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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31156?offset=590</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4108/tijana-milenkovic-lab</guid>
  <pubDate>Fri, 30 Aug 2013 06:45:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Tijana Milenkovic Lab]]></title>
  <description><![CDATA[
<p>Complex networks and network mining: developing graph theoretic, mathematical, and computational algorithms for efficient extraction of function from topology of complex real-world networks, such as biological, social, and technological networks.</p>

<p>Computational and systems biology: studying the interplay between network topology and biological function, disease, and evolution in molecular (e.g., protein-protein interaction) networks.</p>

<p>Computational chemistry: protein folding; computational drug discovery and design.</p>

<p>Synthetic biology.</p>

<p>More at http://www.cse.nd.edu/~tmilenko/index.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</guid>
	<pubDate>Sat, 16 Dec 2017 17:37:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</link>
	<title><![CDATA[Tools for bacterial whole genome annotation]]></title>
	<description><![CDATA[<p><a href="http://rast.nmpdr.org/">RAST</a>&nbsp;&ndash;&nbsp;Web tool (upload contigs), uses the subsystems in the SEED database and&nbsp;provides detailed annotation and pathway analysis. Takes several hours per genome but I think this is the best way to get a high quality annotation (if you have only a few genomes to annotate).</p><p><a href="http://www.vicbioinformatics.com/software.prokka.shtml">Prokka</a>&nbsp;&ndash;&nbsp;Standalone command line tool, takes just a few minutes per genome.&nbsp;This is the best way to get good quality annotation in a flash, which is particularly useful if you have loads of genomes or need to annotate a pangenome or metagenome. Note however that the quality of functional information is not as good as RAST, and you&nbsp;will need several extra steps if you want to do&nbsp;functional profiling and pathway analysis of your genome(s)&hellip; which is in-built in RAST.</p><p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p><p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p><p><a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/">PGAP</a>: NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume.&nbsp; NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC453985">BEACON</a> (automated tool for Bacterial GEnome Annotation ComparisON), a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at:&nbsp;<a href="http://www.cbrc.kaust.edu.sa/BEACON/" target="pmc_ext">http://www.cbrc.kaust.edu.sa/BEACON/</a>.</p><p><a href="http://www.kegg.jp/blastkoala/">BlastKOLA</a>: Assigns K numbers to the user's sequence data by BLAST searches, respectively, against a nonredundant set of KEGG GENES. KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to this server and can be executed in an interactive mode. BlastKOALA is suitable for annotating fully sequenced genomes.</p><p><a href="http://www.sanger.ac.uk/science/tools/pagit">PAGIT</a>: Provides a toolkit for improving the quality of genome assemblies created via an assembly software. PAGIT compiled four tools: (i) ABACAS which classifies and orientates contigs and estimates the sizes of gaps between them; (ii) IMAGE uses paired-end reads to extend contigs and close gaps within the scaffolds; (iii) ICORN for identifying and correcting small errors in consensus sequences and; (iv) RATT for help annotation. The software was mainly created to analyze parasite genomes of up to about 300 Mb.</p><p><a href="http://www.yandell-lab.org/software/maker.html">MAKER: </a>A portable and easily configurable genome annotation pipeline. MAKER allows smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. It identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER's inputs are minimal and its ouputs can be directly loaded into a Generic Model Organism Database (GMOD). They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER is available for download and can be tested online via the MAKER Web Annotation Service (MWAS).</p><p><a href="https://www.sciencedirect.com/science/article/pii/S0167701215001207">MyPro</a> is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4234/ncbi-psi-blast-tutorial</guid>
	<pubDate>Wed, 04 Sep 2013 11:46:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4234/ncbi-psi-blast-tutorial</link>
	<title><![CDATA[NCBI PSI-BLAST Tutorial]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/T3kHEieyylk" frameborder="0" allowfullscreen></iframe>http:--www.biotechnology.jhu.edu-
Tutorial for PSI-BLAST, an extension of BLAST that uses matrix algebra. BLAST is a cornerstone bioinformatics tool at NCBI. BLAST is the
Basic Local Alignment Search tool and will protein and DNA sequences that
are related to a sequence that the user provides.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</guid>
	<pubDate>Fri, 02 Feb 2018 13:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</link>
	<title><![CDATA[List of visualization tools for genome alignments]]></title>
	<description><![CDATA[<p><span>Genome</span><span>&nbsp;browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and&nbsp;interpretation of results:</span></p><p>ABySS Explorer</p><p>Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata</p><p>http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer</p><p>BamView</p><p>Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation</p><p>http://www.sanger.ac.uk/resources/software/artemis/</p><p>DNannotator&nbsp;</p><p>Annotation web toolkit for regional genomic sequences</p><p>http://bioapp.psych.uic.edu/DNannotator.htm</p><p>JVM&nbsp;</p><p>Java Visual Mapping tool for NGS reads</p><p>http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501</p><p>LookSeq&nbsp;</p><p>Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation</p><p>http://lookseq.sourceforge.net</p><p>MagicViewer&nbsp;</p><p>Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome</p><p>http://bioinformatics.zj.cn/magicviewer/</p><p>MapView&nbsp;</p><p>Alignments of huge-scale single-end and pair-end short reads</p><p>http://omictools.com/mapview-s1367.html</p><p>MultiPipMaker</p><p>Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a &lsquo;percent identity plot&rsquo; (pip)</p><p>http://pipmaker.bx.psu.edu/pipmaker/</p><p>PileLineGUI&nbsp;</p><p>Handling genome position files in NGS studies</p><p>http://sing.ei.uvigo.es/pileline/pilelinegui.html</p><p>SAMtools tview&nbsp;</p><p>Simple and fast text alignment viewer; NGS compatible</p><p>http://www.htslib.org/</p><p>SEWAL</p><p>Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run</p><p>http://www.sourceforge.net/projects/sewal</p><p>STAR&nbsp;</p><p>A web-based integrated solution to management and visualization of sequencing data</p><p>http://wanglab.ucsd.edu/star/browser</p><p>SVA&nbsp;</p><p>Software for annotating and visualizing sequenced human genomes</p><p>http://www.svaproject.org</p><p>Viewer (IGV)&nbsp;</p><p>Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution</p><p>https://www.broadinstitute.org/igv/</p><p>ZOOM Lite&nbsp;</p><p>NGS data mapping and visualization software</p><p>http://bioinfor.com/zoom/lite/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4352/jrf-bharathidasan-university</guid>
  <pubDate>Sat, 07 Sep 2013 14:20:03 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF @ BHARATHIDASAN UNIVERSITY]]></title>
  <description><![CDATA[
<p>Department of Bioinformatics<br />School of Life Sciences<br />BHARATHIDASAN UNIVERSITY,<br />TIRUCHIRAPPALLI-620 024</p>

