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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32481?offset=1140</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</guid>
	<pubDate>Tue, 30 Oct 2018 10:49:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</link>
	<title><![CDATA[Synima: a Synteny imaging tool for annotated genome assemblies]]></title>
	<description><![CDATA[<p><span>Synima written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><a href="https://github.com/rhysf/Synima" target="_blank">https://github.com/rhysf/Synima</a><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</guid>
	<pubDate>Wed, 14 Nov 2018 04:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</link>
	<title><![CDATA[ANItools web: a web tool for fast genome comparison within multiple bacterial strains]]></title>
	<description><![CDATA[<p><span>ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.</span></p>
<p><span>https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454</span></p><p>Address of the bookmark: <a href="http://ani.mypathogen.cn/" rel="nofollow">http://ani.mypathogen.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14050/assistant-professor-in-bioinformatics-at-indian-institute-of-technology-delhi</guid>
  <pubDate>Fri, 15 Aug 2014 06:16:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor 	in Bioinformatics at Indian Institute of Technology Delhi]]></title>
  <description><![CDATA[
<p>Indian Institute of Technology Delhi Hauz Khas ,New Delhi – 110016</p>

<p>ROLLING ADVERTISEMENT NO. 01/2014(E-1)<br />ADVERTISEMENT FOR THE POSITIONS OF ASSISTANT PROFESSOR CANDIDATES CAN APPLY ANY TIME DURING THE YEAR.</p>

<p>IIT Delhi invites applications from qualified Indian Nationals, Persons of Indian Origin (PIOs) and Overseas Citizens of India (OCIs) for the following positions in the various Departments/Centres/Schools (in the fields<br />mentioned alongwith them):<br />Post Pay Band Assistant Professor and Assistant Professor (on Contract) Rs.15600-39100 (PB-3) (Minimum pay of Rs.30000/-)+ AGP Rs.8000/-</p>

<p>The following norms will be followed for fixing the basic pay + AGP for Assistant Professors appointed on<br />contract with Ph.D but experience of 3 years or less:-<br />Type Qualification &amp; Experience on the date of joining<br />Assistant Professor (Contract) PB3 (Rs. 15,600-39,100).</p>

<p>MINIMUM QUALIFICATIONS AND EXPERIENCE:<br />Ph.D. with First class at the preceding degree or equivalent in the appropriate branch with very good academic record throughout. A minimum of three years industrial/research/teaching experience, excluding however, the experience gained while Pursuing Ph. D. The candidates should preferably be below<br />35 years of age for male and 38 years for female ( to be relaxed by 5 years in case of persons with physical disability, SC/ST and 3 years in case of OBC-NCL).</p>

<p>Qualified persons include:<br />(a) Indian Nationals,<br />(b) Foreign Nationals who are “Persons of Indian Origin” (PIO) or Overseas<br />Citizens of India (OCI), in whose case, if selected, permission will be sought from Govt. of India<br />before he/she can join IIT Delhi, or<br />(c) Other Foreign Nationals, in whose case, if selected, appointment will be on a contract basis for up to 5 (five) years subject to permission from the Govt. of India before he/she can join IIT Delhi.<br />(d) Institute specifically encourages applicants from SC/ST/OBC category as well as persons<br />with disability to apply for these positions. </p>

<p>AMAR NATH &amp; SHASHI KHOSLA SCHOOL OF INFORMATION TECHNOLOGY:<br />Computational Neuroscience, Medical Applications of Information Technologies, Computational &amp; Systems Biology, Machine to Machine (M2M) Technologies, Embedded Systems &amp; Sensors, Computer Security.<br />KUSUMA SCHOOL OF BIOLOGICAL SCIENCES:<br />In-silico Biology Applications, Systems Biology, Infection Biology, Neurodegeneration. </p>

<p>More at http://www.iitd.ac.in/sites/default/files/jobs/faculty/spl-areas-rolling-advt.pdf</p>

<p>http://www.iitd.ac.in/content/faculty-positions</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14272/lecturersenior-lecturer-level-bc-in-bioinformatics</guid>
  <pubDate>Fri, 22 Aug 2014 12:45:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Lecturer/Senior Lecturer (Level B/C) in Bioinformatics]]></title>
  <description><![CDATA[
<p>Lecturer/Senior Lecturer (Level B/C) in Synthetic Biology, Research Fellow (Level B) in Synthetic Biology &amp; Lecturer/Senior Lecturer (Level B/C) in Bioinformatics</p>

<p>Apply now Job no: 494553<br />Work type: Continuing full time<br />Vacancy type: External Vacancy, Internal Vacancy<br />Categories: Academic - Teaching and Research</p>

<p>The Faculty of Science is launching a new and innovative branch of biological science at Macquarie University – Synthetic Biology. Synthetic biology combines engineering principles with molecular biological approaches to design and construct biological devices and systems. Recent highlights in this field include the design and synthesis of a functional bacterial genome and a yeast chromosome, and generation of synthetic bacterial cells. The rational synthesis of "designer" organisms yield important insights into how organisms work and has the potential to revolutionise biotechnological applications in areas such as bioenergy and biomanufacturing.</p>

