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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27110?offset=1050</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7998/faculty-positions-at-iiit-allahabad</guid>
  <pubDate>Thu, 23 Jan 2014 06:19:34 -0600</pubDate>
  <link></link>
  <title><![CDATA[FACULTY POSITIONS AT IIIT-ALLAHABAD]]></title>
  <description><![CDATA[
<p>OPENINGS OF FACULTY POSITIONS AT IIIT-ALLAHABAD</p>

<p>(Under Tenure-Track Model)</p>

<p>Open Advt. No IIITA/DIC/16012014</p>

<p>IIIT-Allahabad has several Openings for the Faculty positions at the Assistant Professor level.</p>

<p>It is a regular tenure-track faculty positions for 3-5 years in teaching and research. A regular faculty is expected to engage heavily in research and teaching. The eligibility criteria for regular faculty positions are similar as in IITs. For an Assistant Professor position, a candidate must have a PhD (in IT/Computer Science &amp;/or Engineering/Electrical, Electronics &amp;/or Communication Engineering/etc; for interdisciplinary areas the PhD may be in an appropriate field), plus three years experience. However, for PhDs from a well known University/Institute (e.g. IITs/IISc/TIFR/ISI in India or well known research universities across the world), and a good research/academic record, the 3 years experience requirement may be waived.</p>

<p>The pay scale for faculty is same as in IITs. Other benefits include initiation research grant, travel support, book grant, professional society membership, etc., and personal benefits such as medical/LTC, on campus subsidized family housing with excellent modern infrastructural facilities.</p>

<p>Areas of Interest</p>

<p>IIIT-Allahabad aims to build strong research groups in important and emerging areas in CS/IT/ECE as well as in emerging interdisciplinary areas, and applications are invited in all these areas. Some of the areas of special interest, besides strengthening the existing research areas, are : Software Engineering, Theoretical Computer Science, Cyber Physical Systems, Robotics, Network science, Digital Media, Computational neuroscience, Machine learning, Healthcare informatics, Computational Biology, Communications networks (both at hardware and protocol levels), Circuits (including VLSI, analog, low power, etc), Energy systems and technologies, Biomedical electronics and systems, Computer Architecture, signal/image processing, Embedded and control systems.</p>

<p>Application Process</p>

<p>Interested candidates can apply by sending their detailed CV with list of publications clearly mentioning Journal names and citation index with three references through email entitled “Faculty positions at IIIT Allahabad” to faculty.applications@iiita.ac.in. Do not send your applications in any other email addresses. Applications will be considered regularly, hence there is no deadline for applying.</p>

<p>Important Clarifications on Eligibility</p>

<p>A PhD in CS/IT (or other disciplines, as announced) is the minimum expected requirement for an Assistant Professor.</p>

<p>Advertisement: http://iiita.ac.in/pub/Faculty-Position-IIITA1.pdf</p>
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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/opportunity/view/11528/post-doctoral-research-assistant-in-genetics</guid>
  <pubDate>Thu, 05 Jun 2014 16:01:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Post-doctoral Research Assistant in Genetics]]></title>
  <description><![CDATA[
<p>Post-doctoral Research Assistant in Genetics<br />Camden, North London<br />£31.1K per annum inclusive of London Weighting</p>

<p>This is a fixed term post for 36 months.</p>

<p>We wish to recruit a highly motivated, postdoctoral scientist to carry out a BBSRC funded project in the laboratory of Dr. Denis Larkin. The project is focused on developing and applying new algorithms to study genome and chromosome evolution in birds, mammals and other vertebrate species using whole-genome sequences and existing algorithms. The post holder will use cutting edge computational and laboratory approaches to generate chromosomal assemblies for sequenced genomes, study chromosomal structures and genome differences between bird and other vertebrate species in attempt to identify species- and clade-specific genome signatures.</p>

