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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34916?offset=820</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</guid>
	<pubDate>Fri, 27 Dec 2013 19:58:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</link>
	<title><![CDATA[Oldest Hominin DNA Sequenced]]></title>
	<description><![CDATA[<p>Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.<br /><br />From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.<br /><br /></p><p>Reference</p><p>http://www.sciencedaily.com/releases/2013/12/131204132018.htm</p>]]></description>
	<dc:creator>Surajeet</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <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>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44213/bioinformatics-tools-to-explore-ssrs-in-genomes</guid>
	<pubDate>Tue, 07 Mar 2023 13:06:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44213/bioinformatics-tools-to-explore-ssrs-in-genomes</link>
	<title><![CDATA[Bioinformatics tools to explore SSRs in genomes !]]></title>
	<description><![CDATA[<p>There are several bioinformatics tools that can be used to explore Simple Sequence Repeats (SSRs), which are also known as microsatellites. Here are a few examples:</p><ol>
<li>
<p>MISA: MISA (MIcroSAtellite) is a web-based tool that can identify SSRs in DNA sequences. It can be used to analyze nucleotide sequences from various organisms and can identify perfect, compound, and imperfect SSRs.</p>
</li>
<li>
<p>SSR Locator: SSR Locator is a web-based tool that identifies SSRs in both DNA and RNA sequences. It can identify perfect, compound, and imperfect SSRs, and can also filter out low complexity regions.</p>
</li>
<li>
<p>SciRoKo: SciRoKo is a software tool that can identify SSRs in DNA sequences. It can be used to analyze genomic and transcriptomic sequences from various organisms and can identify perfect, compound, and imperfect SSRs.</p>
</li>
<li>
<p>Primer3: Primer3 is a web-based tool that designs PCR primers for SSRs. It can design primers for perfect and imperfect SSRs, and can be used to design primers for SSRs in various organisms.</p>
</li>
<li>
<p>QDD: QDD (Quick Detection of Duplication) is a software tool that can identify SSRs in DNA sequences and can also identify duplicate loci. It can be used to analyze genomic and transcriptomic sequences from various organisms.</p>
</li>
</ol><p>These are just a few examples of the many bioinformatics tools available for exploring SSRs. Depending on your specific needs and research questions, you may find that other tools are more appropriate for your analysis.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
  <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>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</guid>
	<pubDate>Tue, 30 Jan 2018 06:01:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</link>
	<title><![CDATA[Comprehensive list of visualization tools for biological pathways]]></title>
	<description><![CDATA[<p>The study of biological pathways is a key to understand the different processes inside a cell: proteins exert their function not in isolation but in a tightly controlled network of interactions and reactions. Activation of a pathway typically leads to a change of state in the cell. Pathways come in different flavors, depending on their functions in the cell &ndash; the three main types are metabolic pathways, gene regulatory pathways, and signaling pathways. These biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization.</p><p><img src="https://photos-1.dropbox.com/t/2/AABemz29qAuSTqSzr5mEsQE7JIMxZlU1CBy0E5n0yUVYbA/12/85115969/png/32x32/1/_/1/2/pathway.png/EOfXoUIYrJ8CIAcoBw/01qsT2eykyPvSH-rNpy3cqioDzZPc4i-xULG3BEZvCk?preserve_transparency=1&amp;size=1280x960&amp;size_mode=3" width="800" height="533" alt="image" style="border: 0px;"></p><p>Following are the comprehensive list of visualization tools for biological pathways:</p><p>BiNA</p><p>Drawings of metabolic networks supporting hiding of cofactors and drawing of chemical structures</p><p>http://bina.unipax.info/</p><p>BioTapestry</p><p>Interactive tool for building, visualizing and sharing gene regulatory network models over the web</p><p>http://www.biotapestry.org/</p><p>Caleydo</p><p>Visual analysis framework targeted at biomolecular data. Visualization of interdependencies