<p>Find more at http://jobs.mq.edu.au/cw/en/job/494553/lecturersenior-lecturer-level-bc-in-synthetic-biology-research-fellow-level-b-in-synthetic-biology-lecturersenior-lecturer-level-bc-in-bioinformatics</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</guid>
	<pubDate>Fri, 21 Dec 2018 22:06:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</link>
	<title><![CDATA[Versatile genome assembly evaluation with QUAST-LG]]></title>
	<description><![CDATA[<p>QUAST-LG is an extension of&nbsp;<a href="http://cab.spbu.ru/software/quast/">QUAST</a>&nbsp;intended for evaluating large-scale genome assemblies (up to mammalian-size).</p>
<p>QUAST-LG&nbsp;is included in the QUAST&nbsp; package starting from version 5.0.0 (<a href="https://sourceforge.net/projects/quast/files/latest/download?source=files">download the latest release</a>). Run QUAST as usual and do not forget to add&nbsp;<span>‐‐large</span>&nbsp;option to your command!</p>
<p>A short list of the new features (see&nbsp;<a href="http://cab.spbu.ru/files/quast/latest-docs/CHANGES.txt">CHANGES</a>&nbsp;for all):</p>
<ul>
<li>Significant speedup achieved by both&nbsp;use of new fast aligner (<a href="https://github.com/lh3/minimap2">minimap2</a>) and the refactoring of alignment analyzing&nbsp;modules</li>
<li>New k-mer-based completeness and correctness metrics</li>
<li>BUSCO added for enhanced reference-free analysis</li>
<li>The concept of upper bound&nbsp;assembly (theoretical limits on the assembly&nbsp;completeness and&nbsp;contiguity for a given genome and set of reads)</li>
</ul><p>Address of the bookmark: <a href="http://cab.spbu.ru/software/quast-lg/" rel="nofollow">http://cab.spbu.ru/software/quast-lg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14758/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Mon, 01 Sep 2014 17:16:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38670/ltr-finder-an-efficient-program-for-finding-full-length-ltr-retrotranspsons-in-genome-sequences</guid>
	<pubDate>Sun, 13 Jan 2019 07:05:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38670/ltr-finder-an-efficient-program-for-finding-full-length-ltr-retrotranspsons-in-genome-sequences</link>
	<title><![CDATA[LTR_Finder: an efficient program for finding full-length LTR retrotranspsons in genome sequences.]]></title>
	<description><![CDATA[<p>LTR_Finder is an efficient program for finding full-length LTR retrotranspsons in genome sequences.</p>
<p>The Program first constructs all exact match pairs by a suffix-array based algorithm and extends them to long highly similar pairs. Then Smith-Waterman algorithm is used to adjust the ends of LTR pair candidates to get alignment boundaries. These boundaries are subject to re-adjustment using supporting information of TG..CA box and TSRs and reliable LTRs are selected. Next, LTR_FINDER tries to identify PBS, PPT and RT inside LTR pairs by build-in aligning and counting modules. RT identification includes a dynamic programming to process frame shift. For other protein domains, LTR_FINDER calls ps_scan (from PROSITE,&nbsp;<a href="http://www.expasy.org/prosite/">http://www.expasy.org/prosite/</a>) to locate cores of important enzymes if they occur.</p><p>Address of the bookmark: <a href="https://github.com/xzhub/LTR_Finder" rel="nofollow">https://github.com/xzhub/LTR_Finder</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14905/internship-in-computational-biology</guid>
  <pubDate>Thu, 04 Sep 2014 04:19:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship in Computational Biology]]></title>
  <description><![CDATA[
<p>We are looking for a motivated and autonomous intern to study gene expression in hybrid organisms. The student will work on natural hybrids of two or three different species of fungal endosymbionts of grasses. The pupose of this project is to build software allowing us to identify the genomic origin of expressed genes. To do that, the intern will have to analyze expression data (from RNA-seq) to find SNPs on the sequenced mRNAs allowing to identify from which of the parental genome the expressed gene come from. The data will have to be saved in a database using the standard BioSQL schema.</p>

<p>This job will allow the intern to become more familiar with new biological and bioinformatics tools like next generation sequencing, RNA-Seq data analysis and comparative genomics.</p>

<p>To apply for this position, send the following documents (in PDF format) to Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz):</p>

<p>1. A short cover letter.<br />2. A curriculum vitae, with transcript details.<br />3. The names and contact details of two referees willing to provide a confidential letter of recommendation upon request.</p>

<p>Informal enquiries are welcome. Formal applications are due by Sunday 2nd December 2012.<br />Requirements: </p>

<p>This position requires a good understanding of genetic problems, a good command of at least one scripting language (Perl, Python...), a basic knowledge of MySQL or any relational database management system. Knowledge in biological programming libraries (BioPython, BioPerl, BioRuby...), Java, C++ or any compiled language is an asset but not required. Undergraduate or Master degree is required.<br />Contact Information: </p>

<p>Dr. Pierre-Yves Dupont<br />Institute of Molecular BioSciences<br />Massey University<br />Private Bag 11 222<br />Palmerston North 4442<br />NEW ZEALAND</p>

<p>http://massey.genomicus.com/<br />p.y.dupont@massey.ac.nz</p>

<p>Information about the Institute of Molecular BioSciences (http://imbs.massey.ac.nz/) and the Computational Biology Research Group (http://massey.genomicus.com/) is available online. For more information about the position, you can contact Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz).</p>
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