<p>Applicants must have a Ph.D. and a track record of success, as indicated by first-author publications in international journals. They must possess excellent organisation skills and be capable of individual initiative and of interacting as part of a team. Applicants with extensive practical experience in bioinformatics or computer science, programming, visualization, handling of large data sets, high-performance computing are encouraged to apply. The post will involve collaboration with a wide range of academic partners both within the UK, EU and worldwide. In addition to leading their own project the post holder will have opportunities to contribute to multiple international genome initiatives.</p>

<p>Experience in programming, bioinformatics and comparative genome analysis is essential. Applicants should have a minimum of a degree and preferably a higher degree in a relevant subject.</p>

<p>The Royal Veterinary College has the largest range of veterinary, para-veterinary and animal science undergraduate and postgraduate courses of any veterinary school in the world and is one of the largest veterinary schools in Europe.</p>

<p>Prospective applicants are encouraged to contact Dr. Denis Larkin, Comparative Biomedical Sciences Department on +442071211906 or email: dlarkin@rvc.ac.uk</p>

<p>We offer a generous reward package.</p>

<p>For further information and to apply on-line please visit our website: www.rvc.ac.uk<br />Job reference CBS-0025-14A</p>

<p>Closing date: 4 July 2014<br />Interviews are likely to be held in July 2014</p>

<p>We promote equality of opportunity and diversity within the workplace and welcome applications from all sections of the community.</p>
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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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8198/scientist-positions-at-rajiv-gandhi-centre-for-biotechnology</guid>
  <pubDate>Thu, 06 Feb 2014 23:18:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist Positions at Rajiv Gandhi Centre for Biotechnology]]></title>
  <description><![CDATA[
<p>Rajiv Gandhi Centre for Biotechnology</p>

<p>An Autonomous National Institute under Government of India,<br />Ministry of Science &amp; Technology<br />Department of Biotechnology</p>

<p>No: RGCB/ Advt./2014/1   <br />January 24, 2014</p>

<p>Scientist Positions</p>

<p>Group Leader in Computational Biology/Bioinformatics<br />A highly motivated and innovative individual who will pursue basic research, solve biological problems with emphasis on computational and quantitative experimental methods and build active bridges to translational research. The scientist will also provide computational biology support to analyze complex data sets generated by RGCB scientists and collaborators.</p>

<p>Location: Thiruvananthapuram (Trivandrum)</p>

<p>The above positions will be at the E-II, F or equivalent levels. For senior applicants with an outstanding track record, an option of a contract career path for research excellence at Scientist G or H equivalent level can also be discussed. All positions will initially be for 5 years. Essential and desired qualifications as well as other relevant details for all the above positions are posted on the RGCB website (http://www.rgcb.res.in). The last date for receiving applications is March 14, 2014.   </p>

<p>Sd/-<br />Director</p>

<p>Rajiv Gandhi Centre for Biotechnology<br />Thycaud, P.O., Poojappura,<br />Thiruvananthapuram, Kerala, India-695 014<br />Ph.: 91-471-2529400 (30 Lines), 2347975, 2348104, 2348753, 2345899<br />Fax: 91-471-2348096, 2346333</p>

