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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27959?offset=70</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43272/bioinformatics-head-bioinformatics-manager-iii-cancer-genomics-research-laboratory-at-frederick-national-laboratory</guid>
  <pubDate>Wed, 18 Aug 2021 00:19:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at  Frederick National Laboratory]]></title>
  <description><![CDATA[
<p>Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR).  CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).</p>

<p>More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&amp;c=leidosbiomed&amp;id=2040</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44718/mycology-research-resources-for-bioinformaticians-unlocking-the-fungal-kingdom</guid>
	<pubDate>Fri, 13 Dec 2024 11:21:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44718/mycology-research-resources-for-bioinformaticians-unlocking-the-fungal-kingdom</link>
	<title><![CDATA[Mycology Research Resources for Bioinformaticians: Unlocking the Fungal Kingdom]]></title>
	<description><![CDATA[<p>Mycology, the study of fungi, is a field that bridges ecology, medicine, and biotechnology. With advancements in bioinformatics, researchers now have unprecedented opportunities to explore the fungal kingdom at molecular, genetic, and ecological levels. From understanding pathogenic fungi to harnessing fungal enzymes for industrial applications, the potential is vast.</p><p>To fully leverage these opportunities, bioinformaticians require specialized tools and databases. This blog highlights essential resources for mycology research, focusing on databases, tools, and platforms tailored for fungal biology.</p><h4><strong>1. Fungal Databases</strong></h4><h5><strong>1.1. MycoCosm</strong></h5><p><strong>Website</strong>: <a target="_new">MycoCosm</a><br />Developed by the DOE Joint Genome Institute, MycoCosm is a comprehensive portal for fungal genomics. It offers genomic and transcriptomic data for a wide range of fungi, including saprobes, pathogens, and symbionts.</p><ul>
<li><strong>Key Features</strong>: Genome browsers, comparative genomics tools, and functional annotations.</li>
<li><strong>Best For</strong>: Large-scale studies on fungal evolution and ecology.</li>
</ul><h5><strong>1.2. FungiDB</strong></h5><p><strong>Website</strong>: <a href="https://fungidb.org/" target="_new">FungiDB</a><br />FungiDB is an integrated genomic resource for fungal pathogens and non-pathogens. It provides access to genome sequences, transcriptomic data, and functional annotations.</p><ul>
<li><strong>Key Features</strong>: Advanced search options, BLAST, and pathway analysis tools.</li>
<li><strong>Best For</strong>: Studying fungal pathogenesis and host-pathogen interactions.</li>
</ul><h5><strong>1.3. Index Fungorum</strong></h5><p><strong>Website</strong>: <a href="http://www.indexfungorum.org/" target="_new">Index Fungorum</a><br />This nomenclatural database provides information on the scientific names of fungi. It&rsquo;s an essential resource for taxonomists and researchers focused on fungal biodiversity.</p><ul>
<li><strong>Key Features</strong>: Taxonomic hierarchy and synonymy tracking.</li>
<li><strong>Best For</strong>: Identifying and classifying fungal species.</li>
</ul><h5><strong>1.4. UNITE</strong></h5><p><strong>Website</strong>: <a target="_new">UNITE</a><br />UNITE is a specialized database for fungal ITS (Internal Transcribed Spacer) sequences, often used in fungal identification and phylogenetics.</p><ul>
<li><strong>Key Features</strong>: Curated reference datasets and community annotations.</li>
<li><strong>Best For</strong>: Environmental mycology and microbial ecology studies.</li>
</ul><h4><strong>2. Analytical Tools</strong></h4><h5><strong>2.1. Funannotate</strong></h5><p><strong>Repository</strong>: <a href="https://github.com/nextgenusfs/funannotate" target="_new">GitHub - Funannotate</a><br />Funannotate is a genome annotation tool designed for fungi. It supports tasks like gene prediction, functional annotation, and orthology analysis.</p><ul>
<li><strong>Best For</strong>: Annotating newly sequenced fungal genomes.</li>
</ul><h5><strong>2.2. BUSCO (Benchmarking Universal Single-Copy Orthologs)</strong></h5><p><strong>Website</strong>: <a target="_new">BUSCO</a><br />BUSCO evaluates genome assembly and annotation completeness using orthologs. It includes a fungal-specific dataset.</p><ul>
<li><strong>Best For</strong>: Assessing the quality of fungal genome assemblies.</li>
</ul><h5><strong>2.3. Pathogen-Host Interactions Database (PHI-base)</strong></h5><p><strong>Website</strong>: <a href="http://www.phi-base.org/" target="_new">PHI-base</a><br />PHI-base is a manually curated resource containing information on pathogen-host interactions, including fungal pathogens.</p><ul>
<li><strong>Best For</strong>: Exploring virulence factors and host-pathogen relationships.</li>
