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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29912?offset=1360</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37959/rainbow-an-integrated-tool-for-efficient-clustering-and-assembling-rad-seq-reads</guid>
	<pubDate>Fri, 19 Oct 2018 08:23:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37959/rainbow-an-integrated-tool-for-efficient-clustering-and-assembling-rad-seq-reads</link>
	<title><![CDATA[Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads]]></title>
	<description><![CDATA[<p><span>Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top&ndash;down manner. And along a guided tree, it iteratively merges sibling leaves in a bottom&ndash;up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, we show that Rainbow is more competent than the other tools in dealing with RAD-seq data</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/bio-rainbow/files/" rel="nofollow">https://sourceforge.net/projects/bio-rainbow/files/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25406/assistant-professor-bioinformatics-at-alagappa-university</guid>
  <pubDate>Thu, 03 Dec 2015 23:30:43 -0600</pubDate>
  <link></link>
  <title><![CDATA[ASSISTANT PROFESSOR Bioinformatics at ALAGAPPA UNIVERSITY]]></title>
  <description><![CDATA[
<p>ALAGAPPA UNIVERSITY<br /> Recruitment and Sarkari Naukri for the Post of ASSISTANT PROFESSOR Bioinformatics<br />Job Description UGC scale of pay is applicable. For eligibility qualifications and other norms, please refer to the ?Instructions to the Candidates? available with the application forms which can be had on payment of Rs.520/- inclusive of Rs.20/- for postage. For SC/ST, Rs.320/- inclusive of Rs.20/- for postage on enclosure of a copy of the community certificate. Payment is to be made by means of Demand Draft drawn on any nationalized bank in favour of ?The Registrar, Alagappa University? payable at Karaikudi. Candidates can also download the application form and instructions to the candidates from httpwww.alagappauniversity.ac Filled-in application should reach on or before 19.10.2015<br />Salary for Job : Rs.15600-39100+AGP Rs.6000<br />Education : Good academic record with at least 55 marks (or an equivalent grade in a point scale wherever grading system is followed) at the Masters Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university. Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.Notwithstanding anything contained in sub-clauses (i) and (ii) above, the candidates, who are, or have been awarded a Ph.D. degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.<br />Number of Vacancies : 02<br />Naukri Location : Other City(s) in Tamil Nadu<br />Address : KARAIKUDI ? 630 003<br />Last Date to Apply : 2015-12-04<br />Apply Process : written test/interview</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Sat, 06 Jul 2019 03:48:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25651/jrftraineeshipstudentship-bioinformatics</guid>
  <pubDate>Thu, 10 Dec 2015 13:49:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF/Traineeship/Studentship Bioinformatics]]></title>
  <description><![CDATA[
<p>JRF/Traineeship/Studentship Bioinformatics</p>

<p>Eligibility : ME/M.Tech(Bio-Informatics/Bio-Chemistry Engg, CSE), MSc(Bio-Informatics, CS)</p>

<p>Location : Delhi</p>

<p>Last Date : 18 Dec 2015</p>

<p>Hiring Process : Walk - In<br />IARI - Job Details</p>

<p>JRF/Traineeship/Studentship Bioinformatics job position in Indian Agricultural Research Institute (IARI) purely temporary</p>

<p>JRF</p>

<p>Qualification: i) Master’s degree in Bioinformatics or Computer Science + NET qualification, or ii) M. Tech degree in Bioinformatics or Computer Science/Engineering</p>

<p>Desirable: Efficiency to handle agricultural databases and bioinformatics tool development</p>

<p>Pay Scale :Rs 25000/- </p>

<p>Age limit : 35 years</p>

<p>Traineeship/2 Post</p>

<p>Qualification: M.Sc./M. Tech (Bioinformatics) with 60 % marks from a recognized University </p>

<p>Pay Scale :Rs. 8000/-consolidated</p>

<p>Age limit : 35 years</p>

<p>Studentship/4 Post</p>

<p>Qualification: Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University</p>

<p>Pay Scale :Rs. 8000/-consolidated</p>

<p>Age limit : 35 years<br />How to apply</p>

<p>Walk-in-Interview will be held on 18th December 2015 at 10:00 AM at AKMU, LBS Building,IARI, Pusa Campus, New Delhi-110012. Bring self attested copies and originals of all certificates ( class 10th )onwards along with biodata in the attached format, proof of date of birth, one passport size photo, NOC from present employer, if any.</p>

<p>More at http://www.iari.res.in/index.php?option=com_jumi&amp;fileid=24&amp;Itemid=664</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</guid>
	<pubDate>Fri, 07 Feb 2020 14:08:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</link>
	<title><![CDATA[Free Genomics data !]]></title>
	<description><![CDATA[<p><span>The specimens were collected by the Oxford Wytham Woods and Edinburgh Lohse lab teams. DNA extraction and sequencing was carried out by the Sanger Institute Scientific Operations teams. Assemblies were carried out by the Tree of Life team (Shane McCarthy) and colleagues in Pacific Biosciences (Jonas Korlach).</span></p>
<p><a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p><p>Address of the bookmark: <a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/" rel="nofollow">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25815/jrf-bioinformatics-job-position-in-university-of-hyderabad</guid>
  <pubDate>Tue, 29 Dec 2015 01:00:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics job position in University of Hyderabad]]></title>
  <description><![CDATA[
<p>JRF Bioinformatics</p>