<p>More at http://rgcb.res.in/jobs.html</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37514/list-of-non-commercial-ngs-genotype-calling-software</guid>
	<pubDate>Thu, 09 Aug 2018 04:21:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37514/list-of-non-commercial-ngs-genotype-calling-software</link>
	<title><![CDATA[List of non-commercial NGS genotype-calling software]]></title>
	<description><![CDATA[<p><span>Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data.&nbsp;</span></p><p><span>A list of programs for genotype and SNP calling :</span></p><p><br />SOAP2&nbsp;http://soap.genomics.org.cn/index.html</p><p>Single-sample High-quality variant database (for example, dbSNP) Package for NGS data analysis, which includes a single individual genotype caller (SOAPsnp)</p><p>realSFS&nbsp;http://128.32.118.212/thorfinn/realSFS/</p><p>Single-sample Aligned reads Software for SNP and genotype calling using single individuals and allele frequencies. Site frequency spectrum (SFS) estimation</p><p>Samtools http://samtools.sourceforge.net/</p><p>Multi-sample Aligned reads Package for manipulation of NGS alignments, which includes a computation of genotype likelihoods (samtools) and SNP and genotype calling (bcftools)</p><p>GATK http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit Multi-sample Aligned reads Package for aligned NGS data analysis, which includes a SNP and genotype caller (Unifed Genotyper), SNP filtering (Variant Filtration) and SNP quality recalibration (Variant Recalibrator)</p><p>Beagle http://faculty.washington.edu/browning/beagle/beagle.html</p><p>Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation, phasing and association that includes a mode for genotype calling</p><p>IMPUTE2 http://mathgen.stats.ox.ac.uk/impute/impute_v2.html</p><p>Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation and phasing, including a mode for genotype calling. Requires fine-scale linkage map</p><p>QCall ftp://ftp.sanger.ac.uk/pub/rd/QCALL</p><p>Multi-sample LD &lsquo;Feasible&rsquo; genealogies at a dense set of loci, genotype likelihoods Software for SNP and genotype calling, including a method for generating candidate SNPs without LD information (NLDA) and a method for incorporating LD information (LDA). The &lsquo;feasible&rsquo; genealogies can be generated using Margarita (http://www.sanger.ac.uk/resources/software/margarita)</p><p>MaCH http://genome.sph.umich.edu/wiki/Thunder</p><p>Multi-sample LD Genotype likelihoods Software for SNP and genotype calling, including a method (GPT_Freq) for generating candidate SNPs without LD information and a method (thunder_glf_freq) for incorporating LD information</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8382/c-dac-launch-supercomputing-facility-param-bio-blaze</guid>
	<pubDate>Tue, 18 Feb 2014 11:55:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8382/c-dac-launch-supercomputing-facility-param-bio-blaze</link>
	<title><![CDATA[C-DAC launch supercomputing facility "Param Bio Blaze" !!!]]></title>
	<description><![CDATA[<p>The bioinformatics centre at Centre for Development of Advanced Computing (C-DAC) completed 10 years, this month. Established in 2004, the centre has been widely used by numerous researchers across the globe and has an ultimate aim of making personalised drugs depending on the composition of a human body.<br /><br />When biological data is processed using computer science, statistics, mathematics and engineering, it constitutes bioinformatics. The technological advancements are bringing new dimensions to the understanding of molecular basis of living organisms. There is immense data generated due to computing, but storage and analysis of this data is becoming a challenge, therefore there is an urgent need of supercomputers.</p><p>The&nbsp;C-DAC will launch Param Bio Blaze, a supercomputing facility, to address the challenges in bioinformatics on Tuesday at a three-day symposium, titled: 'Accelerating biology: Computing life'. The supercomputing facility will be inaugurated on Tuesday by Ramakrishna Ramaswamy, vice-chancellor, Central University of Hyderabad at the Yashada. The new C-DAC's facility will have a capacity of 10 teraflop and will be able to analyse human cells and its functions.</p><p><img src="http://www.datacenterjournal.com/wp-content/uploads/2012/06/supercomputer.jpg" alt="image" width="1024" height="632" style="border: 0px; border: 0px;"></p><p><br />Param Bio Blaze will help have a larger storage space and better computing facility for the bioinformatics sector. The facility will help capture the movement of molecules and also interaction between two molecules and the effects.<br /><br />Applications of Param BioBlaze<br /><br />- Collaboration with National Centre for Cell Science for research on Malaria and understanding how the disease spreads<br /><br />- Collaborative work with Tata Memorial hospital on breast cancer and find out the difference between normal tissues and tissues from breast cancer patients<br /><br />- Designing anti-cancer molecules, a collaborative research with the University of Pune</p><p>Reference:</p><p>Times of India</p><p>Image:datacenterjournal.com</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8330/atlas-of-ancient-inter-ethnic-group</guid>
