<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31353?offset=1320</link>
	<atom:link href="https://bioinformaticsonline.com/related/31353?offset=1320" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44900/pegas-a-comprehensive-bioinformatic-solution-for-pathogenic-bacterial-genomic-analysis</guid>
	<pubDate>Mon, 01 Sep 2025 01:18:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44900/pegas-a-comprehensive-bioinformatic-solution-for-pathogenic-bacterial-genomic-analysis</link>
	<title><![CDATA[PeGAS: A Comprehensive Bioinformatic Solution for Pathogenic Bacterial Genomic Analysis]]></title>
	<description><![CDATA[<p><span>This is PeGAS, a powerful bioinformatic tool designed for the seamless quality control, assembly, and annotation of Illumina paired-end reads specific to pathogenic bacteria. This tool integrates state-of-the-art open-source software to provide a streamlined and efficient workflow, ensuring accurate insights into the genomic makeup of pathogenic microbial strains.</span></p>
<p><span><img src="https://github.com/liviurotiul/PeGAS/raw/main/Features.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/liviurotiul/PeGAS" rel="nofollow">https://github.com/liviurotiul/PeGAS</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29263/srf-bioinformatics-at-bose-institute-india</guid>
  <pubDate>Thu, 29 Sep 2016 09:39:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics at Bose Institute, India]]></title>
  <description><![CDATA[
<p>Advt. No. S/DPB(CB)/17/2016-17 <br />Junior Research Assistant/ Senior Research Assistant  Job vacancies in Bose Institute on temporary basis<br />Project Title : “Genome wide transcriptome analysis to identity MYMIV-stress related genomic resources of blackgram”<br />Junior Research Assistant <br />Qualification : Good academic record in B.Sc. and M.Sc. in Botany or Biotechnology from reputed Universities. Must have good practical hand, this should be certified by two Senior/reputed PG teachers on a scale of 10. <br />Desirable : Preference will be given to those who already have some research experience (for at least 2 months). <br />Consolidated Pay : Rs. 16,400/- p.m. <br />Age Limit : Below 28 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).<br />Senior Research Assistant <br />Qualification : B.Sc. in Biotechnology and M.Sc. in Biotechnology or Bioinformatics. Hands on training in Bioinformatics. At least two Research Publications with Bioinformatics components. <br />Desirable : Preference will be given to the candidates who have previous experience in Next Gen Sequencing data analysis of genomic/transcriptome/miRNA. <br />Consolidated Pay : Rs. 18,700/- p.m.  <br />Age Limit : Below 30 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).</p>