</ul><h4><strong>3. Visualization Platforms</strong></h4><h5><strong>3.1. Cytoscape</strong></h5><p><strong>Website</strong>: <a href="https://cytoscape.org/" target="_new">Cytoscape</a><br />A powerful tool for visualizing molecular interaction networks, Cytoscape can be used to study protein-protein interactions, gene networks, and metabolic pathways in fungi.</p><ul>
<li><strong>Best For</strong>: Network biology and functional genomics.</li>
</ul><h5><strong>3.2. iTOL (Interactive Tree of Life)</strong></h5><p><strong>Website</strong>: <a target="_new">iTOL</a><br />iTOL is an interactive tool for visualizing phylogenetic trees.</p><ul>
<li><strong>Best For</strong>: Displaying fungal phylogenies and comparing evolutionary relationships.</li>
</ul><h4><strong>4. Community Resources</strong></h4><h5><strong>4.1. Mycological Society of America (MSA)</strong></h5><p><strong>Website</strong>: <a href="https://msafungi.org/" target="_new">MSA</a><br />The MSA promotes fungal research and provides access to resources, conferences, and publications.</p><ul>
<li><strong>Best For</strong>: Networking with fungal researchers and accessing recent studies.</li>
</ul><h5><strong>4.2. OpenFungi</strong></h5><p><strong>Website</strong>: <a href="https://openfungi.org/" target="_new">OpenFungi</a><br />OpenFungi is an open-source initiative providing fungal genomic and transcriptomic datasets for research and education.</p><ul>
<li><strong>Best For</strong>: Sharing and accessing public fungal datasets.</li>
</ul><h4><strong>5. Genomics Workflows</strong></h4><h5><strong>5.1. Galaxy</strong></h5><p><strong>Website</strong>: <a href="https://usegalaxy.org/" target="_new">Galaxy Project</a><br />Galaxy offers a web-based platform for reproducible bioinformatics workflows, including tools for fungal genome and transcriptome analysis.</p><ul>
<li><strong>Best For</strong>: User-friendly analysis pipelines without requiring coding skills.</li>
</ul><h5><strong>5.2. Snakemake</strong></h5><p><strong>Repository</strong>: <a target="_new">Snakemake</a><br />A flexible pipeline management tool that supports fungal data processing and analysis.</p><ul>
<li><strong>Best For</strong>: Custom workflows for large-scale fungal datasets.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Fungal research is a rapidly growing field with vast implications for medicine, agriculture, and industry. For bioinformaticians, the availability of specialized resources&mdash;databases, tools, and community platforms&mdash;opens doors to innovative discoveries. Whether you are investigating fungal genomics, studying host-pathogen interactions, or exploring fungal biodiversity, the resources outlined above will empower your research journey.</p><p>Dive into these resources and help unravel the mysteries of the fungal kingdom!</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis</guid>
	<pubDate>Sat, 20 Mar 2021 00:28:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis</link>
	<title><![CDATA[List of bioinformatics packages for NGS analysis !]]></title>
	<description><![CDATA[<p>Package suites gather software packages and installation tools for specific languages or platforms. We have some for bioinformatics software.</p><ul>
<li><a href="https://github.com/Bioconductor">Bioconductor</a>&nbsp;&ndash; A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [&nbsp;<a href="https://link.springer.com/article/10.1186/gb-2004-5-10-r80">paper-2004</a>&nbsp;|&nbsp;<a href="https://www.bioconductor.org/">web</a>&nbsp;]</li>
<li><a href="https://github.com/biopython/biopython">Biopython</a>&nbsp;&ndash; Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the&nbsp;<a href="http://open-bio.org/">Open Bioinformatics Foundation</a>. Contains the very useful&nbsp;<a href="https://biopython.org/DIST/docs/api/Bio.Entrez-module.html">Entrez</a>&nbsp;package for API access to the NCBI databases. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/19304878">paper-2009</a>&nbsp;|&nbsp;<a href="https://biopython.org/">web</a>&nbsp;]</li>
<li><a href="https://github.com/bioconda">Bioconda</a>&nbsp;&ndash; A channel for the&nbsp;<a href="http://conda.pydata.org/docs/intro.html">conda package manager</a>&nbsp;specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with&nbsp;<code>conda install</code>) bioinformatics packages. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29967506">paper-2018</a>&nbsp;|&nbsp;<a href="https://bioconda.github.io/">web</a>&nbsp;]</li>
<li><a href="https://github.com/BioJulia">BioJulia</a>&nbsp;&ndash; Bioinformatics and computational biology infastructure for the Julia programming language. [&nbsp;<a href="https://biojulia.net/">web</a>&nbsp;]</li>
<li><a href="https://github.com/rust-bio/rust-bio">Rust-Bio</a>&nbsp;&ndash; Rust implementations of algorithms and data structures useful for bioinformatics. [&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/early/2015/10/06/bioinformatics.btv573.short?rss=1">paper-2016</a>&nbsp;]</li>
<li><a href="https://github.com/seqan/seqan3">SeqAn</a>&nbsp;&ndash; The modern C++ library for sequence analysis.</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40882/troyanskaya-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:40:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.</p>

