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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29144?offset=450</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42633/protocol-for-de-novo-genome-assembly-using-illumina-reads</guid>
	<pubDate>Sat, 16 Jan 2021 21:42:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42633/protocol-for-de-novo-genome-assembly-using-illumina-reads</link>
	<title><![CDATA[Protocol for De novo Genome Assembly using Illumina Reads]]></title>
	<description><![CDATA[<p>In this protocol, we address and describe the de novo assembly method for small to medium-sized genomes.</p><p><strong>What is de novo genome assembly?<br /></strong>The method of taking a large number of short DNA sequences and placing them back together to create a reflection of the original chromosomes from which the DNA originated relates to genome assembly. No previous knowledge of the source DNA sequence length, structure or composition is inferred by De novo genome assemblies. The DNA of the target organism is split up into millions of tiny parts and read on a sequencing computer in a genome sequencing experiment. Depending on the sequencing system used, these "reads" range from 20 to 1000 nucleotide base pairs (bp) in length. Usually, length reads of 36 - 150 bp are produced for Illumina style short read sequencing. These reads can be either &ldquo;single ended&rdquo; as described above or &ldquo;paired end.&rdquo;</p><p><strong>Why genome assembly?</strong><br />In basic research into why and how they live, as well as in applied topics, identifying the DNA sequence of an organism is useful. Awareness of a DNA sequence may be useful in virtually any biological research because of the relevance of DNA to living things. For example, it may be used in medicine to classify, diagnose and eventually improve genetic disorder therapies. Similarly, pathogens study can lead to treatments for infectious diseases.</p><p><strong>Raw NGS data</strong><br />Reads can be saved as a Fasta file as text or in a FastQ file with their attributes.&nbsp;FastQ is the most common read file format since this is what the Illumina sequencing pipeline creates. This will henceforth be the subject of our conversation.</p><p><strong>In a nutshell the protocol:</strong> <br />Get the sequence file(s) read from the sequencing machine (s). <br />Look at the readings - have an idea of what you have and what the standard is like. <br />If required, raw data cleanup/quality trimming. <br />Choose an adequate parameter set for assembly. <br />Assemble the data into scaffolds/contigs. <br />Examine the assembly performance and determine the efficiency of the assembly.</p><p><strong>Read Quality Control:</strong><br />Check the qualiy with fastQC.<br />Script<br />https://bioinformaticsonline.com/snippets/view/42540/install-fastqc-using-conda</p><p>Quality trimming/cleanup of read files.<br />This function trims adapters, barcodes and other contaminants from the reads.<br />Script<br />https://bioinformaticsonline.com/snippets/view/42542/trimmomatic-command</p><p><strong>Genome Assembly:</strong><br />The object of this portion of the protocol is to explain the method of assembling the reads trimmed by quality into draft contigs.</p><blockquote><p>spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o result_of_spades_assembly_all_illumina</p></blockquote><p>A significant range of short-read assemblers are available. Everyone with strengths and disadvantages of their own. <br /><em>Some of the assemblers available include:</em><br />Velvet<br />SOAP-denovo<br />MIRA<br />ALLPATHS</p><p>Next step is to assess the suitability and what to do with a draft package of contiguous details for the remainder of the study now.&nbsp;Few stuff you can note about the contigs you just created:&nbsp;They're the draft Contigs. Any mis-assemblies can occur.</p><p><strong>Mis-assembly checking and assembly metric tools:</strong><br />QUAST - Quality assessment tool for genome assembly http://bioinf.spbau.ru/quast<br />Mauve assembly metrics - http://code.google.com/p/ngopt/wiki/How_To_Score_Genome_Assemblies_with_Mauve<br />InGAP-SV - https://sites.google.com/site/nextgengenomics/ingap and http://ingap.sourceforge.net/<br />inGAP is also useful for finding structural variants between genomes from read mappings.</p><p><strong>Genome finishing tools:</strong><br />Semi-automated gap fillers:<br />Gap filler - http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/gapfiller/</p><p>IMAGE (V2) - http://sourceforge.net/apps/mediawiki/image2/index.php?title=Main_Page</p><p><strong>Genome visualisers and editors:</strong><br />Artemis - http://www.sanger.ac.uk/resources/software/artemis/<br />IGV - http://www.broadinstitute.org/igv/</p><p><strong>Automated and semi automated annotation tools:</strong><br />Prokka - https://github.com/tseemann/prokka<br />RAST - http://www.nmpdr.org/FIG/wiki/view.cgi/FIG/RapidAnnotationServer<br />JCVI Annotation Service - http://www.jcvi.org/cms/research/projects/annotation-service/</p><p><strong>Frequent command use for the analysis are at:</strong></p><p>https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly<br />https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <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/43315/genome-assembly-workshop-2020</guid>