<p>WALK-IN-INTERVIEW FOR JUNIOR RESEARCH FELLOWSHIP</p>

<p>Project title: Structural and Functional Evolution of Bacterial ADP-ribosylation Superfamily–A Special Emphasis for Engineering Immunotoxins from Binary toxin A Funding Agency: Life Science Research Board, Defence Research and Development Organization, New Delhi</p>

<p>Tenure of the project: Three years or till the end of the project period.</p>

<p>Position: Junior Research Fellow (1 no.)</p>

<p>Essential qualification: First class in M.Sc. in Genomics/Biotechnology/ Microbiology/ Biochemistry/Life Sciences</p>

<p>Desirable qualification: Experience in an area relevant (Molecular Microbiology, Protein engineering and Structural Bioinformatics) to the project.</p>

<p>Fellowship: Rs. 16, 000 per month plus HRA as per University rule.</p>

<p>Upper age limit: 28 years</p>

<p>Date of interview: 16-09-2013</p>

<p>Venue of interview: Department of Bioinformatics, Bharathidasan University, Tiruchirappalli -620 024, Tamil Nadu</p>

<p>The above post is purely temporary and will be terminated with three month notice. The Terms and the condition of the appointment shall be governed according to DRDO, Govt. of India. The eligible candidates will bring their original certificates and documents at the time of interview. No TA/DA will be paid for attending the interview.</p>

<p>Dr. P. CHELLAPANDI<br />Principal Investigator,<br />Department of Bioinformatics,<br />Bharathidasan University,<br />Tiruchirappalli -620 024, Tamil Nadu</p>

