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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28199?offset=1180</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4183/320000-viruses-in-mammals-yet-to-sequenced-in-future</guid>
	<pubDate>Tue, 03 Sep 2013 08:35:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4183/320000-viruses-in-mammals-yet-to-sequenced-in-future</link>
	<title><![CDATA[320000 viruses in mammals yet to sequenced in future!!!]]></title>
	<description><![CDATA[<p>With current biological technique improvements, finally it is now possible to look at millions of unknown viruses at genomic level and understand the mechanism. According to available data, close to 70 per cent of emerging viral diseases such as HIV/AIDS, West Nile, Ebola, SARS, and influenza, are zoonoses - infections of animals that cross into humans.</p><p>To address the challenges of describing and estimating virodiversity, a team of investigators from Center for Infection and Immunity (CII) and EcoHealth Alliance began in jungles of Bangladesh - home to the flying fox.</p><p>Reference:</p><p><a href="http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms">http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms</a></p><p><a href="http://www.bbc.co.uk/news/science-environment-23932400">http://www.bbc.co.uk/news/science-environment-23932400</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12988/guest-lecturer-molecular-biology-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 13:34:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Lecturer - Molecular Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>Adv. No. F.TU/ACA/GT-APP/01/14 Date: 07.07.2014</p>

<p>Faculty of Science</p>

<p>Essential Qualifications:</p>

<p>(i) Good academic record having at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master’s Degree level in a relevant subject, from an Indian University, or an equivalent degree from an accredited foreign University.</p>

<p>(II) Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.</p>

<p>(III) Notwithstanding anything contained in sub-clauses (i) and (ii) of clause 4.4.1 of UGC regulations 2010, 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 engagement of guest Teacher.</p>

<p>(IV) NET/ SLET/ SET shall also not be required for such Master’s Degree Programmes in discipline for which NET/ SLET/ SET is not conducted.</p>

<p>Application form along with detailed instructions can be downloaded from Tripura University website: www.tripurauniv.in. The duly filled in application forms complete in all respects may be sent so as to reach the Office of the Deputy Registrar Academic Branch, Tripura University, Suryamaninagar - 799022, Tripura on or before 31st July, 2014. The Candidates who responded against advertisement No. TU.REG/N-Advt./02/10 dated 20.02.2014 need not apply again.</p>