<p>http://www.boseinst.ernet.in/advertisement.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34463/single-cell-rnaseq-data-analysis-tutorial</guid>
	<pubDate>Mon, 27 Nov 2017 16:24:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34463/single-cell-rnaseq-data-analysis-tutorial</link>
	<title><![CDATA[Single Cell RNAseq data analysis tutorial !!]]></title>
	<description><![CDATA[<ul>
<li>A major breakthrough (replaced microarrays) in the late 00&rsquo;s and has been widely used since</li>
<li>Measures the&nbsp;average expression level&nbsp;for each gene across a large population of input cells</li>
<li>Useful for comparative transcriptomics, e.g.&nbsp;samples of the same tissue from different species</li>
<li>Useful for quantifying expression signatures from ensembles, e.g.&nbsp;in disease studies</li>
<li>Insufficient&nbsp;for studying heterogeneous systems, e.g.&nbsp;early development studies, complex tissues (brain)</li>
<li>Does&nbsp;not&nbsp;provide insights into the stochastic nature of gene expression</li>
</ul><p>Following are the useful links:</p><p><a href="http://hemberg-lab.github.io/scRNA.seq.course/scRNA-seq-course.pdf" target="_blank">Single Cell RNAseq data analysis Tutorial</a></p><p><a href="https://f1000research.com/articles/5-2122/v2" target="_blank">A step-by-step workflow for low-level analysis of single-cell RNA-seq data</a></p><p><a href="https://www.bioconductor.org/help/workflows/simpleSingleCell/" target="_blank">A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor</a></p><p>SCell: single-cell RNA-seq analysis software</p><p><a href="https://github.com/diazlab/SCell">https://github.com/diazlab/SCell</a></p><p>Beta-Poisson model for single-cell RNA-seq data analyses</p><p><a href="https://github.com/nghiavtr/BPSC">https://github.com/nghiavtr/BPSC</a></p><p>Sincera: A Computational Pipeline for Single Cell RNA-Seq Profiling Analysis</p><p><a href="https://research.cchmc.org/pbge/sincera.html">https://research.cchmc.org/pbge/sincera.html</a></p><p>SC3 &ndash; consensus clustering of single-cell RNA-Seq data</p><p><a href="http://biorxiv.org/content/early/2016/09/02/036558">http://biorxiv.org/content/early/2016/09/02/036558</a></p><p>Citrus: A toolkit for single cell sequencing analysis</p><p><a href="http://biorxiv.org/content/early/2016/09/14/045070">http://biorxiv.org/content/early/2016/09/14/045070</a></p><p>Single-Cell Resolution of Temporal Gene Expression during Heart Development</p><p><a href="http://www.cell.com/developmental-cell/fulltext/S1534-5807%2816%2930682-7">http://www.cell.com/developmental-cell/fulltext/S1534-5807(16)30682-7</a></p><p>Scalable latent-factor models applied to single-cell RNA-seq data separate biological drivers from confounding effects</p><p><a href="http://biorxiv.org/content/early/2016/11/15/087775">http://biorxiv.org/content/early/2016/11/15/087775</a></p><p>Single cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes</p><p><a href="http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract">http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract</a></p><p>SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation</p><p><a href="http://biorxiv.org/content/early/2016/11/21/088856">http://biorxiv.org/content/early/2016/11/21/088856</a></p><p>SCOUP is a probabilistic model to analyze single-cell expression data during differentiation</p><p><a href="https://github.com/hmatsu1226/SCOUP">https://github.com/hmatsu1226/SCOUP</a></p><p>scLVM is a modelling framework for single-cell RNA-seq data</p><p><a href="https://github.com/PMBio/scLVM">https://github.com/PMBio/scLVM</a></p><p>Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories</p><p><a href="https://github.com/jw156605/SLICER">https://github.com/jw156605/SLICER</a></p><p>SinQC: A Method and Tool to Control Single-cell RNA-seq Data Quality</p><p><a href="http://www.morgridge.net/SinQC.html">http://www.morgridge.net/SinQC.html</a></p><p>TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis</p><p><a href="https://github.com/zji90/TSCAN">https://github.com/zji90/TSCAN</a></p><p>Visualization and cellular hierarchy inference of single-cell data using SPADE</p><p><a href="http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html">http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html</a></p><p>OEFinder: Identify ordering effect genes in single cell RNA-seq data</p><p><a href="https://github.com/lengning/OEFinder">https://github.com/lengning/OEFinder</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29953/traineeship-at-jawaharlal-nehru-tropical-botanic-garden-and-research-institute</guid>
  <pubDate>Fri, 25 Nov 2016 08:07:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Traineeship at JAWAHARLAL NEHRU TROPICAL BOTANIC GARDEN AND RESEARCH INSTITUTE]]></title>
  <description><![CDATA[
<p>JAWAHARLAL NEHRU TROPICAL BOTANIC GARDEN AND RESEARCH INSTITUTE</p>

<p>THIRUVANANTHAPURAM - 695 562</p>

<p>Traineeship on Bioinformatics(2)</p>

<p>First class M.Sc. Bioinformatics/ Agriculture/ Botany/ Biotechnology @ Rs.8000</p>

<p>Those candidates who fulfill the above criteria may attend a walk PCC Coordinator in-interview on 28th November 2016 at Saraswathy Thangavelu center, JNTBGRI, Puthenthope, Thiruvananthapuram between at 10.00 am and 2.00 pm with all the relevant document and testimonials.</p>

<p>No TA/DA will be given to candidates for attending the interview.</p>

<p>More Info : http://jntbgri.res.in/downloads/traineeship_notification.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29588/research-associate-and-junior-research-fellow-at-north-eastern-hill-university-tura-meghalaya</guid>
  <pubDate>Fri, 28 Oct 2016 09:54:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate and Junior Research Fellow at North-Eastern Hill University - Tura, Meghalaya]]></title>
  <description><![CDATA[
<p>Research Associate and Junior Research Fellow <br />North-Eastern Hill University - Tura, Meghalaya <br />₹18,000 a month<br />Applications are invited for the post of Research Associate and JRF in the DBT sponsored Bioinformatics Infrastructure Facility (BIF), posts are purely temporary and terminable at anytime without prior notice or assigning any reason thereof. </p>

<p>Research Associate : <br />Essential Qualification: Ph.D in Bioinformatics/Biotechnology/Life Science from a reocngised univeristy/institute <br />Pay: Rs.36000-/- + Admissible 10% HRA per month <br />Age: Below 35 years </p>

