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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29029?offset=1400</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34479/bioinformatics-lectures</guid>
	<pubDate>Wed, 29 Nov 2017 05:39:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34479/bioinformatics-lectures</link>
	<title><![CDATA[Bioinformatics lectures !]]></title>
	<description><![CDATA[<div>
<div>
<div>Computational Biology is a&nbsp;<em style="font-size: 12.8px; font-weight: normal;">huge</em>&nbsp;field of study, that touches upon many distinct algorithmic and biological areas of study. What we are able to cover in this course will depend, in part, on the pace at which we move, which I will attempt to adjust as appropriate. However, here is a tentative list of topics I hope to cover this semester (not necessarily in order).
<ul>
<li>Optimal sequence alignment (global, local, and glocal alignment &amp;mdash with constant &amp; affine gap penalties</li>
<li>Algorithms and data structures for efficient text indexing and&nbsp;<em>exact</em>&nbsp;search</li>
<li>Heuristics for read&nbsp;<em>alignment</em>&nbsp;and&nbsp;<em>mapping</em>&nbsp;&amp;mdash mapping DNA-seq and RNA-seq reads</li>
<li>Genome assembly &amp;mdash k-mers, De Brujin graph construction and representation, long-read technology and read-overlap graph assembly</li>
<li>Motif finding via Gibbs sampling</li>
<li>Gene finding &amp;mdash statistical models for&nbsp;<em>ab initio</em>&nbsp;and evidence-guided prediction of genes</li>
<li>RNA-seq and transcriptomics &amp;mdash transcript assembly, abundance estimation and differential expression testing</li>
<li>Phylogenetics &amp;mdash The small and large phylogeny problem; parsimony, maximum likelihood and Bayesian methods</li>
</ul>
</div>
</div>
</div><p>Address of the bookmark: <a href="https://rob-p.github.io/CSE549F16/lectures/" rel="nofollow">https://rob-p.github.io/CSE549F16/lectures/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/news/view/35257/india-and-germany-to-begin-joint-research-in-the-area-of-bioinformatics-in-health-research</guid>
	<pubDate>Wed, 17 Jan 2018 14:10:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/35257/india-and-germany-to-begin-joint-research-in-the-area-of-bioinformatics-in-health-research</link>
	<title><![CDATA[India and Germany to begin joint research in the area of 'Bioinformatics in Health Research']]></title>
	<description><![CDATA[<p><span>To facilitate bilateral cooperation in biotechnology between the scientific communities of India and Germany, the Department of Biotechnology (DBT) will soon begin collaborative research in the identified priority area of 'Bioinformatics in Health Research' under the programme of Indo-German Cooperation in Health Research.&nbsp;</span><br /><br /><span>The purpose of the programme is to stimulate new collaborations, e.g. the preparation of joint projects under national funding programmes. The programme facilitates bilateral cooperation in biotechnology between the scientific communities of India and Germany by way of joint research projects which will encompass bilateral workshops/seminar and exchange visits of scientists.&nbsp;</span><br /><br /><span>The programme is being implemented within the agreement of Indo-German cooperation in S&amp;T of 1974, under which the Department of Biotechnology, Government of India and Forschungszentrum Julich BMBH (FZJ), Federal Republic of Germany, have agreed for cooperative programme in biotechnology.</span><br /><br /><span>DBT of the Ministry of Science &amp; Technology, Government of India and the Project Management Agency at the German Aerospace Center (DLR-PT, European and International Cooperation), Bonn are the nodal implementing agencies from the Indian and German side respectively.</span><br /><br /><span>Through this programme, it is expected that the funded cooperation enables the partners to develop applicable scientific results which can be published and/ or could be commercialised and may lead to formation of joint ventures. All publications, patents coming out of these projects, need to be jointly authored by both Indian and German scientists. All necessary approvals like ethical clearance, HMSC approval from Indian point of view as well as EU, if applicable, from German point of view, e.g. before conducting animal experimentation if any needs to be obtained by PIs before undertaking the project.&nbsp;</span><br /><br /><span>Now, both the nodal agencies have invited research proposals in identified priority area of 'Bioinformatics in Health Research' from eligible scientists.&nbsp; Joint research projects are required to be submitted to both the nodal agencies by 15 January 2018. Scientists/faculty members working in regular capacity in universities, national R&amp;D laboratories/institutes and private R&amp;D institutes can be part of this joint research programme.&nbsp;&nbsp; For the private sector, partners from all kind of private sectors are eligible, but financing is limited. For Indian scientists from the private sector, only local hospitality in Germany as part of the exchange visit is available from the German side.&nbsp; For German scientists from the private sector, only travel costs are available for small and medium size enterprises (for definition of SME ref. to 2003/361/EC) as well as local hospitality in India will be borne by themselves.</span></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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics</guid>
