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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29142?offset=1560</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<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>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43447/rna-seq-workflow-gene-level-exploratory-analysis-and-differential-expression</guid>
	<pubDate>Sat, 09 Oct 2021 07:59:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43447/rna-seq-workflow-gene-level-exploratory-analysis-and-differential-expression</link>
	<title><![CDATA[RNA-seq workflow: gene-level exploratory analysis and differential expression]]></title>
	<description><![CDATA[<p><span>Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count datasets for downstream analysis. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.</span></p><p>Address of the bookmark: <a href="http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html" rel="nofollow">http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43999/tools-for-differential-expression-analysis</guid>
	<pubDate>Tue, 08 Nov 2022 03:40:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43999/tools-for-differential-expression-analysis</link>
	<title><![CDATA[Tools for Differential expression analysis]]></title>
	<description><![CDATA[<p><span>apeglm</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/apeglm.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/apeglm.html</a></p><p><span>ashr</span>&nbsp;-&nbsp;<a href="https://github.com/stephens999/ashr" target="_blank">https://github.com/stephens999/ashr</a>,&nbsp;<a href="https://cran.r-project.org/web/packages/ashr/index.html" target="_blank">https://cran.r-project.org/web/packages/ashr/index.html</a></p><p><span>consensusDE</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/consensusDE.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/consensusDE.html</a></p><p><span>DESeq2</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/DESeq2.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/DESeq2.html</a></p><p><span>edgeR</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/edgeR.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/edgeR.html</a></p><p><span>limma</span>&nbsp;-&nbsp;<a href="https://kasperdanielhansen.github.io/genbioconductor/html/limma.html" target="_blank">https://kasperdanielhansen.github.io/genbioconductor/html/limma.html</a>&nbsp;&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/limma.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/limma.html</a></p><p><span>MetaCycle</span>&nbsp;-&nbsp;<a href="https://cran.r-project.org/web/packages/MetaCycle/index.html" target="_blank">https://cran.r-project.org/web/packages/MetaCycle/index.html</a>,&nbsp;<a href="https://github.com/gangwug/MetaCycle" target="_blank">https://github.com/gangwug/MetaCycle</a></p><p><span>RUVSeq</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/RUVSeq.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/RUVSeq.html</a></p><p><span>SARTools</span>&nbsp;-&nbsp;<a href="https://github.com/PF2-pasteur-fr/SARTools" target="_blank">https://github.com/PF2-pasteur-fr/SARTools</a></p><p><span>tximport</span>&nbsp;-&nbsp;<a href="https://github.com/mikelove/tximport" target="_blank">https://github.com/mikelove/tximport</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Sat, 08 Jun 2024 16:25:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a flexible pipeline for complete analysis of bacterial genomes]]></title>
	<description><![CDATA[<p>Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p>Bactopia was inspired by&nbsp;<a href="https://staphopia.github.io/">Staphopia</a>, a workflow we (Tim Read and myself) released that is targeted towards&nbsp;<em>Staphylococcus aureus</em>&nbsp;genomes. Using what we learned from Staphopia and user feedback, Bactopia was developed from scratch with usability, portability, and speed in mind from the start.</p>
<p>Bactopia uses&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>&nbsp;to manage the workflow, allowing for support of many types of environments (e.g. cluster or cloud). Bactopia allows for the usage of many public datasets as well as your own datasets to further enhance the analysis of your sequencing. Bactopia only uses software packages available from&nbsp;<a href="https://bioconda.github.io/">Bioconda</a>&nbsp;and&nbsp;<a href="https://conda-forge.org/">Conda-Forge</a>&nbsp;to make installation as simple as possible for&nbsp;<em>all</em>&nbsp;users.</p>
<p>To highlight the use of&nbsp;<a href="https://bactopia.github.io/latest/full-guide/">Bactopia</a>&nbsp;and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>, we performed an analysis of 1,664 public&nbsp;<em>Lactobacillus</em>&nbsp;genomes, focusing on&nbsp;<em>Lactobacillus crispatus</em>, a species that is a common part of the human vaginal microbiome. The results from this analysis are published in mSystems under the title:&nbsp;<em><a href="https://doi.org/10.1128/mSystems.00190-20">Bactopia: a flexible pipeline for complete analysis of bacterial genomes</a></em></p>
<p><a href="https://bactopia.github.io/latest/assets/bactopia-workflow.png"><img src="https://bactopia.github.io/latest/assets/bactopia-workflow.png" alt="Bactopia Workflow" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://bactopia.github.io/latest/" rel="nofollow">https://bactopia.github.io/latest/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <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>
</item>

<item>
  <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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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34718/dipspades-assembler-for-highly-polymorphic-diploid-genomes</guid>
	<pubDate>Wed, 20 Dec 2017 18:35:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34718/dipspades-assembler-for-highly-polymorphic-diploid-genomes</link>
	<title><![CDATA[dipSPAdes: Assembler for Highly Polymorphic Diploid Genomes.]]></title>
	<description><![CDATA[<p><span>While the number of sequenced diploid genomes have been steadily increasing in the last few years, assembly of highly polymorphic (HP) diploid genomes remains challenging. As a result, there is a shortage of tools for assembling HP genomes from the next generation sequencing (NGS) data. The initial approaches to assembling HP genomes were proposed in the pre-NGS era and are not well suited for NGS projects. To address this limitation, we developed the first de Bruijn graph assembler, dipSPAdes, for HP genomes that significantly improves on the state-of-the-art assemblers for HP diploid genomes.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pubmed/25734602" rel="nofollow">https://www.ncbi.nlm.nih.gov/pubmed/25734602</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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