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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44718?offset=1250</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36508/mitobim-mitochondrial-baiting-and-iterative-mapping</guid>
	<pubDate>Tue, 08 May 2018 04:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36508/mitobim-mitochondrial-baiting-and-iterative-mapping</link>
	<title><![CDATA[MITObim - mitochondrial baiting and iterative mapping]]></title>
	<description><![CDATA[<p>This document contains instructions on how to use the MITObim pipeline described in Hahn et al. 2013. The full article can be found&nbsp;<a href="http://nar.oxfordjournals.org/content/41/13/e129" title="MITObim full article at NAR">here</a>. Kindly cite the article if you are using MITObim in your work. The pipeline was originally developed for&nbsp;<span>Illumina</span>&nbsp;data, but thanks to the versatility of the MIRA assembler, MITObim supports in principle also data from the&nbsp;<span>Iontorrent</span>,&nbsp;<span>454</span>&nbsp;and&nbsp;<span>PacBio</span>&nbsp;sequencing platforms.</p>
<p>Below you can find a few basic tutorials for how to run MITObim and I encorage you to give them a try with the testdata that comes with this Repo, just to make sure everything is running smoothly on your system. It'll only take a few minutes and will potentially safe you a lot of time down the line.</p>
<p>I provide further examples&nbsp;<a href="https://github.com/chrishah/MITObim/tree/master/examples">here</a>&nbsp;as Jupyter notebooks. Get in touch if you feel like sharing your particular MITObim solution and I'd be happy to put it up here, too!</p><p>Address of the bookmark: <a href="https://github.com/chrishah/MITObim" rel="nofollow">https://github.com/chrishah/MITObim</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14003/jrf-position-in-the-faculty-of-life-sciences-biotechnology-at-sauth-asian-university</guid>
  <pubDate>Wed, 13 Aug 2014 07:16:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF position in the Faculty of Life Sciences &amp; Biotechnology at  Sauth Asian University]]></title>
  <description><![CDATA[
<p>Opening for a Project-JRF position in the Faculty of Life Sciences &amp; Biotechnology</p>

<p>Applications are invited for the post of Junior Research Fellow (JRF) in a DBT funded IYBA project entitled “Generatingaprotein-ncRNA interactome for Dorsal mediated gene regulation and dorso-ventral patterning genes in Drosophila” in the Lab. Of Molecular Biology at the Faculty of Life Sciences and Biotechnology, South Asian University, New Delhi. The project requires extensive use of molecular, genetic and genomic approaches.</p>

<p>POST: Junior Research Fellow (JRF)</p>

<p>NO. OF VACANCIE(S) - (01)</p>

<p>FELLOWSHIP: Rs. 16,000/- plus HRA</p>

<p>PROJECT DURATION: 2014-2016 (Two years)</p>

<p>LAST DATE FOR APPLICATION: Aug 18, 2014.</p>

<p>Eligibility criteria:</p>

<p>M.Sc./M.Tech./ in Biological Sciences/Biotechnology/Bio-Informatics. Candidates with research experience in the field of Drosophila/Yeast genetics will be preferred.</p>

<p>Application Procedure:</p>

<p>A covering letter along with your CV, copy of prior publications (if any) and proof of experience should be e-mailed to lmb_sau@aol.com. Hardcopy of the application should be brought on the day of interview along with other testimonials and marks statements for verification purpose.</p>

<p>IMPORTANT NOTE:</p>

<p>-No TA/DA will be paid for attending the interview.</p>

<p>-SAU may select candidates against the post depending upon qualification and experience of candidates and reserves the right to relax any of the qualifications in case the candidate is found otherwise well qualified by the Selection Committee</p>

<p>-The abovementioned post is temporary and will be initially offered for a period of one year and can be extended, on satisfactory performance. </p>

<p>More at http://www.sau.ac.in/recruitment/vacancy.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 11 May 2018 05:07:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads]]></title>
	<description><![CDATA[<p>MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>. MECAT performance were compared with&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>,&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>&nbsp;and&nbsp;<a href="http://canu.readthedocs.io/en/latest/">Canu(v1.3)</a>&nbsp;in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>&nbsp;and&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>.&nbsp;</p>
<p>https://www.nature.com/articles/nmeth.4432</p><p>Address of the bookmark: <a href="https://github.com/xiaochuanle/MECAT" rel="nofollow">https://github.com/xiaochuanle/MECAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14054/project-fellow-at-institute-of-himalayan-bioresource-technology</guid>
  <pubDate>Fri, 15 Aug 2014 06:50:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow at Institute of Himalayan Bioresource Technology]]></title>
  <description><![CDATA[
<p>Research Associate/ Project FellowDate of posting:14 Aug</p>

<p>Eligibility : MSc, M Phil / Phd, BE/B.Tech<br />Location : Himachal Pradesh-other<br />Job Category : Govt Jobs, Research, Walkin<br />Last Date : 20 Aug 2014</p>