<p>For more info visit: http://www.tripurauniv.in/images/universitymedia/EmploymentNotification/Guest%20Teacher%20Advt.%20website_09072014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/4574/tools-to-detect-synteny-blocks-regions-among-multiple-genomes</guid>
	<pubDate>Mon, 16 Sep 2013 17:12:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/4574/tools-to-detect-synteny-blocks-regions-among-multiple-genomes</link>
	<title><![CDATA[Tools to detect synteny blocks regions among multiple genomes]]></title>
	<description><![CDATA[<p>The synteny block (which etymologically means &ldquo;on the same ribbon&rdquo;) is a collection of contiguous genes located on the same chromosome. These block regions have mostly been preserved by genome rearrangements, and so synteny blocks from two related species (e.g., humans and mice) will be roughly similar but flipped around on the respective genomes. Ovcharenko et. al. define it as &lsquo;any conserved sequence blocks, regardless of whether it encompasses multiple genes, an area containing single genes, or areas devoid of known genes to be considers as synteny block as long as there is conservation at the sequence level. Today, however, biologists usually refer to synteny as the conservation of blocks of order within two sets of chromosomes that are being compared with each other. This concept can also be referred to as shared synteny. The NHBLI/NCBI Glossary define synteny as &ldquo;Two genes which occur on the same chromosome are syntenic; however, syntenic genes may or may not be "linked."</p><p>Now a day, geneticists have developed a language of their own. They are pouring lots of money and energy to read the entire genomic text and understand the gods own code ATGC. It is somewhat fascinating, not only for geneticist but also for non-biologist to know that there are several conserved blocks in genome which remain conserved over hundreds of millions of years. There have been several researches on conserved blocks and non-conserved regions to understand the mechanism and importance of all these regions (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). The finding indicates conservation and rearrangements of certain evolutionary important genes play an important role in evolution/adaptive changes (http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html https://academic.oup.com/gbe/article/8/8/2442/2198198/Novel-Insights-into-Chromosome-Evolution-in-Birds , http://science.sciencemag.org/content/346/6215/1311).</p><p>But the puzzle remains open, how to correctly define the synteny (presence of two or more genes on the same chromosome) and conserved synteny (presence of two or more genes on chromosome of each of the two species) on several genomes.</p><p><img src="http://bioinformaticsonline.com/mod/photo/syntenyImg.jpg" alt="image" width="720" height="179" style="border: 0px; border: 0px;"></p><p>Figure: Image generated with Evolution Highway (EH) tool http://eh-demo.ncsa.illinois.edu/&nbsp;</p><p>Keeping the new approach to define conserved synteny in mind there have been various algorithms developed to identify the conserved homologous synteny blocks (HSB) amongst species. Some of them which were commonly used for synteny detections are:</p><p>SyntenyTracker ( http://www-app.igb.uiuc.edu/labs/lewin/donthu/Synteny_assign/html/),</p><p>SyntenyTracker was shown to be an efficient and accurate automated tool for defining HSBs using datasets that may contain minor errors resulting from limitations in map construction methodologies.</p><p>CoGe (http://genomevolution.org/CoGe/SynFind.pl )</p><p>Satsuma (http://evomics.org/learning/genomics/satsuma/)</p><p>Cinteny (http://cinteny.cchmc.org/) ,</p><p>Cinteny server can be used for finding regions syntenic across multiple genomes and measuring the extent of genome rearrangement using reversal distance as a measure.</p><p>OrthoCluster (http://krono.act.uji.es/noticias/orthocluster-a-new-tool-for-mining-syntenic-blocks)</p><p>A new tool for mining syntenic blocks in comparative genomics</p><p>SynMap (http://genomevolution.org/wiki/index.php/SynMap),</p><p>SyMAP (http://www.symapdb.org/)</p><p>SyMAP (Synteny Mapping and Analysis Program) v4.0 is an automated system for identifying and displaying genome synteny alignments. The genomes may be represented by sequenced chromosomes (pseudomolecules), by draft sequence contigs, or by FPC physical maps (with BAC-end or marker sequence).</p><p>http://genomevolution.org/CoGe/SynMap.pl</p><p>RegionMiner (http://www.genomatix.de/online_help/help_regionminer/orthologous.html)</p><p>SyntenyMiner is being developed as an application to visualize and interrogate comparisons among multiple complete genome sequences. http://syntenyminer.sourceforge.net/</p><p>AutoGRAPH ( http://autograph.genouest.org/),</p><p>AutoGRAPH is an integrated web server for multi-species comparative genomic analysis. It is designed for constructing and visualizing synteny maps between two or three species, determination and display of macrosynteny and microsynteny relationships among species, and for highlighting evolutionary breakpoints.