<p>https://function.princeton.edu/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</guid>
	<pubDate>Tue, 27 Oct 2020 19:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</link>
	<title><![CDATA[Frequent parameters for bioinformatics tools !]]></title>
	<description><![CDATA[<div><div>Third party executable parameters and options.</div><div>&nbsp;</div><div>Trimmomatic</div><div>&nbsp;</div><div>&ldquo;ILLUMINACLIP:...:2:30:10&rdquo;</div><div>&ldquo;LEADING:15&rdquo;</div><div>&ldquo;TRAILING:15&rdquo;</div><div>&ldquo;SLIDINGWINDOW:4:20&rdquo;</div><div>&ldquo;MINLEN:20&rdquo;</div><div>&ldquo;TOPHRED33&rdquo;</div><div>&nbsp;</div><div>Filtlong</div><div>--min_length 500</div><div>--min_mean_q 85</div><div>--min_window_q 65</div><div>&nbsp;</div><div>FastQ Screen</div><div>--aligner bowtie2' (bwa for PacBio)</div><div>--subset 1000 (for PacBio)</div><div>&nbsp;</div><div>SPAdes</div><div>--careful</div><div>--disable-gzip-output</div><div>--cov-cutoff auto</div><div>--phred-offset 33</div><div>&nbsp;</div><div>HGAP</div><div>Pbalign.task_options.min_accuracy: 70</div><div>Pbalign.task_options.no_split_subreads: false</div><div>Genomic_consensus.task_options.min_confidence: 40</div><div>falcon_ns.task_options.HGAP_GenomeLength_str:</div><div>6000000</div><div>Pbcoretools.task_options.read_length: 0</div><div>Genomic_consensus.task_options.use_score: 0</div><div>Pbalign.task_options.min_length: 50</div><div>Pbalign.task_options.algorithm_options: --minMatch 12</div><div>--bestn 10 --minPctSimilarity 70.0</div><div>Pbalign.task_options.hit_policy: randombest</div><div>Pbcoretools.task_options.other_filters: rq &gt;= 0.7</div><div>Pbalign.task_options.concordant: false</div><div>Genomic_consensus.task_options.min_coverage: 5</div><div>falcon_ns.task_options.HGAP_SeedCoverage_str: 30</div><div>falcon_ns.task_options.HGAP_AggressiveAsm_bool: false</div><div>Genomic_consensus.task_options.algorithm: best</div><div>falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1</div><div>Genomic_consensus.task_options.diploid: false</div><div>&nbsp;</div><div>MeDuSa</div><div>-random 100</div><div>&nbsp;</div><div>Prokka</div><div>--usegenus</div><div>--force</div><div>--addgenes</div><div>--rfam</div><div>--rawproduct</div><div>&nbsp;</div><div>cmsearch (taxonomy, 16S)</div><div>--rfam</div><div>--noali</div><div>&nbsp;</div><div>blastn (taxonomy, 16S)</div><div>-evalue 1E-10</div><div>&nbsp;</div><div>blastn (MLST)</div><div>-ungapped</div></div><div><div>-dust no</div><div>-evalue 1E-20</div><div>-word_size 32</div><div>-culling_limit 2</div><div>-perc_identity 95</div><div>&nbsp;</div><div>blastp (VF)</div><div>-culling_limit 2</div><div>&nbsp;</div><div>RGI (ABR)</div><div>--input_type contig</div><div>&nbsp;</div><div>bowtie2 (mapping)</div><div>--sensitive</div><div>&nbsp;</div><div>minimap2 (mapping)</div><div>-a</div><div>-x map-ont</div><div>&nbsp;</div><div>samtools mpileup (SNP&nbsp;detection)</div><div>-uRI</div><div>&nbsp;</div><div>bcftools call (SNP detection)</div><div>--variants-only</div><div>--skip-variants indels</div><div>--output-type v</div><div>--ploidy 1</div><div>-c</div><div>&nbsp;</div><div>SNPsift