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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44716?offset=1020</link>
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	<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/bookmarks/view/12206/bioinformatics-algorithms-tutorials</guid>
	<pubDate>Tue, 24 Jun 2014 00:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12206/bioinformatics-algorithms-tutorials</link>
	<title><![CDATA[Bioinformatics algorithms tutorials]]></title>
	<description><![CDATA[<p>Useful bioinformatics tutorial, such as</p>
<p>De Bruijn Graphs for NGS Assembly<br>Algorithms for PacBio Reads<br>Software and Hardware Concepts for Bioinformatics<br>Finding us in Homolog.us (Search Algorithms)<br>NGS Genome and RNAseq Assembly - a Hands on Primer<br>Introduction to PERL, Python, R and C/C++ for Bioinformatics</p><p>Address of the bookmark: <a href="http://www.homolog.us/Tutorials/" rel="nofollow">http://www.homolog.us/Tutorials/</a></p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/23582/integrative-rna-and-chip-seq-analysis-of-regulatory-t-cells</guid>
	<pubDate>Tue, 04 Aug 2015 05:03:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/23582/integrative-rna-and-chip-seq-analysis-of-regulatory-t-cells</link>
	<title><![CDATA[Integrative RNA and ChIP-Seq analysis of regulatory T-cells]]></title>
	<description><![CDATA[<p><a href="http://www.strand-ngs.com/learn/white-papers#rna-chip" target="_blank" title="strand ngs white paper">Integrative RNA and ChIP-Seq analysis of regulatory T-cells&nbsp;</a><span>, a Strand NGS application note describes how integrated multi-omics functionality in Strand NGS was used to find the regulatory role of FoxP3 in T-regulatory and T-helper cells. Learn how the gene expression profiles from RNA-Seq and FoxP3 DNA-protein binding sites from ChIP-Seq are integrated. For mor information,&nbsp;</span><a href="http://www.strand-ngs.com/contact/sales" target="_blank" title="strand ngs contact">please write to us</a></p>]]></description>
	<dc:creator>Strand</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12567/workshop-on-molecular-modeling-and-dynamics-simulation-analyses</guid>
  <pubDate>Fri, 04 Jul 2014 13:38:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Workshop On Molecular Modeling and Dynamics Simulation Analyses]]></title>
  <description><![CDATA[
<p>Workshop On Molecular Modeling and Dynamics Simulation Analyses</p>

<p>August1-2, 2014</p>

<p>Organised By</p>

<p>Centre of Excellence in Bioinformatics<br />Bioinformatics Infrastructure Facility<br />Department of Biochemistry<br />University of Lucknow<br />Lucknow-226007</p>

<p>Course Contents</p>

<p>Molecular Modeling<br /> Homology Modeling<br />Molecular Docking<br />Post-structural Analyses</p>

<p>Molecular Dynamics (MD)<br />Simulation<br />Linux Introduction<br />Gromacs Installation</p>

<p>MD Simulation of Protein ligand complex<br />Analyses of MD<br />Trajectories<br />Visualization of Dynamic<br />complexes</p>