<p>Junior Research Fellow <br />Essential Qualification: M.Sc in Bioinformatics/Biotechnology/Life Science from a reocngised univeristy/institute <br />Pay: Rs.18000-/- + per month <br />Age: Below 35 years </p>

<p>Last date for receving application by mail or post is 08.11.2016 </p>

<p>Company Info. <br />North-Eastern Hill University </p>

<p>Bioinformatics Infrastructure Facility (BIF) Department of RDAP North-Eastern Hill University, Tura Campus Tura-794002, Meghalaya</p>

<p>More at http://www.nehu.ac.in/Advertisements/BIFTuraManpowerAdvt_25102016.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29624/information-officer-at-iiar-gujarat</guid>
  <pubDate>Fri, 04 Nov 2016 05:19:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Information Officer at IIAR, Gujarat]]></title>
  <description><![CDATA[
<p>Walk in interview at 10.30 am on Nov 11th, 2016 for the following position at Distributed Information Sub-Centre (DISC) established by Dept. Of Biotechnology, Govt. of India at Indian Institute of Advanced Research, Gandhinagar, Gujarat</p>

<p>Position (scale), qualifications and experience</p>

<p>1. Information Officer (Rs 8000-275-13500): one post <br />Qualifications and experience: MCA, Post-Graduate in any field of biosciences, bioinformatics with at least two years of experience in working in a bioinformatics setup and good knowledge of linux operating system and computer networking.</p>

<p>General terms and conditions: <br />1. The above engagements is presently till March 31st, 2017. However on extension of project grant and satisfactory performance of the candidate, your services can be extended beyond March 31st, 2017 based on the terms and conditions of extension of project grant.</p>

<p>2. It is not an appointment with the institute and will not confer any right to the incumbent to any claim implicit or explicit on any position.</p>

<p>3.No TA/DA will be paid for attending the interview. Outstation candidates have to make their own arrangement for their stay.</p>

<p>4.Candidates, appearing in the walk-in interview are requested to bring the hard copy of application addressed to Dr. Anju Pappachan with latest photograph, CV mentioning qualifications, work experience and name of two referees and one page write up as to why you would like to join the project.</p>

<p>Address: <br />Dr. Anju Pappachan <br />Indian Institute of Advanced Research (IIAR), <br />University  and Institute of Advanced Research, <br />The Puri Foundation for Education in India, <br />Koba Institutional Area, <br />Gandhinagar- 382 007, Gujarat, India. Contact no. 079-30514152 <br />e-mail- anju@iiar.res.in</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29849/ra-bioinformatics-at-national-institute-of-cancer-prevention-research-icmr</guid>
  <pubDate>Thu, 17 Nov 2016 04:11:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NATIONAL INSTITUTE OF CANCER PREVENTION &amp; RESEARCH (ICMR)]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF CANCER PREVENTION &amp; RESEARCH (ICMR)</p>

<p>Noida 201301 (U.P)</p>

<p>Applications are invited upto 21.11.2016 from interested candidates as per details available on NICPR website (www.nicpr.res.in)/ ICMR website (www.icmr.nic.in) to fill up following temporary position in the time bound DHR Project entitled “Next generation EGFR inhibitor identification using ligand based QSAR technique” under Dr. Subhash M. Agarwal, Scientist-D, Division of Bioinformatics.</p>

<p>Research Assistant (One)</p>

<p>Rs.27000/- p.m. (Fixed/temporary)</p>

<p>Essential: M.Sc. in Bioinformatics or related field.</p>

<p>Desirable: Experience in QSAR and structure based drug designing.</p>

<p>More Info : www.icmr.nic.in/icmrnews/NICPR_Advertisement%20for%20RA.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</guid>
	<pubDate>Thu, 23 Jul 2020 05:49:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</link>
	<title><![CDATA[wgd—simple command line tools for the analysis of ancient whole-genome duplications]]></title>
	<description><![CDATA[<p><span>wgd is a easy to use command-line tool for<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>distribution construction named wgd. The wgd suite provides commonly used<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner.</span></p>
<p><a href="https://academic.oup.com/bioinformatics/article/35/12/2153/5162749">https://academic.oup.com/bioinformatics/article/35/12/2153/5162749</a></p><p>Address of the bookmark: <a href="https://github.com/arzwa/wgd" rel="nofollow">https://github.com/arzwa/wgd</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

</channel>
</rss>