</p><p>SynChro(http://www.lgm.upmc.fr/CHROnicle/SynChro.html)</p><p>SynChro is a tool designed to define conserved synteny blocks. It reconstructs synteny blocks between pairwise comparison of multiple genomes. The reconstructed synteny blocks may overlap each other, be included in one another or duplicated due to micro-rearrangements.</p><p>SyntenyView ( http://www.cbs.dtu.dk/dtucourse/cookbooks/nikob/exercises/gf1_output_5.html),</p><p>Ensembl 'SyntenyView' shows conservation of large-scale gene order between species pairs. A brief summary of the calculation method appears at the bottom of this help page.&nbsp; The left of a 'SyntenyView' page displays a diagram of chromosomes with blocks of conserved synteny. The right of a page shows homology matches between individual genes within syntenic blocks.</p><p>SynBrowse ( http://www.synbrowse.org/),</p><p>SynBrowse (Synteny Browser) is a generic sequence comparison tool for visualizing genome alignments both within and between species. It is intended to help scientists study and analyze synteny, homologous genes and other conserved elements between sequences. This software is useful in studying genome duplication and evolution. It can also aid in identifying uncharacterized genes, putative regulatory elements and novel structural features of study species by comparing to a well annotated reference sequence, thus enabling genome curators to refine and edit annotations of species that have incomplete genome annotations.</p><p>Sibelia (http://arxiv.org/abs/1307.7941).</p><p>A comparative genomic tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the evolutionary and genome rearrangement studies for multiple strains of microorganisms.</p><p>GSV (http://cas-bioinfo.cas.unt.edu/gsv/homepage.php)</p><p>Genome Synteny Viewer allows users to upload files which contain synteny regions between two or more genomes and interactively visualize the synteny between them. GSV also allows users to upload annotation files to visualize annotated regions in addition to synteny regions.</p><p>MicroSyn (http://www.lgm.upmc.fr/CHROnicle/SynChro.html)</p><p>MicroSyn software as a means of detecting microsynteny in adjacent genomic regions surrounding genes in gene families. MicroSyn searches for conserved, flanking colinear homologous gene pairs between two genomic fragments to determine the relationship between two members in a gene family.</p><p>SynOrth (http://synorth.genereg.net/)</p><p>Synorth [s n &ocirc;rth], named in combination of "synteny" and "ortholog", is designed for the study of evolutionary changes of genomic regulatory blocks (GRBs) in vertebrate genomes, and especially the changes following the whole-genome duplication in teleost fish, by tracing the ortholog genes gain and loss in ancient synteny blocks.</p><p>SyDiG (http://www.ncbi.nlm.nih.gov/pubmed/21441096)</p><p>Uncovering Synteny in Distant Genomes.</p><p>MapSynteny&nbsp; (http://www.automatizacionysistemas.com/download.html)</p><p>MapSynteny is a macro in MS Excel&reg; able to create images to show the relationship between genetic maps and large sequences (scaffolds, chromosomes, BACs, etc.). Based on tab &ndash; delimited BLAST results and some formulas, a suitable image of syntenic relationships or physical mapping can be obtained. http://www.automatizacionysistemas.com/Poster_MapSynteny.pdf</p><p>One of the best synteny tutorial for beginer @&nbsp;http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022</p><p>Reference:</p><p><a href="http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022">http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022</a></p><p><a href="http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html">http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html</a></p><p><a href="http://en.wikipedia.org/wiki/Synteny">http://en.wikipedia.org/wiki/Synteny</a></p><p><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/8650/bioinformatician-duties-and-jobs</guid>
	<pubDate>Wed, 05 Mar 2014 14:32:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/8650/bioinformatician-duties-and-jobs</link>
	<title><![CDATA[Bioinformatician duties and jobs !!!]]></title>
	<description><![CDATA[<p><span><em>Needle</em> in a haystack</span> ... ohh yes this is what bioinformatician do. We handle and analyse, Terabytes and Petabytes of genomic data on daily basis.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/8650" length="37079" type="image/gif" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12936/assistant-professor-medical-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 05:00:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Medical Bioinformatics]]></title>
  <description><![CDATA[
<p>Advt. No : ME-I/A-IV/03/14</p>