<p>Important Dates</p>

<p>Registration Begins June 25, 2014<br />Registration Closes July 25, 2014</p>

<p>Brochure : www.lkouniv.ac.in/conference/Brochure_August,%202014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34212/webinar-on-unique-molecular-identifier-umi-powered-ultra-sensitive-variant-calling-using-strand-ngs-case-study</guid>
	<pubDate>Tue, 07 Nov 2017 03:55:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34212/webinar-on-unique-molecular-identifier-umi-powered-ultra-sensitive-variant-calling-using-strand-ngs-case-study</link>
	<title><![CDATA[Webinar on Unique Molecular Identifier (UMI)-powered Ultra-sensitive Variant Calling using Strand NGS - Case Study]]></title>
	<description><![CDATA[<h2><a href="http://www.strand-ngs.com/webinar_registration">Webinar on Unique Molecular Identifier-powered Ultra-sensitive Variant Calling using Strand NGS - Case Study</a></h2><p>by&nbsp;Dr. Pandurang Kolekar, Bioinformatics Engineer, Strand Life Sciences</p><h3><a href="http://www.strand-ngs.com/webinar_registration">Abstract</a>:</h3><p>Unique Molecular Identifiers (UMIs) are short random nucleotide sequences that are increasingly being used in high-throughput sequencing experiments. In this webinar, we will highlight the UMI-friendly features of Strand NGS v3.1 including support for handling well known and customised UMI libraries, QC metrics, consensus alignment, UMI-based family size filters for read list, genome browser enabled with UMI-specific features and filters, UMI-aware variant calling parameters, and exporting UMI-tagged aligned samples. These all features together empower users to harness the potential of UMI-tagged NGS data for deeper insights. A case study demonstrating application of these UMI-based features in Strand NGS for low frequency variant calling in cfDNA sample will be presented.</p><p>UMI-tagged NGS libraries allow, ultra-sensitive detection of low frequency variants from liquid biopsy samples using DNA-Seq and accurate quantification of transcript-level expression using RNA-Seq. The recent release of Strand NGS v3.1, is equipped with the necessary features to efficiently analyse UMI-tagged NGS data helping researchers and labs involved in rare variant calling like in cfDNA based cancer diagnostics, and accurate transcript quantification with RNA-Seq.</p><p><a href="http://www.strand-ngs.com/webinar_registration"><strong>Webinar Details:</strong></a></p><p><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1:</strong></a> 13 Dec 2017, 2:30 PM IST<br /><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2:</strong></a> 13 Dec 2017, 9:30 PM IST</p><p><br /><a href="http://www.strand-ngs.com/webinar_registration"><strong>Register here:</strong></a> http://www.strand-ngs.com/webinar_registration</p><h3>&nbsp;</h3>]]></description>
	<dc:creator>Strand</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</guid>
	<pubDate>Wed, 23 Jul 2014 06:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</link>
	<title><![CDATA[Orione – a web-based framework for NGS analysis in microbiology]]></title>
	<description><![CDATA[<p>End-to-end NGS microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult due to a lack of interoperability, reproducibility, and transparency. To overcome these limitations researchers at <a href="http://www.crs4.it/" target="_blank">CRS4</a>, Italy have developed Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for NGS microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.</p>
<p>Reference</p>
<p>Cuccuru G1, Orsini M, Pinna A, Sbardellati A, Soranzo N, Travaglione A, Uva P, Zanetti G, Fotia G. (2014)<strong> Orione, a web-based framework for NGS analysis in microbiology.</strong> <em>Bioinformatics</em> [Epub ahead of print]. [<a href="http://bioinformatics.oxfordjournals.org/content/early/2014/03/10/bioinformatics.btu135.long" target="_blank">article</a>]</p><p>Address of the bookmark: <a href="http://orione.crs4.it/" rel="nofollow">http://orione.crs4.it/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43308/rna-seq-differential-expression-work-flow-using-deseq2</guid>
	<pubDate>Mon, 23 Aug 2021 10:57:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43308/rna-seq-differential-expression-work-flow-using-deseq2</link>
	<title><![CDATA[RNA-Seq differential expression work flow using DESeq2]]></title>
	<description><![CDATA[<p><span>One of the aim of RNAseq data analysis is the detection of differentially expressed genes. The package&nbsp;</span><a href="http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html">DESeq2</a><span>&nbsp;provides methods to test for differential expression analysis.</span></p><p>Address of the bookmark: <a href="http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2" rel="nofollow">http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</guid>
	<pubDate>Fri, 18 Jul 2014 05:42:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</link>
	<title><![CDATA[Breaking chromosomes to study cancer !!!]]></title>
	<description><![CDATA[<p>Chromosomes are present in every cell of our body and they contain the information the body needs to develop and function properly. This information is carried in genes that are arranged along the chromosomes. There are usually 46 chromosomes in every cell. These chromosomes come in pairs, one from our mother and one from our father. The chromosomes can be sorted into 23 pairs by looking at them down a microscope.</p><p>Most people who have a balanced translocation have the right amount of chromosome material but it has been rearranged in some way. This may happen if two chromosomes swap pieces (a reciprocal translocation). In other cases two whole chromosomes may become stuck together (a Robertsonian translocation). This page describes what happens when someone has a reciprocal translocation. <br /><br />Reciprocal chromosomal translocations occur following double-strand breaks (DSBs) in DNA when a section of one chromosome is exchanged with that of another, non-homologous chromosome. These exchanges may produce a dysfunctional fusion gene that disrupts cell growth and survival pathways, such as the translocations seen in leukemia and childhood sarcomas. <br /><br />Chromosomal translocations have been well studied in cancer cell lines which are associated with two types of cancer, acute myeloid leukemia and Ewing's sarcoma, but determining how they contribute to cancer development is complicated by additional mutations and altered gene expression profiles in these cultured cells. Now, Juan Carlos Ramirez, head of the Viral Vector Facility at the Fundacion Centro Nacional de Investigaciones Cardiovasculares (CNIC) and his colleagues Raul Torres at CNIC and Sandra Rodriguez-Peralez at the Spanish National Cancer Center (CNIO) in Madrid, Spain have used a new genome editing tool, CRISPR-Cas9, to induce chromosomal translocations for the first time in a human cell line and in primary cells. The study's authors conclude by stating that the use of this technology will allow for the clarification of how and why chromosomal translocation occurs, which without doubt will allow new anti-cancer therapeutic strategies to be tackled.</p><p>Using RNA-Guided Endonuclease (RGEN) technology or CRISPR/Cas9 genome engineering technology, CNIO and CNIC researchers have shown that it is possible to obtain such chromosomal translocations. The CRISPR-Cas9 system is extremely simple to introduce a cut at the desired locus, easier to design, and cheaper than many other systems. Using the CRISPR-Cas9 system, Ramirez and his colleagues reproduced the translocations observed in Ewing&rsquo;s Sarcoma (ES) and Acute Myeloid Leukemia (AML) patient cell lines in HEK293 cells and also generated the ES translocation in human mesenchymal stem cells and the AML translocation in umbilical cord blood cells.</p><p>By focusing on chromosomal translocation without the confounding characteristics of established cell lines, these new cells lines should help answer the fundamental question of what causes a cell to become cancerous. Ramirez and his team now look forward to modeling other chromosome translocations in a variety of cell types.</p><p>Reference:</p><p>http://en.wikipedia.org/wiki/Chromosomal_translocation</p><p>http://www.nature.com/ncomms/2014/140603/ncomms4964/abs/ncomms4964.html<br /><br /></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35747/webinar-on-rna-seq-data-analysis-on-28-feb-2018</guid>
	<pubDate>Thu, 22 Feb 2018 06:38:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35747/webinar-on-rna-seq-data-analysis-on-28-feb-2018</link>
	<title><![CDATA[Webinar on RNA-Seq Data Analysis on 28 Feb 2018]]></title>
	<description><![CDATA[<p>Strand NGS is a biologist friendly NGS analysis tool that allows biologists to analyze their data using a very intuitive workflow for the analysis and visualization of RNA-Seq data. This webinar will give an overview of the workflow which includes Transcriptome/ Genome alignment, Differential expression analysis, Splicing events and gene fusion detection. Strand NGS also supports novel discovery like identification of novel genes, exons and novel splice junctions.<br />We will highlight the use of Strand NGS features such as PCA, sample correlation, clustering, Venn diagrams, CVA, UMI support and elastic genome browser used in RNA-Seq workflow that supports large scale RNA-Seq data analysis too. The tool also supports biological contextualization on the set of interesting genes from the data by allowing downstream analysis such as GO and pathway analysis. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS.</p><p>Details:<br /><a href="http://www.strand-ngs.com/webinar_registration">Session 1: </a>28 Feb 2018, 9 AM CET<br /><a href="http://www.strand-ngs.com/webinar_registration">Session 2:</a> 28 Feb 2018, 8 AM PST<br />Register here: http://www.strand-ngs.com/webinar_registration</p><p><span style="font-size: 12.8px;">About Speaker:</span></p><p>Dr. Suman Kapoor, Manager- Application Science at Strand Life Sciences, has over 11 years experience in molecular biology, next-generation sequencing based testing, clinical genomics, and personalized medicine for disease management and prenatal testing. Dr. Suman holds a Ph.D in Molecular and Cell Biology from Indian Institute of Science, Bangalore. Prior to joining Strand NGS team, Suman has worked extensively on protein synthesis in eubacteria and has experience working in CAP and NABL accredited lab validating and interpreting NGS based diagnostic tests.</p>]]></description>
	<dc:creator>Strand</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12940/ra-at-iiser-kolkata-computational-biologybioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 06:24:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at IISER Kolkata Computational Biology/Bioinformatics]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for research associate (post-doc; Rs. 22000-32000)/research fellow (16000-18000)/project assistant (Rs. 10000-14000) positions in the Department of Biological Sciences, Indian Institute for Science Education and Research Kolkata in the extramural project. Condition to satisfactory performance, the positions is for a period of upto 2 years (or funding of the project).</p>

