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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27076?offset=500</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</guid>
	<pubDate>Tue, 07 Jul 2015 16:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</link>
	<title><![CDATA[Scaffolding of a bacterial genome using MinION nanopore sequencing]]></title>
	<description><![CDATA[<p><span>Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program.</span></p><p>Address of the bookmark: <a href="http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html" rel="nofollow">http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8520/rcb-gurgaon-bioinformatics-rapa-openings</guid>
  <pubDate>Thu, 27 Feb 2014 08:42:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[RCB Gurgaon Bioinformatics RA/PA Openings]]></title>
  <description><![CDATA[
<p>Advt. No.1/2014</p>

<p>Recruitment for Research Associate and Project Assistant positions</p>

<p>Regional Centre for Biotechnology (RCB) is an autonomous academic institution established by the Department of Biotechnology, Govt. of India with regional and global partnerships synergizing with the programmes of UNESCO as a Category II Centre. The primary focus of RCB is to provide world class education, training and conduct innovative research at the interface of multiple disciplines to create high quality human resource in disciplinary and interdisciplinary areas of biotechnology in a globally competitive research milieu. </p>

<p>Research Associate (02 Position)</p>

<p>Consolidated emoluments Rs.22000/- + 30% H.R.A. p.m.</p>

<p>Essential: Ph.D. in Natural Sciences, minimum 60% marks in all qualifying exams and below 35 years of age.</p>

<p>Desirable: Prior experience at the PhD level in Biochemistry, Bioinformatics and Proteomics with a strong motivation for a career in research is highly desirable.</p>

<p>Strong PhD level training with proteins chemistry, protein purification and statistical analysis of proteomics or genomics dataset will be preferred. Either/ both qualifications should be substantiated by published papers.</p>

<p>Inter-Institutional Program for  Maternal, Neonatal and Infant  Sciences: A translational approach to studying preterm birth. </p>

<p>Principal Investigator: Dr. Dinakar M. Salunke </p>

<p>Applicants may apply along with the requisite documents (attested copies) pertaining to proof of date of birth, academic/professional qualifications, experience (if any), in the prescribed format available on our websites: www.rcb.res.in and www.rcb.ac.in. Applications should be sent to the Registrar, Regional Centre for Biotechnology, 180 Udyog Vihar Phase 1, Gurgaon-122016, Haryana, India, through Registered Post on or before Feb 28, 2014. A soft copy of the application should be sent by email to registrar@rcb.res.in. Incomplete applications or applications received after Feb 28, 2014 will not be entertained. </p>

