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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36607?offset=180</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes</guid>
	<pubDate>Tue, 10 Sep 2024 04:54:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes</link>
	<title><![CDATA[NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes]]></title>
	<description><![CDATA[<p>NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes&nbsp;</p>
<p><img src="https://github.com/hewm2008/NGenomeSyn/raw/main/Example/example2/OUT3.png" alt="image" style="border: 0px;"></p>
<p><span>NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.</span></p>
<p>https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460</p><p>Address of the bookmark: <a href="https://github.com/hewm2008/NGenomeSyn" rel="nofollow">https://github.com/hewm2008/NGenomeSyn</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34704/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization</guid>
	<pubDate>Mon, 18 Dec 2017 04:16:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34704/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization</link>
	<title><![CDATA[NanoSim: nanopore sequence read simulator based on statistical characterization.]]></title>
	<description><![CDATA[<p><span>NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data and allows for adjustments upon improvement of nanopore sequencing technology. The first step of NanoSim is read characterization, which provides a comprehensive alignment-based analysis and generates a set of read profiles serving as the input to the next step, the simulation stage. The simulation stage uses the model built in the previous step to produce in silico reads for a given reference genome. NanoSim is written in Python and R. The source files and manual are available at the Genome Sciences Centre website: http://www.bcgsc.ca/platform/bioinfo/software/nanosim</span></p>
<p><span>https://github.com/bcgsc/NanoSim</span></p><p>Address of the bookmark: <a href="http://www.bcgsc.ca/platform/bioinfo/software/nanosim" rel="nofollow">http://www.bcgsc.ca/platform/bioinfo/software/nanosim</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42490/bioinformatics-scientist-%E2%80%93-icmr-computational-genomics-centre</guid>
  <pubDate>Sat, 26 Dec 2020 10:18:29 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist – ICMR Computational Genomics Centre]]></title>
  <description><![CDATA[
<p>ICMR invites online applications, from Indian Citizens, up to 8th January 2020 till 5:30 PM to fill up the following post to be filled purely on a temporary basis under “ICMR Computational Genomics Centre” under Dr. Harpreet Singh, Head, Division of Biomedical Informatics (BMI), ICMR HQRS, New Delhi 110029.<br />The Terms &amp; Conditions for the post are as follows:</p>

<p>a) Scientist-B – UR (2 posts-Bioinformatics) on consolidated salary of Rs.48,000/- pm + HRA</p>

<p>b) Scientist C – UR (1 post -Bioinformatics) on consolidated salary of Rs. 51,000 pm+ HRA</p>

<p>c) Scientist B- UR (2 post-Statistics) on a consolidated salary of Rs.48,000/- pm +HRA</p>

<p>d) Computer Programmer 1 post UR &amp; 1 post SC on a consolidated salary of Rs. 32,500/- pm</p>

<p>e) Research Assistant -UR 1 post on a consolidated salary of Rs. 31,000/- pm</p>

<p>More at https://projectjobs.icmr.org.in/sccbioinformatics/uploads/recruitment/Adv_BMI_24122020.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34477/computational-genomics-applied-comparative-genomics</guid>
	<pubDate>Wed, 29 Nov 2017 05:11:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34477/computational-genomics-applied-comparative-genomics</link>
	<title><![CDATA[Computational Genomics: Applied Comparative Genomics]]></title>
	<description><![CDATA[<p><span>The primary goal of the course is for students to be grounded in theory and leave the course empowered to conduct independent genomic analyses.</span><span>&nbsp;We will study the leading computational and quantitative approaches for comparing and analyzing genomes starting from raw sequencing data. The course will focus on human genomics and human medical applications, but the techniques will be broadly applicable across the tree of life. The topics will include genome assembly &amp; comparative genomics, variant identification &amp; analysis, gene expression &amp; regulation, personal genome analysis, and cancer genomics. The grading will be based on assignments, a midterm exam, class presentations, and a significant class project. There are no formal course prerequisites, although the course will require familiarity with UNIX scripting and/or programming to complete the assignments and course project.</span></p><p>Address of the bookmark: <a href="https://github.com/schatzlab/appliedgenomics" rel="nofollow">https://github.com/schatzlab/appliedgenomics</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/40503/3-phd-positions-available-in-the-area-of-bioinformaticscomputational-biology-at-ulsteracuk</guid>
  <pubDate>Thu, 02 Jan 2020 12:41:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[3 PhD positions available in the area of Bioinformatics/Computational Biology at ulster.ac.uk]]></title>
  <description><![CDATA[
<p>3 PhD positions available in the area of Bioinformatics/Computational Biology, Machine Learning (ML)/Artificial Intelligence (AI), Biomarker Discovery, Stratified/Personalized Medicine in Mental Health, Diabetes and Multimorbidity. Please see details (weblinks) below:</p>

<p>1. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/510894<br />2. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/511458<br />3. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/512618</p>

<p>Looking for students with good computational/programming skills (preferable in Linux/Shell, Python and/or R) and knowledge in computational biology and statistics. However, students from more biology oriented background but strong interest to learn bioinformatics and programming are also encouraged to apply.</p>

<p>Informal inquiries are welcomed at: p.shukla@ulster.ac.uk</p>

<p>Dr Priyank Shukla PhD FHEA FCHERP<br />Lecturer (Asst Prof) in Stratified Medicine (Bioinformatics)</p>

<p>Northern Ireland Centre for Stratified Medicine<br />Biomedical Sciences Research Institute<br />University of Ulster (Magee Campus)<br />C-TRIC Building, Altnagelvin Area Hospital<br />Glenshane Road, Derry/Londonderry<br />BT47 6SB, Northern Ireland, United Kingdom</p>