<p>Advertisement: http://www.bdu.ac.in/tender_list.php</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</guid>
	<pubDate>Thu, 12 Apr 2018 10:00:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</link>
	<title><![CDATA[G-compass: a comparative genome browser]]></title>
	<description><![CDATA[<p><span>G-compass (</span><a href="http://www.h-invitational.jp/g-compass/" target="_top">http://www.h-invitational.jp/g-compass/</a><span>) is a comparative genome browser. It visualizes evolutionarily conserved genomic regions between human and other 12 vertebrates based on original genome alignments pursuing higher coverage (1,2). Annotations of human genes/transcripts and their ortholog information were derived from&nbsp;</span><a href="http://www.h-invitational.jp/hinv/ahg-db/index.jsp" target="_top">H-InvDB</a><span>&nbsp;and its subdatabase&nbsp;</span><a href="http://www.h-invitational.jp/evola/" target="_top">Evola</a><span>, respectively. G-compass is available for free of charge. [&nbsp;</span><a href="http://www.h-invitational.jp/g-compass/cgi-bin/gc_main.cgi?species_1=Hg18&amp;species_2=pt2&amp;strand_1=%2B&amp;strand_2=%2B&amp;from_win=main&amp;gen_str=2&amp;chr_1=01&amp;chr_2=01&amp;st_1=103804298&amp;ed_1=104204297&amp;st_2=105235351&amp;ed_2=105635350" target="_top">Sample</a><span>&nbsp;]</span></p><p>Address of the bookmark: <a href="http://www.h-invitational.jp/g-compass/" rel="nofollow">http://www.h-invitational.jp/g-compass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/4482/bioinformatics-definitions-and-applications</guid>
	<pubDate>Thu, 12 Sep 2013 15:04:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/4482/bioinformatics-definitions-and-applications</link>
	<title><![CDATA[Bioinformatics definitions and applications !!!]]></title>
	<description><![CDATA[<p>There have been long discussion amongst several specialized/expert educator regarding bioinformatics arena, but everyone explain bioinformatics with their own view. I tried to explain it with a cartoon. Hope you all will like it.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/4482" length="49464" type="image/gif" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4575/hiv-phd-and-msc-research-positions</guid>
  <pubDate>Mon, 16 Sep 2013 18:55:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[HIV PhD and MSc Research Positions]]></title>
  <description><![CDATA[
<p>SANBI are looking to recruit two MSc students and a PhD student who are interested in implementing a computational biology approach to explore HIV’s glycan shield. Successful candidates for the MSc should hold an honours degree in physics, computer science or biological sciences while PhD applicants should hold an honours degree and a MSc in one or more of physics, computer science or biological sciences.</p>

<p>As these positions are funded by the South African National Research Foundation (NRF) priority will be given to South African citizens and permanent residents however exceptional applicants who do not fulfil these criteria may be considered.</p>

<p>Applications including a CV outlining your experience together with a cover letter detailing why you are a suitable candidate should be sent to simon_at_sanbi.ac.za by 30th September 2013.</p>

<p>More @ http://www.sanbi.ac.za/hiv-phd-and-msc-research-positions/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4657/giovanni-parmigiani-lab</guid>
  <pubDate>Fri, 20 Sep 2013 13:21:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Giovanni Parmigiani Lab]]></title>
  <description><![CDATA[
<p>Scientific Interests:</p>

<p>Models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer. Application to breast, ovarian, colorectal, pancreatic and skin cancer.</p>

<p>Statistical methods for the analysis of high throughput genomic data: analysis of cancer genome sequencing projects; integration of genomic information across technologies; cross-study validation of genomics results.</p>

<p>Statistical methods for comparative effectiveness research: comprehensive models for lifetime history of chronic disease outcomes; Bayesian meta-analysis; Bayesian causal inference; decision analysis.</p>

<p>Bayesian modeling and computation: multilevel models; decision theoretic approaches to inference; sequential experimental design and their application to adaptive and multistage studies in clinical and epidemiological research.</p>

<p>http://bcb.dfci.harvard.edu/~gp/index.html</p>

<p>http://scholar.google.com/citations?user=OlpYP3UAAAAJ&amp;hl=en</p>
]]></description>
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