filter (SNP detection)</div><div>"( QUAL &gt;= 30 ) &amp; (( na FILTER ) | (FILTER = 'PASS')) &amp;</div><div>( DP &gt;= 20 ) &amp; ( MQ &gt;= 20 )"</div><div>&nbsp;</div><div>SNPeff ann (SNP detection)</div><div>-nodownload</div><div>-no-intron</div><div>-no-downstream</div><div>-no SPLICE_SITE_REGION</div><div>-upDownStreamLen 250</div><div>&nbsp;</div><div>bcftools consensus</div><div>(phylogenetic tree)</div><div>--haplotype 1</div><div>&nbsp;</div><div>fasttreemp</div><div>-nt</div><div>-boot 100</div><div>&nbsp;</div><div>roary</div><div>-e</div><div>-n</div><div>-cd 100</div><div>-g 100000</div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<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/bookmarks/view/17924/software-developed-in-pevsner-lab</guid>
	<pubDate>Mon, 06 Oct 2014 12:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</link>
	<title><![CDATA[Software developed in pevsner lab]]></title>
	<description><![CDATA[<div>
<div id="block-system-main">
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<div>
<p><a href="http://pevsnerlab.kennedykrieger.org/dragon.htm">DRAGON</a>: Database Referencing of Array Genes Online</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/96">SNOMAD</a>: Standardization and Normalization of Microarray Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/70">SNPduo</a>: SNP Analysis Between Two Individuals</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/71">SNPtrio</a>: Analyzing and Visualizing and Inheritance Patterns in Trios</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">SNPscan</a>: Data Analysis and Visualization of SNP Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">pediSNP</a>: Analyze SNP Data From a Pedigree of Two Generations</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/73">kcoeff</a>: Calculate Cotterman Coefficients of SNP Genotype Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/113">triPOD:</a> Detects chromosomal abnormalities in parent-child trio-based microarray data</p>
</div>
</div>
</div>
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</div>
</div>
</div><p>Address of the bookmark: <a href="http://pevsnerlab.kennedykrieger.org/php/?q=software" rel="nofollow">http://pevsnerlab.kennedykrieger.org/php/?q=software</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19090/deeptools</guid>
	<pubDate>Sat, 08 Nov 2014 15:02:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19090/deeptools</link>
	<title><![CDATA[deepTools]]></title>
	<description><![CDATA[<p>deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.<br /><br />Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full<br /><br />Source Code and Wiki: https://github.com/fidelram/deepTools/wiki<br /><br />Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools<br /><br />and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22285/project-associate-bioinformatics-iit-mandi</guid>
  <pubDate>Wed, 06 May 2015 06:18:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Associate Bioinformatics @ IIT Mandi]]></title>
  <description><![CDATA[
<p>Eligibility : MSc(Bio-Informatics, Bio-Tech), BSc, BE/B.Tech(Bio-Medical /Bio-Technology Engg, CSE)</p>