<p>Eligibility : ME/M.Tech(Bio-Informatics/Bio-Chemistry Engg), MSc(Bio-Informatics)</p>

<p>Location : Hyderabad</p>

<p>Last Date : 30 Dec 2015</p>

<p>Hiring Process : Written-test<br />University of Hyderabad</p>

<p>JRF Bioinformatics job position in University of Hyderabad </p>

<p>Project Entitled : Programming protective humoral responses with novel vaccine formulations against Dengue Virus</p>

<p>Essential Qualifications : M. Sc. in Life Sciences/Bioinformatics/ or M. Tech in Bioinformatics with a minimum of 60% marks and with CSIR-UGC JRF/NET or valid GATE score are preferred. Desirable : Candidates should have six months to one year hands on experience in molecular biology techniques like gene cloning, protein expression and purification, hands on various nano-formulations for drug/vaccine delivery, immunological assays including animal handling, immunizations, T cells and B cell assays or Candidate should have strong background in Bioinformatics and computational Biology, good programming skill particularly proficiency in R/PERL/PYTHON. Candidates interested in above position should send a one page statement clearly explaining how their skills are relevant to the above said position. The candidates should also enclose detailed CV and the name/Email IDs of three references</p>

<p>Fellowship : Rs. 16,000 p.m. + 30% H.R.A. for the first two years (Revised DBT fellowship guidelines maybe applicable)</p>

<p>Duration : The appointment will be on temporary basis for a period of one year. Based on performance, the appointment could be extended till the end of project<br /> <br />How to apply</p>

<p>Submit your application (hardcopy) in a closed envelope to Dr.Nooruddin<br />Khan, Room S-66B,Department of Biotechnology and Bioinfromatics, School of Life Sciences, University of Hyderabad, Gachibowli, Hyderabad 500 046 or E mail: nklabsls@gmail.com. Last date for receipt of applications is on or before 30.12.2015</p>

<p>More at http://uohyd.ac.in/index.php/component/content/article/87-administration/recruitments/129</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</guid>
	<pubDate>Mon, 17 Aug 2020 05:21:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</link>
	<title><![CDATA[SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis]]></title>
	<description><![CDATA[<p><span>SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, &hellip;).</span><br><span>The bioinformatics treatment is based on Vsearch [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/27781170">Rognes 2016</a><span>] which showed to be both accurate and fast [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/26664811">Wescott 2015</a><span>].The statistical analysis is based on DESeq2 R package [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/20979621">Anders and Huber 2010</a><span>] which robustly identifies the differential abundant features as suggested in [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/">McMurdie and Holmes 2014</a><span>] and [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/">Jonsson2016</a><span>]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/25516281">Love 2014</a><span>].</span><br><span>SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_presentation.pdf">here</a><span>&nbsp;and a poster&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_poster.pdf">here</a><span>.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4</a></span></p><p>Address of the bookmark: <a href="https://github.com/aghozlane/shaman" rel="nofollow">https://github.com/aghozlane/shaman</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/25993/hoffman-lab</guid>
  <pubDate>Tue, 12 Jan 2016 02:47:41 -0600</pubDate>
  <link></link>
  <title><![CDATA[Hoffman Lab]]></title>
  <description><![CDATA[
<p>They develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight.</p>

<p>https://www.pmgenomics.ca/hoffmanlab/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</guid>
	<pubDate>Sat, 26 Dec 2020 08:35:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</link>
	<title><![CDATA[FastProNGS: fast preprocessing of next-generation sequencing reads]]></title>
	<description><![CDATA[<p><span>FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/Megagenomics/FastProNGS" rel="nofollow">https://github.com/Megagenomics/FastProNGS</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44171/hairsplitter-assembling-long-reads-in-an-unknown-number-of-haplotypes</guid>
	<pubDate>Wed, 07 Dec 2022 00:13:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44171/hairsplitter-assembling-long-reads-in-an-unknown-number-of-haplotypes</link>
	<title><![CDATA[HairSplitter: assembling long reads in an unknown number of haplotypes]]></title>
	<description><![CDATA[<p>Pros and cons of HairSplitter Limitations of HairSplitter:</p>
<p>Not very fast: it re-polishes the whole assembly&nbsp;</p>
<p>Limited in the number of haplotypes</p>
<p>Strengths of HairSplitter:</p>
<p>Very modular, can be used with any assembler</p>
<p>Naive: makes no assumption on ploidy, parameter-free</p>
<p>Safe: won&rsquo;t artificially duplicate contigs</p>
<p>&nbsp;</p>
<p>HairSplitter splits collapsed assemblies from &ldquo;draft&rdquo; assemblies obtained by any means</p>
<p>HairSplitter can recover haplotypes and distinguish repeated elements</p>
<p>Only needs sequencing reads, potentially error-prone</p>
<p>HairSplitter splits collapsed assemblies from &ldquo;draft&rdquo; assemblies obtained by any means</p>
<p>HairSplitter can recover haplotypes and distinguish repeated elements</p>
<p>Only needs sequencing reads, potentially error-prone</p>
<p>Not really available yet (github.com/RolandFaure/HairSplitter)</p>
<p>https://hal.archives-ouvertes.fr/hal-03864075/file/RolandFaure_presentation_SeqBIM_2022.pdf</p><p>Address of the bookmark: <a href="https://hal.archives-ouvertes.fr/hal-03817928/document" rel="nofollow">https://hal.archives-ouvertes.fr/hal-03817928/document</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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