<p>T: +44 28 7167 5690<br />E: p.shukla@ulster.ac.uk<br />W: https://www.ulster.ac.uk/staff/p-shukla</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/35267/a-computational-postdoc-position-and-a-bioinformatician-position</guid>
  <pubDate>Thu, 18 Jan 2018 16:29:42 -0600</pubDate>
  <link></link>
  <title><![CDATA[A computational postdoc position and a bioinformatician position]]></title>
  <description><![CDATA[
<p>A computational postdoc position and a bioinformatician position are available in Alessandro Romanel's Lab recently established at the Centre for Integrative Biology (CIBIO) in Trento, Italy. The positions are in the context of an AIRC grant and are immediately available.<br /> <br />Successful candidates will be involved in the design and implementation of strategies to study the role of inherited polymorphisms in combination with timedependent variables and somatic events on cancer genesis, progression and resistance.<br />The ideal postdoc candidate will have a PhD in Computer Science, Bioinformatics, Computational Biology or equivalent, experience in the analysis of next generation sequencing and high-density array data from human cells, strong analytical and quantitative background and programming skills. Background in cancer genomics is recommended.<br />The ideal bioinformatician candidate will have a four or five years degree in Computer Science, Bioinformatics or equivalent, experience in the management of large datasets, implementation of processing pipelines and strong programming skills. Background in biology/genomics is a plus.<br />Highly motivated individuals are invited to send a detailed CV, a cover letter describing research interests and experience, and contact information for two references to Alessandro Romanel (alessandro.romanel@unitn.it).</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42201/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design</guid>
	<pubDate>Sun, 20 Sep 2020 06:03:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42201/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design</link>
	<title><![CDATA[RosettaAntibodyDesign (RAbD): A general framework for computational antibody design]]></title>
	<description><![CDATA[<p><strong>RosettaAntibodyDesign (RAbD)</strong>&nbsp;is a generalized framework for the design of antibodies, in which a user can easily tailor the run to their project needs.&nbsp;<strong>The algorithm is meant to sample the diverse sequence, structure, and binding space of an antibody-antigen complex.</strong>&nbsp;It can be used for a multitude of project types, from denovo design to redesigns that improve binding affinity, optimize stability, or manipulate function.</p>
<p>The framework is based on rigorous bioinformatic analysis and rooted very much on our&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pubmed/21035459">recent clustering</a>&nbsp;of antibody CDR regions. It uses the&nbsp;<strong>North/Dunbrack CDR definition</strong>&nbsp;as outlined in the North/Dunbrack clustering paper.</p>
<p>More at</p>
<p>https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign</p>
<p>https://bio-jade.readthedocs.io/en/latest/installation.html</p><p>Address of the bookmark: <a href="https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign" rel="nofollow">https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/1926</guid>
	<pubDate>Sun, 11 Aug 2013 11:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/1926</link>
	<title><![CDATA[Want to Know which genome assembler rule the world ?]]></title>
	<description><![CDATA[<p><span><strong>Assemblathon 2</strong>: evaluating de novo methods of genome assembly&nbsp;</span></p><p><span><a href="http://www.gigasciencejournal.com/content/2/1/10/abstract">http://www.gigasciencejournal.com/content/2/1/10/abstract</a></span></p><p><span><a href="http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html">http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html</a></span></p><p><a href="http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p">http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3917/the-story-of-you-encode-and-the-human-genome</guid>
	<pubDate>Sat, 24 Aug 2013 18:49:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3917/the-story-of-you-encode-and-the-human-genome</link>
	<title><![CDATA[The Story of You: ENCODE and the human genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/TwXXgEz9o4w" frameborder="0" allowfullscreen></iframe><p>Ever since a monk called Mendel started breeding pea plants we've been learning about our genomes. In 1953, Watson, Crick and Franklin described the structure of the molecule that makes up our genomes: the DNA double helix. Then, in 2001, scientists wrote down the entire 3-billion letter code contained in the average human genome. Now they're trying to interpret that code; to work out how it's used to make different types of cells and different people. The ENCODE project, as it's called, is the latest chapter in the story of you. To read the ENCODE research papers and more, visit http://www.nature.com/ENCODE</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4761/dna-is-packaged-in-a-chromosome-experiment</guid>
	<pubDate>Mon, 23 Sep 2013 18:01:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4761/dna-is-packaged-in-a-chromosome-experiment</link>
	<title><![CDATA[DNA is packaged in a chromosome experiment]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fecfROFrp_c" frameborder="0" allowfullscreen></iframe>For more information, log on to-
http://shomusbiology.weebly.com/
Download the study materials here-
http://shomusbiology.weebly.com/bio-materials.html
A nucleosome is the basic unit of DNA packaging in eukaryotes, consisting of a segment of DNA wound in sequence around four histone protein cores.[1] This structure is often compared to thread wrapped around a spool.[2]

Nucleosomes form the fundamental repeating units of eukaryotic chromatin,[3] which is used to pack the large eukaryotic genomes into the nucleus while still ensuring appropriate access to it (in mammalian cells approximately 2 m of linear DNA have to be packed into a nucleus of roughly 10 µm diameter). Nucleosomes are folded through a series of successively higher order structures to eventually form a chromosome; this both compacts DNA and creates an added layer of regulatory control, which ensures correct gene expression. Nucleosomes are thought to carry epigenetically inherited information in the form of covalent modifications of their core histones. Nucleosomes were observed as particles in the electron microscope by Don and Ada Olins [4] and their existence and structure (as histone octamers surrounded by approximately 200 base pairs of DNA) were proposed by Roger Kornberg.[5][6] The role of the nucleosome as a general gene repressor was demonstrated by Lorch et al. in vitro [7] and by Han and Grunstein in vivo.]]></description>
	
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