<p>No.of Posts:01 (SC)</p>

<p>Pay Scale:</p>

<p>Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.</p>

<p>Qualifications:</p>

<p>Area of Specialization:-</p>

<p>Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology</p>

<p>1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.</p>

<p>2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/</p>

<p>Immunology/Structural Biology etc</p>

<p>Experience:</p>

<p>1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical</p>

<p>Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.</p>

<p>2. Minimum two publication with atleast one in international journal and atleast one as first author</p>

<p>Desirable:-</p>

<p>Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)</p>

<p>Send your applications to O/O, Deputy Registrar, Recruitment &amp; Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014</p>

<p>For more details,please visit website:http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26179/alignment-of-closely-related-whole-genomesscaffolds</guid>
	<pubDate>Fri, 29 Jan 2016 10:37:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26179/alignment-of-closely-related-whole-genomesscaffolds</link>
	<title><![CDATA[Alignment of closely related whole genomes/scaffolds]]></title>
	<description><![CDATA[<p>With the relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.This bookmaks have been created to report new tools for whole genome alignments.</p>
<p>Please report new whole genome alignment tools under comment sections.</p><p>Address of the bookmark: <a href="http://www.cs.utoronto.ca/~brudno/721.full.pdf" rel="nofollow">http://www.cs.utoronto.ca/~brudno/721.full.pdf</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</guid>
	<pubDate>Thu, 24 Jul 2014 02:51:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</link>
	<title><![CDATA[The 5 reasons to mistakes at bioinformatics work !!!]]></title>
	<description><![CDATA[<p>When you're just starting out with biological programming, it's easy to run into complex problems that make you wonder how anyone has ever managed to write a program. There are some problems that trip up nearly every bioinformatician--everything from getting started understanding the biological problems to dealing with program design. Some random mistakes are so prominent that even experienced biological programmers do it. The 8 years in bioinformatics and my few random observations, most of them are snarky. These reasons will always take longer than expected and compel you to postpone your project deadline.</p><p><strong>1.Stupid for biologist:</strong> Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.<br /><br /><strong>2.Puzzling why:</strong> Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.<br /><br /><strong>3.Running marathon:</strong> The most of the biological software&rsquo;s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( &hellip; <br /><br /><strong>4.Folders missing:</strong> The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery&hellip;<br /><br /><strong>5.Digging deeper:</strong> Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue &hellip;. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.<br /><br />The most common frustrating&nbsp; common line: Why do we do this again?</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/33973/list-of-genome-announcement-notes-and-reporting-journals</guid>
	<pubDate>Wed, 26 Jul 2017 08:01:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/33973/list-of-genome-announcement-notes-and-reporting-journals</link>
	<title><![CDATA[List of genome announcement, notes and reporting journals]]></title>
	<description><![CDATA[<p><span>Faced with an increasing number of articles describing DNA data and a need for more appropriate venues to present these data, some publishers and journals have responded by changing the structure and format of genome papers. Specifically, certain journals have started accepting very short manuscripts (500&ndash;1500 words) that present a new chromosome sequence, its GenBank accession number and little else. These pint-sized articles go by various names, such as genome reports, genome announcements, genome notes or genome letters</span><span>, but will be referred to here broadly as genome reports. Their short length and minimal number (or complete absence) of figures, tables and article subheadings are a significant departure from long-form genome papers, which typically span 8&ndash;10 journal pages, contain many supporting items and have formal introduction, methods, results and discussion sections.</span></p><p>Following are the list of journals publishing&nbsp;<span>pint-sized articles go by various names, such as genome reports, genome announcements, genome notes or genome letters</span><span>, but will be referred to here broadly as genome reports.</span></p><p>1. <strong>Genome Announcements</strong>, American Society for Microbiology, Genome announcement, Impact factor 1.3, &nbsp;A 500-word report stating that the genome of a particular organism (prokaryote, eukaryote or virus) has been sequenced and providing a citable record of the corresponding GenBank submission. Must include abstract but no text headings can be used except for &lsquo;Acknowledgments&rsquo; and &lsquo;References&rsquo;. Cannot include figures, tables or supplemental material to present data or analysis.</p><p>Link: https://mra.asm.org/</p><p>2. <strong>Genome Biology and Evolution</strong>, Oxford University Press, Genome report, Impact factor 4.2, Focused 1500-word papers (up to six tables or figures) that publish the main evolutionary message of new genome sequences as they become submitted to GenBank. May also contain specifically focused comparative analyses of previously published genomes that contain a substantial and novel insight of broadest evolutionary significance.</p><p>Link: https://academic.oup.com/gbe</p><p>3. <strong>Journal of Biotechnology</strong>, Elsevier, Genome announcement, Impact factor 2.9, A 500-word report announcing the availability of the completely annotated genome sequence of a biotechnologically relevant organism in the corresponding database (for eukaryotes, advanced draft genomes will also be considered). Articles can contain an Abstract, a brief report on the organism and its biotechnological relevance, a table summarizing the genome features, References and an Acknowledgement. Figures are generally not allowed.</p><p>Link: https://www.journals.elsevier.com/journal-of-biotechnology</p><p>4. <strong>Journal of Genomics</strong>, Ivyspring, Genome note, Impact factor N/A, A 1000-word report (10 reference limit; conclusions not permitted) describing novel data sets from high-throughput analysis of genotypes, phenotypes, gene expression, metabolomes, proteomes or genome assemblies.Standard metrics for data quality and the experimental design must be clearly reported.</p><p>Link: http://www.jgenomics.com/</p><p>5. <strong>Mem&oacute;rias do Instituto</strong>, Oswaldo Cruz Oswaldo Cruz Foundation, Genome announcement and highlight, Impact factor 1.6, Dedicated to publishing new genome information from eukaryote parasites, virus, bacteria and their respective vectors, as well as re-sequencing or comparative genome analyses. Should occupy no more than three printed pages including figures and/or tables.</p><p>Link: http://memorias.ioc.fiocruz.br/</p><p>6. <strong>Molecular Ecology Resources,</strong> Wiley, Genomic resources note, &nbsp;Impact factor 3.7, Short notes on newly assembled and annotated transcriptomes, genome fractions or whole genomes, and/or a library of SNP/SSR markers.Authors submit a short manuscript describing how the resource was developed and where the data can be accessed. Do not appear in journal as individual papers but are instead published as part of a summary article.</p><p>Link: https://onlinelibrary.wiley.com/journal/17550998</p><p>7. <strong>Standards in Genomic Science</strong>, BioMed Central (Springer), Short genome report, Impact factor 3.2,&nbsp;<span>Short (&sim;500-word) article on newly sequenced genome. Article format must follow guidelines and template (available from journal Web site) put forward by the SGS. Any manuscripts not using template or that are missing key figures, tables and/or references (as per the guidelines) will be returned to authors. Rationale of the content model is to provide information that is consistently and uniformly presented for rapid and easy consumption by both human and machine readers.&nbsp;</span></p><p><span>Link: https://standardsingenomics.biomedcentral.com/</span></p><p><span>8. <strong>3biotech</strong>, Springer,&nbsp;<span>Short genome report, Impact factor 1.3,&nbsp;</span><span>Short (&sim;500-word) article on newly sequenced genome. Article format must follow guidelines (available from journal Web site).&nbsp;<span>&nbsp;Genome of a particular organism (prokaryote, eukaryote or virus) has been sequenced and providing a citable record of the corresponding GenBank submission.</span></span></span></p><p><span><span><span>Link: https://link.springer.com/journal/13205</span></span></span></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>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</guid>
	<pubDate>Wed, 14 Feb 2018 02:49:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</link>
	<title><![CDATA[MeDuSa: a multi-draft based scaffolder]]></title>
	<description><![CDATA[<p><span>MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/combogenomics/medusa" rel="nofollow">https://github.com/combogenomics/medusa</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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