<p>More at https://www.rcb.res.in/Advt-1._for_websites_PTB-revised.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</guid>
	<pubDate>Wed, 19 Oct 2016 05:25:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</link>
	<title><![CDATA[Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016]]></title>
	<description><![CDATA[<p><strong><a href="http://www.strand-ngs.com/webinar_registration">Live Webinar on RNA-Seq Data Analysis</a></strong></p><p><a href="http://www.strand-ngs.com/webinar_registration">Abstract: </a>Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.</p><p><a href="http://www.strand-ngs.com/webinar_registration">Speaker:</a> Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences</p><p>Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 1</a> for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 2</a> for AFO/ EMEA: 9:00 AM PST</p><p>Register here <a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p>]]></description>
	<dc:creator>Strand</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8504/update-genome-workbench-2715-released</guid>
	<pubDate>Wed, 26 Feb 2014 16:12:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8504/update-genome-workbench-2715-released</link>
	<title><![CDATA[Update Genome Workbench 2.7.15 released]]></title>
	<description><![CDATA[<p>NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. With Genome Workbench, you can view data in publically available sequence databases at NCBI, and mix this data with your own private data.</p><p><img src="http://www.ncbi.nlm.nih.gov/core/assets/gbench/images/firstscreen_still.gif" alt="Introductory screen shot" style="border: 0px; border: 0px;"></p><p>Genome Workbench can display sequence data in many ways, including graphical sequence views, various alignment views, phylogenetic tree views, and tabular views of data. It can also align your private data to data in public databases, display your data in the context of public data, and retrieve BLAST results.</p><p>Genome Workbench is built on the NCBI C++ ToolKit and uses cross-platform APIs for graphics. It runs on your local machine, and is available for Windows 2000/XP, Linux, MacOS X, and various flavors of Unix.</p><p>NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. Genome Workbench was developed entirely in-house at NCBI and makes use of the NCBI C++ ToolKit. The C++ ToolKit provides a convenient and flexible cross-platform API for managing system internals, database connections, network sockets, and the NCBI data model. In addition, the C++ ToolKit provides the Object Manager, which abstracts handling of sequences and sequence-related objects.</p><p>&nbsp;New Features in Genome Workbench 2.7.15 <br /><br /></p><ul>
<li>Multiple Alignment View: implemented adaptive feature display when zooming in</li>
<li>Active Objects Inspector replaces Selection Inspector. New View should offer an improved selection context examination. See Using Active Objects Inspector tutorial for more details.</li>
<li>Binary packages for Linux OpenSUSE 13.1 are now available</li>
</ul><p><br />Bug Fixes and Improvements in Genome Workbench 2.7.15 <br /><br /></p><ul>
<li>Fixed major issue with OpenGL overlay/scrolling. Could cause crashes or view scrolling irregularities</li>
<li>Multiple Pane View: fixed crash on loading BLAST results</li>
<li>Graphical Sequence View: fixed crash on zooming in and out, related to SNP track</li>
<li>Graphical Sequence View: fixed Go To Position dialog to give better diagnostics in case of a user error</li>
<li>Graphical Sequence View: PDF export fixed rendering of Markers with commas in the name</li>
<li>Text View / Flat File: fixed Mac OS rendering issues</li>
<li>Text View / Flat File: performance optimization, extended capabilities of real-time rendering of molecules to tens of thousands</li>
<li>File Import: optimization improvement to speed up load of files containing multiple project items</li>
<li>File Import: remapping stage now shows accession.version and description of molecules, instead of plain GI numbers</li>
<li>Mac OS: improved tooltips for toolbar buttons</li>
<li>Phylogenetic Tree Builder Tool: improved diagnostics of errors</li>
<li>Multiple Alignment View: optimizations to avoid main GUI freezes</li>
<li>Open Dialog: removed duplicate elements in table of genomes (load Genome)</li>
<li>PDF export: fixed issue with XREF table errors</li>
<li>Tree View: fixed issues with showing Force Layout progress on Mac OS</li>
<li>Tree View: PDF export fixed issues for showing labels of collapsed nodes</li>
<li>Tree View: added an option to stop layout</li>
<li>Tree View: broadcasting mechanism fixed not to accumulate selected nodes</li>
</ul><p>Reference:</p><p>NCBI news</p><p>http://www.ncbi.nlm.nih.gov/tools/gbench/</p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</guid>
	<pubDate>Fri, 09 Jun 2017 04:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</link>
	<title><![CDATA[Quick next generation sequencing (NGS) terms definition]]></title>
	<description><![CDATA[<p><strong>fragment size:</strong><span>&nbsp;the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [&delta;min,&delta;max]. Most (&gt;90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.</span><br /><br /><strong>concordant reads:</strong><span>&nbsp;a read pair is called concordant if they can be mapped to the reference genome as &ldquo;expected&rdquo;: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.</span><br /><br /><strong>discordant reads:</strong><span>&nbsp;briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.</span><br /><br /><strong>split reads:</strong><span>&nbsp;a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).</span><br /><br /><strong>read depth:</strong><span>&nbsp;number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that &ldquo;cover&rdquo; each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8857/junior-research-fellow-at-iari</guid>
  <pubDate>Mon, 10 Mar 2014 13:10:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[Junior Research Fellow at IARI]]></title>
  <description><![CDATA[
<p>DIVISION OF NEMATOLOGY<br />INDIAN AGRICULTURAL RESEARCH INSTITUTE<br />NEW DELHI 110012</p>

<p>Applications are invited for the posts of one Junior Research Fellow in the DBT funded project entitled “Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.</p>

<p>Essential qualifications for JRF: First class M. Sc. / M. Tech in Bioinformatics. Knowledge of programming language, pearl, Statistics and database – HTML, CSS, Java script.</p>

<p>Desirable qualifications: Experience in handling next generation sequencing data</p>

<p>Age limit: 35 years maximum (5 year relaxation for SC/ST and women candidates) Emoluments: 16,000 + 30% HRA.</p>

<p>The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.</p>

<p>Those who are interested in pursuing Ph.D with strong research aptitude are preferred.</p>

<p>Interested candidates may attend the Walk in interview on 25th March 2014 along with the duly filled application forms (format in the following page) with all the relevant documents.</p>

<p>Venue: Division of Nematology, Indian Agricultural Research Institute, New Delhi 110012 (Room No. 306, 3rd floor, LBS building)</p>

