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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42012?offset=120</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22567/rosalind-problem-solution-with-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:35:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22567/rosalind-problem-solution-with-perl</link>
	<title><![CDATA[Rosalind Problem Solution with Perl]]></title>
	<description><![CDATA[<p>Rosalind is a platform for learning bioinformatics and programming through problem solving. <a href="http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track">Take a tour</a> to get the hang of how Rosalind works.</p><p>Bioinformatics Textbook Track</p><p>Find more about Rosalind puzzle at http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track</p><p>I will provide solution of all the Rosalind problem with Perl for community.</p><p>Check out the right sidebar for more links ...</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/23680/five-key-traits-to-seek-out-in-potential-bioinformatics-candidates</guid>
	<pubDate>Mon, 10 Aug 2015 12:53:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/23680/five-key-traits-to-seek-out-in-potential-bioinformatics-candidates</link>
	<title><![CDATA[Five key traits to seek out in potential bioinformatics candidates !!!]]></title>
	<description><![CDATA[<p>Genomics and proteomics data are being collected in bulk, but mostly, traditional biologist don&rsquo;t know what to do with it. Perhaps this is the reason why (not only this!!! ) computational biologist/bioinformatics scientists are hot commodities in the research world.</p><p>In fact, there are huge demands for expert biological data analyst. It&rsquo;s a fairly new &nbsp;(not exactly) hot area, these bioinformatician are invaluable because they know and understand the significance of biological data for your research and how you can use it for better understanding of biological problems.</p><p>The bioinformatics can discover biological patterns and stories in genomic and proteomics data. They can develop the pipeline needed to properly collect, store and analyse it.</p><p><img src="http://bioinformaticsonline.com/mod/photo/hire.gif" alt="image" style="border: 0px;"></p><p>Once your research group is ready to make a larger investment and hire a bioinformatician to gain a competitive edge, there are several key traits to seek out in potential candidates. The best bioinformatician are:</p><p>1. Highly Skilled - programming skills, experience with the biological software and tools.</p><p>The biological data won&rsquo;t illuminate much if the scientist analysing it doesn&rsquo;t possess practical programming skills, experience with the biological software and tools and a thorough understanding of basic biological stuff. A solid background in mathematics and statistics is also an indispensable trait.</p><p>2. Insight - Real vision, robust understanding and deep insight.</p><p>In order to hire the best bioinformatics and computational biologist scientist for your needs, it is always recommended and mostly practiced by the recruiters, to ask each contender to write and develop a sample script/presentation based on a specific set of data you provide. Then, explore the approaches used to deal with data provided and pick up those candidates who convey real vision, robust understanding and deep insight.</p><p>3. Energetic &ndash; Curiosity to explore</p><p>Mostly natural curiosity and enthusiasm for solving big biological problems coupled with an ability to transform data into a scientific stories may place one candidate above the rest. In addition to achieve that, the bioinformatician should be agile enough to quickly modify their methods to suit changes within a particular research.</p><p>4. Researcher &ndash; Publications</p><p>Look for someone who has a keen sense and understanding of concern biological problems. You can judge it by looking at previously published papers and data. It is always recommended to have a look at GitHub and other repository for codes written by her/him.</p><p>5. Impressive communicator - Insight that can&rsquo;t be expressed is worthless.</p><p>Good bioinformatics scientists are able to uncover biological patterns and are willing to explain those patterns in clear and helpful ways through thoughtful and open communication. In other words, they should must have good scientific writing skills. A computational biologis/bioinformatician&nbsp; should know how to present the data and tell a scientific story through numbers/images.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42809/bioinformatics-in-africa-part2-kenya</guid>
	<pubDate>Sat, 06 Feb 2021 13:23:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42809/bioinformatics-in-africa-part2-kenya</link>
	<title><![CDATA[Bioinformatics in Africa: Part2 - Kenya]]></title>