<p>Location : Kulu</p>

<p>Job Category : Govt Jobs, Research</p>

<p>Last Date : 20 May 2015</p>

<p>Job Type : Full Time</p>

<p>Hiring Process : Walk - In<br />IIT Mandi - Job Details<br />IIT Mandi</p>

<p>Project Associate Bioinformatics Job vacancies in IIT Mandi on purely temporary</p>

<p>Project: “Exploring the Human Microbiome: A hunt for the candidates for Pre- and Pro-biotics.”</p>

<p>Minimum Qualification and Experience: M.Sc. in Bioinformatics OR B.Tech / BE in Bioinformatics OR M. Sc. in Biotechnology / Life sciences or related areas with Diploma or relevant experience in Bioinformatics OR B.Tech in Biotechnology / Computer Science or MCA or B. Sc. in Life Sciences or related areas with PG diploma in Bioinformatics. Candidates with experience in NGS data handling and analysis will be preferred. Tenure: Initially for one year, extendable based upon performance.</p>

<p>No of Posts: 01</p>

<p>Salary: Rs. 12000- 18000/- per month.</p>

<p>How to apply</p>

<p>Interested candidates can come for a Walk-in-Interview on 20th May 2015 starting at 8:30 AM at the Academic Block, Indian Institute of Technology (IIT), Mandi, Vallabh College Campus, Near Bus Stand, Mandi, HP. The candidates should bring along their curriculum vitae (CV) and copies of educational and experience certificates. In case of any queries please contact: Dr. Tulika Prakash Srivastava (Principal Investigator), Indian Institute of Technology Mandi, Near Bus Stand Mandi - 175 001, Himachal Pradesh.</p>

<p>More at</p>

<p>http://www.iitmandi.ac.in/administration/advrt/Walk-in-interview_Ad.pdf</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22317/project-associate-bioinformatics-central-food-technological-research-institute-cftri</guid>
  <pubDate>Tue, 19 May 2015 07:01:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Associate Bioinformatics @ Central Food Technological Research Institute (CFTRI)]]></title>
  <description><![CDATA[
<p>Central Food Technological Research Institute (CFTRI)</p>

<p>Project Assistant (Level-II) job position in Central Food Technological Research Institute (CFTRI) on a temporary contractual basis in the research project (GAP 0469) funded by Science &amp; Engineering Research Board (SERB), Government of India, New Delhi tenable at the Lipidomics Centre, CSIR-CFTRI, Mysore, Karnataka</p>

<p>Name of the Position : </p>

<p>Qualification : First class M. Sc. in Biochemistry/Microbiology/Genetics/ Bioinformatics with good academic record and preferably with experience in molecular biology techniques and basic knowledge of molecular biology and biological chemistry</p>

<p>Emoluments : Rs. 12,000/- per month (Consolidated)</p>

<p>Age Limit : The upper age limit for applying shall be 28 years (as on 22-5-2015), which is relaxed for candidates belonging to Scheduled Castes/Schedule Tribes, Women, Persons with Disabilities (PWD) and OBCs as per GoI norms. <br /> <br />How to apply</p>

<p>Eligible candidates may send their complete Bio-data with e-mail address/contact phone number along with attested copies of the necessary certificates through post to Prof. Ram Rajasekharan, Lipidomics Centre, Department of Lipid Science, CSIR-CFTRI, Mysore-570 020, Karnataka (email: ram@cftri.res.in) on or before 22.05.2015</p>

<p>More at http://www.cftri.com/pa_gap0469.html</p>
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