50 evolutionary biology labs in Vienna, across several universities and research institutes. Our Faculty will be relocating to a new campus at the Vienna Biocenter in summer 2021 (https://biologiezentrum.univie.ac.at/en/). Vienna is a vibrant historic European capital with a high QOL. Information about postdoctoral salaries in Austria can be found on this webpage: https://www.fwf.ac.at/en/research-funding/personnel-costs/</p>

<p>Earliest start date will be after July 2021. Initial term of employment is for two years with the possibility of extension. Remote working, at least initially, is a possibility.</p>

<p>Requirements:<br />- PhD degree or equivalent by the start date <br />- Publishing record in peer-reviewed journals or evidence thereof <br />- At least 2 letters of support</p>

<p>Applications including a letter of motivation should be submitted via the Job Center to the University of Vienna (https://personalwesen.univie.ac.at/en/jobs-recruiting/job-center/,<br />job reference number 11615).</p>

<p>Application deadline: January 15th 2021.<br />Application link: https://univis.univie.ac.at/ebewerbung</p>
]]></description>
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