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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/14215?offset=1430</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33651/darkhorse-a-method-for-genome-wide-prediction-of-horizontal-gene-transfer</guid>
	<pubDate>Thu, 22 Jun 2017 07:58:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33651/darkhorse-a-method-for-genome-wide-prediction-of-horizontal-gene-transfer</link>
	<title><![CDATA[DarkHorse: a method for genome-wide prediction of horizontal gene transfer]]></title>
	<description><![CDATA[<p><span>A new approach to rapid, genome-wide identification and ranking of horizontal transfer candidate proteins is presented. The method is quantitative, reproducible, and computationally undemanding. It can be combined with genomic signature and/or phylogenetic tree-building procedures to improve accuracy and efficiency. The method is also useful for retrospective assessments of horizontal transfer prediction reliability, recognizing orthologous sequences that may have been previously overlooked or unavailable. These features are demonstrated in bacterial, archaeal, and eukaryotic examples.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852411/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852411/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</guid>
	<pubDate>Sun, 01 Jun 2014 23:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</link>
	<title><![CDATA[Genomics and Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/pgHAXCMMcro" frameborder="0" allowfullscreen></iframe>(October 20, 2009) Michael Snyder, Professor of Genetics and Chair of the Department of Genetics at Stanford, discusses advances in gene sequencing, the impact of genomics on medicine, the potential for personalized medicine. and efforts at Stanford to further study these issues.

Stanford Mini Med School is a series arranged and directed by Stanford's School of Medicine, and presented by the Stanford Continuing Studies program. Featuring more than thirty distinguished, faculty, scientists and physicians from Stanford's medical school, the series offers students a dynamic introduction to the world of human biology, health and disease, and the groundbreaking changes taking place in medical research and health care.

Stanford University
http://www.stanford.edu

Stanford University School of Medicine
http://med.stanford.edu

Stanford Continuing Studies
http://continuingstudies.stanford.edu

Stanford University Channel on YouTube:
http://www.youtube.com/stanford]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38692/geneck-gene-network-construction-kit-is-a-comprehensive-online-tool-kit-that-integrate-various-statistical-methods-to-construct-gene-networks</guid>
	<pubDate>Tue, 15 Jan 2019 09:39:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38692/geneck-gene-network-construction-kit-is-a-comprehensive-online-tool-kit-that-integrate-various-statistical-methods-to-construct-gene-networks</link>
	<title><![CDATA[GeNeCK (Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks]]></title>
	<description><![CDATA[<p><strong>GeNeCK</strong><span>&nbsp;(Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks based on gene expression data and optional hub gene information.</span></p>
<p><span><span>It efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.</span></span></p>
<p><span><span><span>GeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at&nbsp;</span><span><a href="http://lce.biohpc.swmed.edu/geneck" target="_blank"><span>http://lce.biohpc.swmed.edu/geneck</span></a></span></span></span></p><p>Address of the bookmark: <a href="http://lce.biohpc.swmed.edu/geneck/" rel="nofollow">http://lce.biohpc.swmed.edu/geneck/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11434/adhoc-bioinformatics-faculty-position-nit</guid>
  <pubDate>Tue, 03 Jun 2014 16:19:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Adhoc Bioinformatics Faculty Position @ NIT]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, DEPARTMENT OF BIOTECHNOLOGY, WARANGAL – 506 021, Andhra Pradesh</p>

<p>No.NITW/BT/2014/adhoc</p>

<p>APPLICATIONS ARE INVITED FOR THE APPOINTMENT OF ADHOC FACULTY ON CONTRACT BASIS IN THE DEAPARTMENT OF BIOTECHNOLOGY</p>

<p>Period of Contract: Initially the appointment is for one semester i.e., from July 2014 up to December 2014 only.</p>

<p>Essential Qualifications:</p>

<p>i) B. Tech or equivalent in Biotechnology/ Industrial Biotechnology/ Biochemical Engineering / Chemical Engg. Or M. Sc in Microbiology/ Botany/ Zoology/ Biochemistry/Biotechnology and ii) M. Tech or equivalent in Biotechnology/Industrial Biotechnology/Bioinformatics</p>