<p>Reporting Time: Interested candidates should report strictly between 10.00 to 10.30 AM.</p>

<p>Interview time: 10.30 AM</p>

<p>Short-listed candidates will be called for interview at New Delhi. However, no TA and DA will be paid for attending the interview.</p>

<p>Advertisement:</p>

<p>https://www.iari.res.in/files/JRF_Nema-07032014-20140307-170017.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8972/bioinformaticcomputational-postdoc-at-south-dakota-state-university</guid>
  <pubDate>Wed, 12 Mar 2014 10:02:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatic/computational postdoc at South Dakota State University]]></title>
  <description><![CDATA[
<p>We seek an enthusiastic postdoctoral researcher to work with the Plant Science team within the Biochemical Spatio-temporal NeTwork Resource (BioSNTR). Bio-SNTR</p>

<p>is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.<br />Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.</p>

<p> <br />Required Qualifications:<br />• Ph.D. in plant computational biology or bioinformatics.<br />• Experience in a high performance computing environment.<br />• Perl, Python and Java programming experience<br />• Data management and database development experience</p>

<p>Desired Qualifications:<br />• Parallel computing experience<br />• Experience working in a multidisciplinary environment</p>

<p>Contact Information<br />South Dakota State University<br />Plant Science<br />Anne Fennell<br />anne.fennell@sdstate.edu<br />Tel. Number: 605-688-6373<br />http://www.biosntr.org</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</guid>
	<pubDate>Fri, 08 Jun 2018 10:47:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</link>
	<title><![CDATA[HALC: High throughput algorithm for long read error correction]]></title>
	<description><![CDATA[HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach)

HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.<p>Address of the bookmark: <a href="https://github.com/lanl001/halc" rel="nofollow">https://github.com/lanl001/halc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9029/syntax-for-secure-copy-scp</guid>
	<pubDate>Thu, 13 Mar 2014 17:01:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9029/syntax-for-secure-copy-scp</link>
	<title><![CDATA[Syntax for Secure Copy (scp)]]></title>
	<description><![CDATA[<div><p>In our day to day research activity, we need to securely copy our data from several to local computer and visa-versa. I am jotting down some of the commonly used SCP command for your future help. Hope you all will like it</p><p>What is Secure Copy?<br /><br />scp allows files to be copied to, from, or between different hosts. It uses ssh for data transfer and provides the same authentication and same level of security as ssh.</p><p><br />Examples</p><p><br /><strong>Copy the file "gene.txt" from a remote host to the local host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@remotehost.edu:gene.txt /some/local/directory<br /><br /><strong>Copy the file "foobar.txt" from the local host to a remote host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp gene.txt your_username@remotehost.edu:/some/remote/directory<br /><br /><strong>Copy the directory "chromosome" from the local host to a remote host's directory "bar"</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp -r chromosome your_username@remotehost.edu:/some/remote/directory/bar<br /><br /><strong>Copy the file "gene.txt" from remote host "rh1.edu" to remote host "rh2.edu"</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@rh1.edu:/some/remote/directory/gene.txt \<br />&nbsp;&nbsp;&nbsp; your_username@rh2.edu:/some/remote/directory/<br /><br /><strong>Copying the files "gene.txt" and "cancer.txt" from the local host to your home directory on the remote host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp gene.txt cancer.txt your_username@remotehost.edu:~<br /><br /><strong>Copy the file "gene.txt" from the local host to a remote host using port 2264</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp -P 2264 gene.txt your_username@remotehost.edu:/some/remote/directory<br /><br /><strong>Copy multiple files from the remote host to your current directory on the local host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@remotehost.edu:/some/remote/directory/\{a,b,c\} .<br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@remotehost.edu:~/\{gene.txt,cancer.txt\} .<br /><br /><strong>scp Performance</strong><br /><br />By default scp uses the Triple-DES cipher to encrypt the data being sent. Using the Blowfish cipher has been shown to increase speed. This can be done by using option -c blowfish in the command line.<br /><br />&nbsp;&nbsp;&nbsp; $ scp -c blowfish some_file your_username@remotehost.edu:~<br /><br />It is often suggested that the -C option for compression should also be used to increase speed. The effect of compression, however, will only significantly increase speed if your connection is very slow. Otherwise it may just be adding extra burden to the CPU. An example of using blowfish and compression:<br /><br />&nbsp;&nbsp;&nbsp; $ scp -c blowfish -C local_file your_username@remotehost.edu:~</p></div>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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