	<description><![CDATA[<p>International Livestock Research Institute (ILRI):</p><p>Under&nbsp; &nbsp;a&nbsp; &nbsp;NEPAD&nbsp; &nbsp;initiative,&nbsp; &nbsp;the&nbsp; &nbsp;Biosciences&nbsp; &nbsp;Eastern&nbsp; &nbsp;and&nbsp; &nbsp;Central&nbsp; &nbsp;Africa&nbsp; &nbsp;(BECA)&nbsp; (www.biosciencesafrica.org) was established at ILRI. BECA consists of a hub, regional nodes, and&nbsp; other affiliated laboratories and partner institutes. A state of the art joint Bioinformatics Platform&nbsp; (www.becabioinfo.org), whose overall goal is to provide a coherent and powerful bioinformatics&nbsp; infrastructure for use by all scientists in East and central Africa. The Platform goal requires both&nbsp; physical and intellectual developments that together provide researchers with access to diverse&nbsp; infrastructure in a wide&shy;area network, thereby addressing four important aspects of bioinformatics:&nbsp;</p><p>1) Science: bioinformatics tools for data integration and visualization, standardization of data&nbsp; formats and data analysis strategies, and distribution of analysis tasks over local&shy; and widearea networks are in development;&nbsp;</p><p>2)&nbsp; Bioinformatics Support Facility: provides assistance and custom programming to projects&nbsp; and those unable to establish a bioinformatics support function intrinsic to their project due&nbsp; to shortage of qualified personnel or lack of funding;&nbsp;</p><p>3) Hardware Platform: provide a powerful high performance computing platform capable of&nbsp; handling the largest analysis needs for projects;&nbsp;</p><p>4) Bioinformatics Training for East and central African scientists: While many Web&shy;based&nbsp; tools are available to the wet&shy;lab researcher, the Web is not well suited for tasks beyond&nbsp; single&shy;sequence annotation. Researchers need to become productive in a server&shy;based Unix&nbsp; environment with its wealth of scripting and automation tools. Even at an entry&shy;level, this&nbsp; can be an intimidating task if proper guidance is not available.</p><p>International&nbsp;Centre&nbsp;of&nbsp;Insect&nbsp;Physiology&nbsp;and&nbsp;Ecology&nbsp;(ICIPE): ICIPE&rsquo;s&nbsp;research&nbsp;focus&nbsp;is&nbsp;on&nbsp;insect&nbsp;biology,&nbsp;in&nbsp;order&nbsp;to&nbsp;improve&nbsp;the&nbsp;wellbeing&nbsp;of&nbsp;the&nbsp;peoples&nbsp;of&nbsp;the&nbsp; tropics&nbsp;through&nbsp;insect&nbsp;science.&nbsp;There&nbsp;is&nbsp;a&nbsp;commitment&nbsp;to&nbsp;utilise&nbsp;contemporary&nbsp;science&nbsp;in&nbsp;order&nbsp;to&nbsp; limit&nbsp;the&nbsp;impact&nbsp;of&nbsp;disease&nbsp;vectors,&nbsp;and&nbsp;agricultural&nbsp;pests.&nbsp;The&nbsp;understanding&nbsp;of&nbsp;the&nbsp;mechanisms&nbsp; associated&nbsp;with&nbsp;behaviour&nbsp;(e.g.&nbsp;attraction&nbsp;and&nbsp;repellency)&nbsp;is&nbsp;crucial.&nbsp;ICIPE&nbsp;seeks&nbsp;to&nbsp;enhance&nbsp;its&nbsp; bioinformatics&nbsp;capacity&nbsp;in&nbsp;order&nbsp;to&nbsp;support&nbsp;data&nbsp;from&nbsp;various&nbsp;EST&nbsp;projects&nbsp;designed&nbsp;to&nbsp;gain&nbsp;insights&nbsp; into&nbsp;the&nbsp;insect&nbsp;ecology&nbsp;and&nbsp;plant&nbsp;pathogen&nbsp;interactions&nbsp;though&nbsp;studies&nbsp;of&nbsp;metabolic&nbsp;pathways&nbsp; associated&nbsp;with&nbsp;production&nbsp;of&nbsp;all&nbsp;elochemicals.&nbsp;</p><p>Long&shy;term training activities:</p><p>Kenyatta University: An introductory course in Bioinformatics is offers to MSc Biotechnology&nbsp; students. This comprises of 35 hours of lectures and practicals.</p><p>University of Nairobi: A centre for Biotechnology and Bioinformatics (CEBIB), which will offer&nbsp; postgraduate training (diplomas, MSc and PhD) in areas of biotechnology and bioinformatics has&nbsp; recently been launched. Other universities in Kenya, including Egerton, Maseno and the Jomo Kenyatta University of&nbsp; Agriculture and Technology offer introductory courses to undergraduates in biomedical sciences. In addition, under the BECA platform MSc and PhD fellowships are being made available for&nbsp; Bioinformatics students. ILRI is forging links with Universities in South Africa and the United&nbsp; Kingdom to provide access to courses and training material.&nbsp;</p><p>Research Interest and Activities:</p><p>The following are the present areas of research interest: 1. EST clustering 2. Genome sequencing and annotation 3. Functional genomics and proteomics (including key tropical pathogens) 4. Structural bioinformatics 5. Development of Bioinformatics Data Management Systems 6. Gene Mining 7. High Throughput Genotyping 8. Microarray data management and analysis 9. Metagenomics 10. Immunoinformatics 11. Host&shy;pathogen interaction 12. High performance computing and grid development 13. Parasite transfection technologies 14. Cell cycle regulation 15. Population genetics 16. Vector genomics 17. Drug, vaccine and diagnostic target discovery</p><p>More at&nbsp;Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ilri.cgiar.org/</p><p>http://www.icipe.org/ &nbsp; &nbsp;</p><p>http://www.uonbi.ac.ke/cebib</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</guid>
	<pubDate>Fri, 24 Aug 2018 09:50:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</link>
	<title><![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]></title>
	<description><![CDATA[<p>Mulan: Multiple-sequence local alignment and visualization for studying function and evolution</p>