	<pubDate>Fri, 14 Feb 2014 13:16:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8330/atlas-of-ancient-inter-ethnic-group</link>
	<title><![CDATA[Atlas of ancient inter-ethnic group !!!]]></title>
	<description><![CDATA[<p>Now a dayz, almost 3% of the world's population lived outside their country of origin. These migration is increasingly being perceived as a force that can contribute to development, and an integral aspect of the global development process.&nbsp; While migrants make important contributions to the economic prosperity of their host countries, the flow of financial, technological, social and human capital back to their countries of origin also is having a significant impact on poverty reduction and economic development.</p><p>However, the ancient invasions and migrations to slavery and trade, history is embroidered with events that led to interactions between previously separate populations. Early humans migrated due to many factors such as changing climate and landscape and inadequate food supply. Historical migration of human populations begins with the movement of Homo erectus out of Africa across Eurasia about a million years ago. Homo sapiens appear to have occupied all of Africa about 150,000 years ago, moved out of Africa 70,000 years ago, and had spread across Australia, Asia and Europe by 40,000 years BC. Indo-Aryan migration from the Indus Valley to the plain of the River Ganges in Northern India is presumed to have taken place in the Middle to Late Bronze Age, contemporary to the Late Harappan phase in India (ca. 1700 to 1300 BC). From 180 BC, a series of invasions from Central Asia followed, including those led by the Indo-Greeks, Indo-Scythians, Indo-Parthians and Kushans in the northwestern Indian subcontinent.</p><p><img src="http://upload.wikimedia.org/wikipedia/commons/3/37/Map-of-human-migrations.jpg" alt="image" style="border: 0px; border: 0px;"></p><p>Using the recent advance technologies researchers have created a historical atlas of instances of such mixing. They use a sophisticated statistical method for making inferences about human history and&nbsp;infer populations interbredings ( happen over the past 4,000 years) with an ease.<br /><br />The study published the findings and presented with an interactive map. http://admixturemap.paintmychromosomes.com/</p><p>These sort of genomic study have some limilation. It is hard to precisely define sources of mixing when it occurred between genetically similar groups, and scenarios involving multiple waves of mixing over time or between multiple groups can be difficult to tease apart. But it is believed that larger sample sizes will improve resolution. These high resolution will provide a deeper understanding of human history.</p><p>Reference:</p><p>http://www.sciencemag.org/content/early/2014/01/28/science.1245938</p><p>http://www.ncbi.nlm.nih.gov/pubmed/21390129?dopt=Abstract&amp;holding=npg</p><p>http://www.csulb.edu/~kmacd/paper-ethnicity.html</p><p>Image: Wikipedia</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38829/nquire-a-statistical-framework-for-ploidy-estimation-using-ngs-short-read-data</guid>
	<pubDate>Thu, 31 Jan 2019 05:12:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38829/nquire-a-statistical-framework-for-ploidy-estimation-using-ngs-short-read-data</link>
	<title><![CDATA[nQuire: A statistical framework for ploidy estimation using NGS short-read data]]></title>
	<description><![CDATA[<p>nQuire implements a set of commands to estimate ploidy level of individuals from species, where recent polyploidization occurred and intraspecific ploidy variation is observed. Specifically, nQuire uses next-generation sequencing data to distinguish between diploids, triploids and tetraploids, on the basis of frequency distributions at variant sites where only two bases are segregating.</p>
<p>For more background see also the publication at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2128-z">BMC Bioinformatics</a>.</p>
<p>https://github.com/clwgg/nQuire</p><p>Address of the bookmark: <a href="https://github.com/clwgg/nQuire" rel="nofollow">https://github.com/clwgg/nQuire</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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