<p>Or</p>

<p>Integrated M. Tech in Biotechnology/Industrial Biotechnology/ Bioinformatics</p>

<p>Candidates must possess First class (60% aggregate marks or 6.5 CGPA) at B. Tech/ M. Sc and M. Tech.</p>

<p>Desirable: Ph. D Pay Package: All selected candidates shall be eligible for a consolidated pay of Rs.30, 000/- per month. Candidates with Ph. D shall be eligible for an additional amount of Rs.5, 000/- per month.</p>

<p>How to apply : Applications on plain paper with attested photocopies of certificate and bio data along with justification for eligibility should reach to the Head, Department of Biotechnology, National Institute of Technology, Warangal AP 506004 in the form of soft or hard copy on or before 21st June 2014 email : biotech_hod@nitw.ac.in</p>

<p>Intimation: No separate call letters will be sent to the candidates. All the eligible candidates will be notified in the institute web site on 23rd June 2014. All the eligible candidates are requested to report for the interview to the Head, Department of Biotechnology at 9:00 AM on 27th June 2014</p>

<p>Joining: Selected candidates will be informed and they are expected to join immediately.</p>

<p>Advertisement:</p>

<p>http://www.nitw.ac.in/nitw/announcements/2014/Bio-Adhoc%20Advt.%20May-2014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</guid>
	<pubDate>Thu, 13 Aug 2020 10:06:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</link>
	<title><![CDATA[PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes]]></title>
	<description><![CDATA[<p>PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring&nbsp;O(n2)&nbsp;resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.</p><p>Address of the bookmark: <a href="https://github.com/ryanmelnyk/PyParanoid" rel="nofollow">https://github.com/ryanmelnyk/PyParanoid</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11735/search-shell-command-history</guid>
	<pubDate>Thu, 12 Jun 2014 17:43:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11735/search-shell-command-history</link>
	<title><![CDATA[Search Shell Command History]]></title>
	<description><![CDATA[<p>We use couple of hundreads of command in daily basis. Most of them are actually repeated several time. The question remain open how do I search old command history under bash shell and modify or reuse it? <br /><br />Now a days almost all modern shell allows you to search command history if enabled by user. Use history command to display the history list with line numbers. Lines listed with with a * have been modified by user.</p><p><br /><strong>Shell history search command</strong><br /><br />Type history at a shell prompt:<br />$ history</p><p>It will display the list of all used commandline history with an serial number.<br /><br />To search particular command, enter:<br />$ history | grep command-name<br />$ history | egrep -i 'scp|ssh|ftp'<br />Emacs Line-Edit Mode Command History Searching<br /><br />To get previous command containing string, hit [CTRL]+[r] followed by search string:<br /><br />(reverse-i-search): <br /><br />To get previous command, hit [CTRL]+[p]. You can also use up arrow key.<br /><br />CTRL-p<br /><br />To get next command, hit [CTRL]+[n]. You can also use down arrow key.<br /><br />CTRL-n<br /><br /></p><p><strong>fc command</strong></p><p>Apart from hostory command there are fc command to extract the command from history. The fc stands for either "find command" or "fix command.</p><p>For example list last 10 command, enter:<br />$ fc -l 10<br />To list commands 130 through 150, enter:<br />$ fc -l 130 150<br />To list all commands since the last command beginning with ssh, enter:<br />$ fc -l ssh<br />You can edit commands 1 through 5 using vi text editor, enter:<br />$ fc -e vi 1 5</p><p><strong>Delete command history</strong><br /><br />The -c option causes the history list to be cleared by deleting all of the entries:<br />$ history -c</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44327/homologizer-phylogenetic-phasing-of-gene-copies-into-polyploid-subgenomes</guid>
	<pubDate>Sat, 03 Jun 2023 19:19:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44327/homologizer-phylogenetic-phasing-of-gene-copies-into-polyploid-subgenomes</link>
	<title><![CDATA[homologizer: Phylogenetic phasing of gene copies into polyploid subgenomes]]></title>