<p>Advertisement No.6/2014</p>

<p>Post : Project Fellow<br />Research Associate/ Project Fellow Jobs opportunity in CSIR-Institute of Himalayan Bioresource Technology<br />M.Sc. in Bioinformatics/Computer Science with 55% marks and (ii) M.Sc. Bioinformatics/ Computational biology/ P.G. Diploma in Bioinformatics/B.Tech. or higher Degree in Bioinformatics with 55% marks</p>

<p>Date of Interview: 29.08.2014.</p>

<p>More at http://www.ihbt.res.in/recruit/AdvtNo6_2014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14338/biology-computers-collide-in-high-demand-field-of-bioinformatics</guid>
	<pubDate>Mon, 25 Aug 2014 00:56:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14338/biology-computers-collide-in-high-demand-field-of-bioinformatics</link>
	<title><![CDATA[Biology, Computers Collide in High-Demand Field of Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fk0z7KOTyMo" frameborder="0" allowfullscreen></iframe>Dr. Shivas Amin calls bioinformatics a "collision of biology and computers." Students learn how to use computers and skills in math and biology to analyze genome and proteome projects to prepare for high-demand jobs in the life sciences. Learn more about Amin and hear from student Medina Baitemirova and alumnus Lukas Simon about the fast-growing field of bioinformatics.]]></description>
	