	<pubDate>Wed, 25 Aug 2021 04:30:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</link>
	<title><![CDATA[Genome Assembly Workshop 2020]]></title>
	<description><![CDATA[<p><span>Our team offers custom bioinformatics services to academic and private organizations. We have a strong academic background with a focus on cutting edge, open source software. We replicate standard analysis pipelines (best practices) when appropriate, and/or develop novel applications and pipelines when needed, however we always emphasize biological interpretation of the data.</span></p>
<p><span>More at&nbsp;https://ucdavis-bioinformatics-training.github.io/</span></p><p>Address of the bookmark: <a href="https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro" rel="nofollow">https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro</a></p>]]></description>
	<dc:creator>Jit</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/researchlabs/view/43762/vicoso-group</guid>
  <pubDate>Wed, 02 Feb 2022 02:51:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Vicoso group]]></title>
  <description><![CDATA[
<p>The Vicoso group investigates how sex chromosomes evolve over time, and what biological forces are driving their patterns of differentiation.</p>

<p>The Vicoso group is interested in understanding several aspects of the biology of sex chromosomes, and the evolutionary processes that shape their peculiar features. By combining the use of next-generation sequencing technologies with studies in several model and non-model organisms, they can address a variety of standing questions, such as: Why do some Y chromosomes degenerate while others remain homomorphic, and how does this relate to the extent of sexual dimorphism of the species? What forces drive some species to acquire global dosage compensation of the X, while others only compensate specific genes? What are the frequency and molecular dynamics of sex-chromosome turnover?</p>

<p>More at https://ist.ac.at/en/research/vicoso-group/<br />http://pub.ist.ac.at/~bvicoso/</p>
]]></description>
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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/bookmarks/view/43714/hiv-genome-database</guid>
	<pubDate>Fri, 21 Jan 2022 05:40:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43714/hiv-genome-database</link>
	<title><![CDATA[HIV genome database !]]></title>
	<description><![CDATA[<p>HIV resources</p>
<p>https://www.hiv.lanl.gov/components/sequence/HIV/search/search.html</p><p>Address of the bookmark: <a href="https://www.hiv.lanl.gov/components/sequence/HIV/search/search.html" rel="nofollow">https://www.hiv.lanl.gov/components/sequence/HIV/search/search.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/bookmarks/view/43909/human-complete-genome</guid>
	<pubDate>Wed, 06 Jul 2022 06:42:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43909/human-complete-genome</link>
	<title><![CDATA[Human Complete Genome]]></title>
	<description><![CDATA[<h1 dir="auto">Telomere-to-telomere consortium</h1>
<p dir="auto">We have sequenced the CHM13hTERT human cell line with a number of technologies. Human genomic DNA was extracted from the cultured cell line. As the DNA is native, modified bases will be preserved. The data includes 30x&nbsp;<a href="https://www.pacb.com/">PacBio</a>&nbsp;<a href="https://www.ncbi.nlm.nih.gov/sra/?term=SRX789768*+CHM13">HiFi</a>, 120x coverage of&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>, 70x&nbsp;<a href="https://www.pacb.com/">PacBio</a>&nbsp;CLR, 50x&nbsp;<a href="https://www.10xgenomics.com/">10X Genomics</a>, as well as&nbsp;<a href="https://bionanogenomics.com/technology/dls-technology/">BioNano DLS</a>&nbsp;and&nbsp;<a href="https://arimagenomics.com/kit/">Arima Genomics HiC</a>. Most raw data is available from this site, with the exception of the PacBio data which was generated by the University of Washington/PacBio and is available from&nbsp;<a href="https://www.ncbi.nlm.nih.gov/sra?linkname=bioproject_sra_all&amp;from_uid=269593">NCBI SRA</a>.</p>
<p dir="auto">A UCSC browser is available for&nbsp;<a href="https://genome.ucsc.edu/h/GCA_009914755.4">v2.0</a>&nbsp;(as well as legacy&nbsp;<a href="http://genome.ucsc.edu/cgi-bin/hgTracks?genome=t2t-chm13-v1.0&amp;hubUrl=http://t2t.gi.ucsc.edu/chm13/hub/hub.txt">v1.0</a>&nbsp;and&nbsp;<a href="http://genome.ucsc.edu/cgi-bin/hgTracks?genome=t2t-chm13-v1.1&amp;hubUrl=http://t2t.gi.ucsc.edu/chm13/hub/hub.txt">v1.1</a>&nbsp;versions). An interactive dotplot visualization of all genomic repeats is also available from&nbsp;<a href="https://resgen.io/paper-data/T2T-Nurk-et-al-2021/views/t2t-identity-v2">resgen.io</a>. Known issues identified in the assembly are tracked at&nbsp;<a href="https://github.com/marbl/CHM13-issues">CHM13 issues</a>.</p>
<p dir="auto">&nbsp;</p>
<p dir="auto">MORE at&nbsp;https://github.com/marbl/CHM13</p><p>Address of the bookmark: <a href="https://www.science.org/doi/10.1126/science.abj6987" rel="nofollow">https://www.science.org/doi/10.1126/science.abj6987</a></p>]]></description>
	<dc:creator>Shruti Paniwala</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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