	<pubDate>Fri, 02 Mar 2018 04:26:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics</link>
	<title><![CDATA[An Introduction to Applied Bioinformatics]]></title>
	<description><![CDATA[<p>IAB is primarily being developed by&nbsp;<a href="http://caporasolab.us/people/greg-caporaso/">Greg Caporaso</a>(GitHub/Twitter:&nbsp;<a href="https://github.com/gregcaporaso">@gregcaporaso</a>) in the&nbsp;<a href="http://www.caporasolab.us/">Caporaso Lab</a>&nbsp;at&nbsp;<a href="http://www.nau.edu/">Northern Arizona University</a>. You can find information on the courses I teach on&nbsp;<a href="http://www.caporasolab.us/teaching">my teaching website</a>&nbsp;and information on my research and lab on&nbsp;<a href="http://www.caporasolab.us/">my lab website</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://readiab.org/" rel="nofollow">http://readiab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37636/department-of-genetics-genomics-and-bioinformatics-national-biotechnology-development-agency-nigeria</guid>
	<pubDate>Wed, 05 Sep 2018 10:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37636/department-of-genetics-genomics-and-bioinformatics-national-biotechnology-development-agency-nigeria</link>
	<title><![CDATA[DEPARTMENT OF GENETICS, GENOMICS AND BIOINFORMATICS, National Biotechnology Development Agency, Nigeria]]></title>
	<description><![CDATA[<p>The Genetics, Genomics &amp; Bioinformatics Department (GBBD) at NABDA is unique, encompassing all facets of modern genetics and bioinformatics research. Trans-disciplinary research being conducted in our laboratories would lead to cures for human diseases; improvements to crop and livestock quality and yield; creation of new technologies with applications to medicine; agriculture; environment; and industry.</p>
<p>Our capacity building activities covers both general and specialized topics in translational genetics, and is designed to better acquaint scientists and clinicians with the tools and technologies of genetics and genomics.</p>
<p><span>OUR RESEARCH ACTIVITIES INCLUDE:</span></p>
<div>
<ul>
<li>Biomedical Genetics: investigating genetic and environmental factors contributing to phenotypes with relevance to human health and disease.</li>
<li>Computation and Bioinformatics: develop new approaches for the management, analysis, and modelling of large, complex data sets.</li>
<li>Population and Quantitative Genetics: study of how genetic processes evolve to generate genetic variation in populations of organisms, and the effects on the patterning of variation within and between populations and specie, and</li>
<li>Genetic Engineering and Biotechnology: focuses on the research and innovation for industrial enzymes, biologics and biosimilars production.</li>
</ul>
<p>https://www.h3abionet.org/nabda</p>
</div><p>Address of the bookmark: <a href="http://www.nabda.gov.ng/departments/genetics-genomics-and-bioinformatics" rel="nofollow">http://www.nabda.gov.ng/departments/genetics-genomics-and-bioinformatics</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/38590/senior-bioinformatics-scientist-strand-life-sciences-bangalore-india</guid>
  <pubDate>Wed, 02 Jan 2019 09:23:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[Senior Bioinformatics Scientist @ Strand Life Sciences -- Bangalore, India]]></title>
  <description><![CDATA[
<p>RESPONSIBILITIES<br />The candidate is expected to work on a variety of projects related to analysis of data from NGS, Mass Spectrometry, Flow Cytometry and other related modalities. The position expects hands-on work and a strong eye for detail. The candidate will be able to contribute to impactful work spanning patient care, clinical research, and new assay and method development.<br />REQUIREMENTS<br />A PhD in a quantitative field (statistics, math, bioinformatics, computer science, physics or similar) and work experience or post-doc experience handling high throughout genomics data.<br />PREFERENCES<br />Experience in working in inter-disciplinary groups and ability to author research publications are additional desired qualities.<br />LOCALE<br />The position is in Bangalore and reports to the Chief Scientific Officer.<br />HOW TO APPLY<br />Write to ramesh[at]strandls.com.</p>
]]></description>
</item>
<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/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>

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