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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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14800/a-comprehensive-atlas-of-human-gene-activity-released</guid>
	<pubDate>Tue, 02 Sep 2014 14:20:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14800/a-comprehensive-atlas-of-human-gene-activity-released</link>
	<title><![CDATA[A comprehensive atlas of human gene activity released !!!]]></title>
	<description><![CDATA[<div><div id="postDescription_4018558404"><p>A large international consortium of researchers has produced the first comprehensive, detailed map of the way&nbsp;<a href="http://www.hsph.harvard.edu/news/topic/genetics/" target="_blank">genes</a>&nbsp;work across the major cells and tissues of the human body. The findings describe the complex networks that govern gene activity, and the new information could play a crucial role in identifying the genes involved with disease.</p><p><img src="http://www.kurzweilai.net/images/Coexpression-clustering.jpg" alt="image" width="640" height="460" style="border: 0px; border: 0px;"></p><p>We are able to pinpoint the regions of the genome that can be active in a disease and in normal activity, whether it&rsquo;s in a brain cell, the skin, in blood stem cells or in hair follicles. This is a major advance that will greatly increase our ability to understand the causes of disease across the body.</p><p>The research is outlined in a series of papers published March 27, 2014, two in the journal&nbsp;<em>Nature</em>&nbsp;and 16 in other scholarly journals. The work is the result of years of concerted effort among 250 experts from more than 20 countries as part of&nbsp;<a href="http://fantom.gsc.riken.jp/" target="_blank">FANTOM 5 (Functional Annotation of the Mammalian Genome)</a>. The FANTOM project, led by the Japanese institution RIKEN, is aimed at building a complete library of human genes.</p><p>Researchers studied human and mouse cells using a new technology called Cap Analysis of Gene Expression (CAGE), developed at RIKEN, to discover how 95% of all human genes are switched on and off. These &ldquo;switches&rdquo; &mdash; called &ldquo;promoters&rdquo; and &ldquo;enhancers&rdquo; &mdash; are the regions of DNA that manage gene activity. The researchers mapped the activity of 180,000 promoters and 44,000 enhancers across a wide range of human cell types and tissues and, in most cases, found they were linked with specific cell types.</p><p>Referene : www.kurzweilai.net/first-comprehensive-atlas-of-human-gene-activity-released</p></div></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</guid>
	<pubDate>Tue, 30 Jan 2018 06:01:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</link>
	<title><![CDATA[Comprehensive list of visualization tools for biological pathways]]></title>
	<description><![CDATA[<p>The study of biological pathways is a key to understand the different processes inside a cell: proteins exert their function not in isolation but in a tightly controlled network of interactions and reactions. Activation of a pathway typically leads to a change of state in the cell. Pathways come in different flavors, depending on their functions in the cell &ndash; the three main types are metabolic pathways, gene regulatory pathways, and signaling pathways. These biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization.</p><p><img src="https://photos-1.dropbox.com/t/2/AABemz29qAuSTqSzr5mEsQE7JIMxZlU1CBy0E5n0yUVYbA/12/85115969/png/32x32/1/_/1/2/pathway.png/EOfXoUIYrJ8CIAcoBw/01qsT2eykyPvSH-rNpy3cqioDzZPc4i-xULG3BEZvCk?preserve_transparency=1&amp;size=1280x960&amp;size_mode=3" width="800" height="533" alt="image" style="border: 0px;"></p><p>Following are the comprehensive list of visualization tools for biological pathways:</p><p>BiNA</p><p>Drawings of metabolic networks supporting hiding of cofactors and drawing of chemical structures</p><p>http://bina.unipax.info/</p><p>BioTapestry</p><p>Interactive tool for building, visualizing and sharing gene regulatory network models over the web</p><p>http://www.biotapestry.org/</p><p>Caleydo</p><p>Visual analysis framework targeted at biomolecular data. Visualization of interdependencies between multiple datasets</p><p>http://www.caleydo.org/</p><p>CellDesigner</p><p>A modeling tool for biochemical networks</p><p>http://www.celldesigner.org/</p><p>Edinburgh Pathway Editor</p><p>Edit and draw pathway diagrams</p><p>http://epe.sourceforge.net/SourceForge/EPE.html</p><p>GenMAPP</p><p>Visualization of gene expression and other genomic data on maps representing biological pathways and groupings of genes</p><p>http://www.genmapp.org/</p><p>Ingenuity IPA</p><p>Data integration platform and manually annotated pathways</p><p>http://tinyurl.com/IngenuityPath</p><p>JDesigner</p><p>Graphical modeling environment for biochemical reaction networks</p><p>http://jdesigner.sourceforge.net/Site/JDesigner.html</p><p>KaPPA View</p><p>Plant pathways</p><p>http://kpv.kazusa.or.jp/</p><p>KEGG Atlas</p><p>Interactive Kyoto Encyclopedia of Genes and Genomes pathways</p><p>http://www.genome.jp/kegg/</p><p>Omix&nbsp;</p><p>Visualizing multi-omics data in metabolic networks</p><p>https://www.omix-visualization.com</p><p>PathVisio&nbsp;</p><p>Biological pathway analysis software that allows drawing, editing and analysis of biological pathways</p><p>http://www.pathvisio.org/</p><p>VitaPad&nbsp;</p><p>Application to visualize biological pathways and map experimental data to them</p><p>http://tinyurl.com/vitapad/</p><p>Web tools for pathways</p><p>ArrayXPath&nbsp;</p><p>Mapping and visualizing microarray gene-expression data and integrated biological pathway resources using SVG</p><p>http://tinyurl.com/ArrayXPath/</p><p>GEPAT&nbsp;</p><p>Integrated analysis of transcriptome data in genomic, proteomic and metabolic contexts</p><p>http://gepat.sourceforge.net/</p><p>iPath&nbsp;</p><p>Web-based tool for the visualization, analysis and customization of pathway maps</p><p>http://pathways.embl.de/</p><p>Kegg-Based Viewer&nbsp;</p><p>KEGG-based pathway visualization tool for complex high-throughput data</p><p>http://www.g-language.org/data/marray/</p><p>MapMan&nbsp;</p><p>User-driven tool that displays large datasets onto diagrams of metabolic pathways or other processes</p><p>http://mapman.gabipd.org/web/guest/mapman</p><p>MetPA&nbsp;</p><p>Analysis and visualization of metabolomic data within the biological context of metabolic pathways</p><p>http://metpa.metabolomics.ca</p><p>Omics Viewer&nbsp;</p><p>Data mapping on BioCyc pathways (collection of 5500 pathway/genome databases)</p><p>http://www.biocyc.org/</p><p>Pathway Explorer</p><p>Interactive Java drawing tool for the construction of biological pathway diagrams in a visual way and the annotation of the components and interactions between them</p><p>http://genome.tugraz.at/pathwayexplorer/pathwayexplorer_description.shtml</p><p>Pathway projector&nbsp;</p><p>Zoomable pathway browser using KEGG atlas and Google Maps API</p><p>http://www.g-language.org/PathwayProjector/</p><p>PATIKA&nbsp;</p><p>Integrated environment composed of a central database and a visual editor, built around an extensive ontology and an integration framework</p><p>http://www.cs.bilkent.edu.tr/~patikaweb/</p><p>Reactome SkyPainter&nbsp;</p><p>Visualization of over-represented pathways and reactions from gene lists</p><p>http://www.reactome.org/skypainter-2</p><p>WikiPathways</p><p>Wiki-based, open, public platform dedicated to the curation of biological pathways by and for the scientific community</p><p>http://www.wikipathways.org/</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/14927/which-of-the-following-programming-language-is-best-for-a-bioinformatics-beginner</guid>
	<pubDate>Thu, 04 Sep 2014 07:51:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/14927/which-of-the-following-programming-language-is-best-for-a-bioinformatics-beginner</link>
	<title><![CDATA[Which of the following programming language is best for a bioinformatics beginner?]]></title>
	<description><![CDATA[<p>I will be doing NGS in the course of my research work and I will like to learn a programming language which is compatible with most bioinformatics tools or software. I basically want to do de-novo assembly, map reads, align reads, and expression analysis. Recommendations welcomed. Which languages would you recommend to a student wishing to enter the world of bioinformatics?</p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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