<p><span>Mulan (</span><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/#ref44">http://mulan.dcode.org/</a><span>), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</guid>
	<pubDate>Fri, 07 Feb 2020 07:16:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</link>
	<title><![CDATA[Consed--A Finishing Package (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)]]></title>
	<description><![CDATA[<ul>
<li>Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types</li>
<li>Consed includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targeted regions.</li>
<li>Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.</li>
<li>Quickly takes the user to each variant site for viewing (also available as an automated report)</li>
<li>Overview of assembly can help detect and fix misassemblies</li>
<li>Editing time reduced by the program's ability to pin-point problem areas</li>
<li>Editing is guided by error probabilities</li>
</ul><p>Address of the bookmark: <a href="http://www.phrap.org/consed/consed.html" rel="nofollow">http://www.phrap.org/consed/consed.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40591/modelstudio-a-package-automates-the-explanation-of-machine-learning-predictive-models</guid>
	<pubDate>Wed, 22 Jan 2020 23:58:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40591/modelstudio-a-package-automates-the-explanation-of-machine-learning-predictive-models</link>
	<title><![CDATA[modelStudio: a package automates the explanation of machine learning predictive models]]></title>
	<description><![CDATA[<p>The&nbsp;<code>modelStudio</code>&nbsp;package automates the explanation of machine learning predictive models. This package generates advanced interactive and animated model explanations in the form of a serverless HTML site.</p>
<p>It combines&nbsp;<strong>R</strong>&nbsp;with&nbsp;<strong>D3.js</strong>&nbsp;to produce plots and descriptions for various local and global explanations. Tools for model exploration unite with tools for EDA (Exploratory Data Analysis) to give a broad overview of the model behavior.&nbsp;<code>modelStudio</code>&nbsp;is a fast and condensed way to get all the answers without much effort. Break down your model and look into its ingredients with only a few lines of code.</p><p>Address of the bookmark: <a href="https://modeloriented.github.io/modelStudio/index.html" rel="nofollow">https://modeloriented.github.io/modelStudio/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</guid>
	<pubDate>Thu, 24 Jun 2021 05:43:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</link>
	<title><![CDATA[Luigi: a Python package that helps you build complex pipelines of batch jobs.]]></title>
	<description><![CDATA[<p>Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more.</p>
<p>Run <code>pip install luigi</code> to install the latest stable version from <a href="https://pypi.python.org/pypi/luigi">PyPI</a>. <a href="https://luigi.readthedocs.io/en/stable/">Documentation for the latest release</a> is hosted on readthedocs.</p>
<p>Run <code>pip install luigi[toml]</code> to install Luigi with <a href="https://luigi.readthedocs.io/en/stable/configuration.html">TOML-based configs</a> support.</p><p>Address of the bookmark: <a href="https://github.com/spotify/luigi" rel="nofollow">https://github.com/spotify/luigi</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</guid>
	<pubDate>Tue, 07 Mar 2017 08:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</link>
	<title><![CDATA[PhenoGram]]></title>
	<description><![CDATA[<p><span>With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.</span></p><p>Address of the bookmark: <a href="http://ritchielab.psu.edu/software/phenogram-downloads" rel="nofollow">http://ritchielab.psu.edu/software/phenogram-downloads</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1178/r-package-for-visualising-go-enrichment</guid>
	<pubDate>Mon, 22 Jul 2013 12:25:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1178/r-package-for-visualising-go-enrichment</link>
	<title><![CDATA[R package for visualising GO enrichment]]></title>
	<description><![CDATA[<p>An R package that visualizes the GO enrichment results as word clouds and arranges them together with figures of experimental data. This allows us to draw informative summary plots for analyses such as differential expression or clustering, where for each gene list we display its behaviour in the experiment alongside with its GO annotations.</p><p>Links @ http://raivokolde.github.io/GOsummaries/</p><p>Lab @ http://biit.cs.ut.ee/about/main</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar</guid>
	<pubDate>Wed, 11 Sep 2013 10:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar</link>
	<title><![CDATA[Upcoming R Webinar]]></title>
	<description><![CDATA[<p>This webinar will describe an R based approach to considerably speed GWAS computation time on a notebook book computer.</p><p>More http://www.extension.org/pages/68354/upcoming-webinar:-fast-semi-parallel-linear-and-logistic-regression-for-genome-wide-association-studi#.UjCL9azyPqV</p><p>Register @ https://www1.gotomeeting.com/register/237810425</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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