<p>Brief description: We are looking for suitable candidates in the area o computational biology/bioinformatics/genomics or related field for next-generation sequencing (NGS) data analysis for small-RNAs, RNA-Seq and targeted resequencing of plants and associated organisms. We are an interdisciplinary group where projects equally involve bioinformatics and systems biology (specially microarrays and next-generation sequencing (NGS) data analysis and its use), along with plant molecular biology, genetic engineering, field biology, and analytical plant chemistry for understanding response of plants to biotic stresses.</p>

<p>Essential qualification: MSc/BTech/MTech/PhD (or other suitable qualification) in disciplines preferable to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance Post-Graduate Diploma in Bioinformatics’. Proficiency in programming languages (such as Perl, C++) and/or statistics (proficient in R for example) is compulsory.</p>

<p>Desirable qualification: Experience in the field of genomics e.g. microarray analysis, NGS, genome annotation, database development and management, software development, systems and network biology (or related fields) will be preferred.</p>

<p>Application process: Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by e-mail to Shree Prakash Pandey, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur Campus, WB, India within 14 days of this advertisement.</p>

<p>E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in</p>

<p>Advertisement:</p>

<p>http://www.iiserkol.ac.in/announcements/adverts/671-advt_ra_shree_prakash_july_2014</p>
]]></description>
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