between multiple datasets</p><p>http://www.caleydo.org/</p><p>CellDesigner</p><p>A modeling tool for biochemical networks</p><p>http://www.celldesigner.org/</p><p>Edinburgh Pathway Editor</p><p>Edit and draw pathway diagrams</p><p>http://epe.sourceforge.net/SourceForge/EPE.html</p><p>GenMAPP</p><p>Visualization of gene expression and other genomic data on maps representing biological pathways and groupings of genes</p><p>http://www.genmapp.org/</p><p>Ingenuity IPA</p><p>Data integration platform and manually annotated pathways</p><p>http://tinyurl.com/IngenuityPath</p><p>JDesigner</p><p>Graphical modeling environment for biochemical reaction networks</p><p>http://jdesigner.sourceforge.net/Site/JDesigner.html</p><p>KaPPA View</p><p>Plant pathways</p><p>http://kpv.kazusa.or.jp/</p><p>KEGG Atlas</p><p>Interactive Kyoto Encyclopedia of Genes and Genomes pathways</p><p>http://www.genome.jp/kegg/</p><p>Omix&nbsp;</p><p>Visualizing multi-omics data in metabolic networks</p><p>https://www.omix-visualization.com</p><p>PathVisio&nbsp;</p><p>Biological pathway analysis software that allows drawing, editing and analysis of biological pathways</p><p>http://www.pathvisio.org/</p><p>VitaPad&nbsp;</p><p>Application to visualize biological pathways and map experimental data to them</p><p>http://tinyurl.com/vitapad/</p><p>Web tools for pathways</p><p>ArrayXPath&nbsp;</p><p>Mapping and visualizing microarray gene-expression data and integrated biological pathway resources using SVG</p><p>http://tinyurl.com/ArrayXPath/</p><p>GEPAT&nbsp;</p><p>Integrated analysis of transcriptome data in genomic, proteomic and metabolic contexts</p><p>http://gepat.sourceforge.net/</p><p>iPath&nbsp;</p><p>Web-based tool for the visualization, analysis and customization of pathway maps</p><p>http://pathways.embl.de/</p><p>Kegg-Based Viewer&nbsp;</p><p>KEGG-based pathway visualization tool for complex high-throughput data</p><p>http://www.g-language.org/data/marray/</p><p>MapMan&nbsp;</p><p>User-driven tool that displays large datasets onto diagrams of metabolic pathways or other processes</p><p>http://mapman.gabipd.org/web/guest/mapman</p><p>MetPA&nbsp;</p><p>Analysis and visualization of metabolomic data within the biological context of metabolic pathways</p><p>http://metpa.metabolomics.ca</p><p>Omics Viewer&nbsp;</p><p>Data mapping on BioCyc pathways (collection of 5500 pathway/genome databases)</p><p>http://www.biocyc.org/</p><p>Pathway Explorer</p><p>Interactive Java drawing tool for the construction of biological pathway diagrams in a visual way and the annotation of the components and interactions between them</p><p>http://genome.tugraz.at/pathwayexplorer/pathwayexplorer_description.shtml</p><p>Pathway projector&nbsp;</p><p>Zoomable pathway browser using KEGG atlas and Google Maps API</p><p>http://www.g-language.org/PathwayProjector/</p><p>PATIKA&nbsp;</p><p>Integrated environment composed of a central database and a visual editor, built around an extensive ontology and an integration framework</p><p>http://www.cs.bilkent.edu.tr/~patikaweb/</p><p>Reactome SkyPainter&nbsp;</p><p>Visualization of over-represented pathways and reactions from gene lists</p><p>http://www.reactome.org/skypainter-2</p><p>WikiPathways</p><p>Wiki-based, open, public platform dedicated to the curation of biological pathways by and for the scientific community</p><p>http://www.wikipathways.org/</p>]]></description>
	<dc:creator>Neel</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>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</guid>
	<pubDate>Tue, 08 May 2018 04:27:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</link>
	<title><![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]></title>
	<description><![CDATA[<p><strong>HISAT2</strong><span>&nbsp;is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs&nbsp;</span><a href="http://dl.acm.org/citation.cfm?id=2674828">[Sir&eacute;n et al. 2014]</a><span>, we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).&nbsp;</span></p>
<p><span>more at&nbsp;https://ccb.jhu.edu/software/hisat2/index.shtml</span></p><p>Address of the bookmark: <a href="https://github.com/infphilo/hisat2" rel="nofollow">https://github.com/infphilo/hisat2</a></p>]]></description>
	<dc:creator>Rahul Nayak</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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