	<description><![CDATA[<p dir="auto">This tutorial describes the usage of&nbsp;<code>homologizer</code>&nbsp;to phase gene copies into polyploid subgenomes. The tutorial is an abbreviated version of a soon-to-be published paper in Methods in Molecular Biology. Please see that paper for many more details and practical considerations for running&nbsp;<code>homologizer</code>&nbsp;analyses. If you use&nbsp;<code>homologizer</code>, please cite the paper in which we first describe the method:</p>
<ul dir="auto">
<li>Freyman, W.A., Johnson, M.G., and C.J. Rothfels. 2022. Homologizer: phylogenetic phasing of gene copies into polyploid subgenomes.&nbsp;<em>bioRxiv</em>&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.10.22.351486v4">2020.10.22.351486v4</a></li>
</ul>
<p dir="auto"><code>homologizer</code>&nbsp;is implemented in&nbsp;<code>RevBayes</code>. Please see&nbsp;<a href="http://revbayes.com/">http://revbayes.com</a>&nbsp;to download and install&nbsp;<code>RevBayes</code>. For users without previous&nbsp;<code>RevBayes</code>&nbsp;experience, we recommend the tutorials at&nbsp;<a href="http://revbayes.com/">http://revbayes.com</a>.</p><p>Address of the bookmark: <a href="https://github.com/wf8/homologizer" rel="nofollow">https://github.com/wf8/homologizer</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11609/bioinformatician%E2%80%99s-pocket-reference</guid>
	<pubDate>Sun, 08 Jun 2014 09:56:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11609/bioinformatician%E2%80%99s-pocket-reference</link>
	<title><![CDATA[Bioinformatician’s Pocket Reference !!]]></title>
	<description><![CDATA[<p><span>It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!</span></p><p>Address of the bookmark: <a href="http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/" rel="nofollow">http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</guid>
	<pubDate>Tue, 25 Jul 2017 08:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</link>
	<title><![CDATA[MGRA: Breakpoint graphs and ancestral genome reconstructions]]></title>
	<description><![CDATA[<p>MGRA (Multiple Genome Rearrangements and Ancestors) is a tool for reconstruction of ancestor genomes and evolutionary history of extant genomes.</p>
<p>It takes as an input a set of genomes represented as sequences of genes (or synteny blocks) and produces such sequences for ancestral genomes at the internal nodes of the phylogenetic tree.</p>
<p>The phylogenetic tree may be also specified completely or partially, in the latter case MGRA can reconstruct conserved ancestral regions (CARs) of the ancestral genome of interest.</p>
<p>Since version 2 MGRA supports gene insertion and deletions in addition to genome rearrangements and allows the input genomes to have different gene content.</p>
<p>It also can reconstruct most plausible phylogenetic tree based on the rearrangement characters.</p><p>Address of the bookmark: <a href="http://mgra.cblab.org/" rel="nofollow">http://mgra.cblab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12218/assistant-professor-in-medical-bioinformatics</guid>
  <pubDate>Tue, 24 Jun 2014 01:46:36 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor in Medical Bioinformatics]]></title>
  <description><![CDATA[
<p>Advt. No : ME-I/A-IV/03/14<br />No.of Posts:01 (SC)<br />Pay Scale:<br />Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.<br />Qualifications:<br />Area of Specialization:-<br />Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology<br />1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.<br />2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/<br />Immunology/Structural Biology etc<br />Experience:<br />1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical<br />Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.<br />2. Minimum two publication with atleast one in international journal and atleast one as first author<br />Desirable:-<br />Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)<br />Send your applications to O/O, Deputy Registrar, Recruitment &amp; Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014<br />For more details,please visit website: http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf<br />Last Apply Date: 08 Jul 2014</p>
]]></description>
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