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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28449?offset=640</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</guid>
	<pubDate>Thu, 07 Jul 2016 12:05:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</link>
	<title><![CDATA[Fancy Oneliner for Bioinformatics !!]]></title>
	<description><![CDATA[<p><span>This webpage lists some of the one-liners that we frequently use in metagenomic analyses. You can click on the following links to browse through different topics. You can copy/paste the commands as they are in your terminal screen, provided you follow the same naming conventions and folder structures as we have. We are sharing these codes with the intention that if they are useful and help you in your analyses, then we will be appropriately credited as considerable effort has been put into devising them.</span></p><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/28439/binc-exam-preparation-tips</guid>
	<pubDate>Fri, 15 Jul 2016 20:53:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/28439/binc-exam-preparation-tips</link>
	<title><![CDATA[BINC exam preparation tips !!]]></title>
	<description><![CDATA[<p>How to prepare for <span>BINC (BioInformatics National Certification)</span>&nbsp;exam? What are the expected questions?</p><p>These are just a scant few of the common questions asked by bioinformatics students as they ready themselves for the next exam sitting. If you read the entire <a href="http://bioinformaticsonline.com/bookmarks/view/2334/binc-bioinformatics-national-certification-website-address">Syllabus</a> (and I know that everyone does), you will see a section devoted to study and exam techniques. The section discusses such broad concepts as motivation, scheduling, and retention. Upon reading this section, however, I find the "hints" to be too general. Much of the advice boils down to read, study, understand, and memorize the material. The techniques mentioned apply to everyone and thus the overall advice ends up as a broad overview of the learning process.</p><p>The idea behind this article is to give students ideas on different approaches and techniques in the preparation for exams. By providing various ways to prepare for the exam process, fascinated readers may gain some additional insight to help complement their studying methodology. There are, of course, many common themes expressed in this small empirical sample of students' study habits. The idea of note cards, memorization, and problem solving are frequently mentioned by all students. No matter what technique a candidate uses, it always takes a significant amount of time and personal resources to successfully complete the examination process.</p><p>1 Explain it in your own word</p><p>Your teacher or lecturer can explain something to you, you can learn it from a text book, your friends can study with you, even your own notes can explain it to you but all these explanations are of little use if, by the end, you can&rsquo;t explain what you have learned to yourself. The BINC exam looking for ability to write and explain the concept in your own word. You, therefore, need to illustrate in an exam to get top exam results, then you won&rsquo;t be happy with your end exam result. So don&rsquo;t just memorise and tick off the list &ndash; make sure you understand your theory.</p><p>2 Be an examiner yourself</p><p>Of course, depending on what you&rsquo;re studying, it may be quite difficult to get into a position to understand a concept, theory or other information you need to learn. Ask &lsquo;stupid&rsquo; question to yourself and train yourself for the worst! Embrace your curiosity, for as William Arthur Ward said: &ldquo;Curiosity is the wick in the candle of learning.&rdquo; Doing so will allow you to fill in the blanks and better prepare you for exams.</p><p>3 Quiz yourself</p><p>Once you feel you understand topic, it is important to test yourself regularly. Try yourself to replicate exam conditions as much as possible: turn your phone off, don&rsquo;t talk, time yourself etc. You can set yourself a study quiz or practice exam questions and, so long as you approach it with the right mindset, you can get a very good idea of how much you know. You gain a greater insight into where you stand in relation to what you&rsquo;ve studied so far.</p><p>4 Online study</p><p>Keeping the fact that, bioinformatics is ever changing subject, you might need to update yourself on timely basis. Don&rsquo;t feel obliged to just sit in front of a book with a highlighter; there are many different ways to improve your bioinformatics knowledge. Login and check almost all web servers and keep yourself updated, like how many genomes sequenced, sizes, techniques used, software names etc.</p><p>5 Study plan</p><p>In order to achieve exam success, you need to know what you want to achieve and focus on. That&rsquo;s why it is extremely important to set your Study Goals now and outline to yourself what you need to do. With your study goals in mind, you properly need to attention all subjects. It should be broad enough to allow you to add and change aspects but concise enough so you know you&rsquo;re covering each subject/topic as best you can at this point.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/28563/find-predicted-crispr-sites-using-ensembl</guid>
	<pubDate>Wed, 27 Jul 2016 03:15:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/28563/find-predicted-crispr-sites-using-ensembl</link>
	<title><![CDATA[Find predicted CRISPR sites using Ensembl]]></title>
	<description><![CDATA[<p>Did you know that you can now use Ensembl to help design your CRISPR experiments? Just turn on the brand new track that shows you the CRISPR sites that have been predicted by the WGE group (<a href="http://www.sanger.ac.uk/science/tools/wge" target="_blank">http://www.sanger.ac.uk/science/tools/wge</a>)</p><p><img src="http://www.ensembl.info/wp-content/uploads/2016/07/Screen-Shot-2016-07-22-at-13.04.33.png" width="1400" height="544" alt="image" style="border: 0px;"></p><p>Find out more on our blog:<br /><a href="http://www.ensembl.info/blog/2016/07/26/find-predicted-crispr-sites-using-ensembl/" target="_blank">http://www.ensembl.info/&hellip;/find-predicted-crispr-sites-usin&hellip;/</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29103/genome-strip</guid>
	<pubDate>Tue, 06 Sep 2016 03:58:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29103/genome-strip</link>
	<title><![CDATA[Genome STRiP]]></title>
	<description><![CDATA[<p><strong>Genome STRiP</strong><span>&nbsp;(Genome STRucture In Populations) is a suite of tools for discovering and genotyping structural variations using sequencing data. The methods are designed to detect shared variation using data from multiple individuals.</span><br><br><span>Genome STRiP looks both across and within a set of sequenced genomes to detect variation. The methods are adaptive and support heterogeneous data sets, including variations in sequencing depth, read lengths and mixtures of paired and single-end reads. A minimum of 20 to 30 genomes are required to get acceptable results, but the method gains power across genomes and processing more genomes provide better results.</span><br><br><span>To run discovery or genotyping on a single sequenced genome or a small set of genomes, you need to call your data against a background population, such as a set of genomes from the 1000 Genomes Project.&nbsp; The background population does not need to be matched to the target individuals.</span></p><p>Address of the bookmark: <a href="http://software.broadinstitute.org/software/genomestrip/" rel="nofollow">http://software.broadinstitute.org/software/genomestrip/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</guid>
	<pubDate>Mon, 05 Sep 2016 04:07:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<ul>
<li>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between&nbsp;<em>different assemblies</em>&nbsp;(such as Human&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</li>
<li>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</li>
<li>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s&nbsp;<em>not</em>&nbsp;a program for aligning sequences to reference genome.</li>
<li>We&nbsp;<em>do not</em>&nbsp;recommend using CrossMap to convert genome coordinates between species.</li>
</ul><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</guid>
	<pubDate>Tue, 16 Aug 2016 08:13:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</link>
	<title><![CDATA[OrganellarGenomeDRAW]]></title>
	<description><![CDATA[<p><span>O</span><span>rganellar</span><span>G</span><span>enome</span><span>DRAW</span><span>&nbsp;is dedicated to convert genetic information stored in GenBank entries to graphical maps. The input text file has to be in GenBank flat file format, whereas the output format can be chosen among several formats. The application is especially optimized and adapted for the creation of high-quality, detailed circular maps of organellar genomes like the plastid genome (plastome) or the mitochondrial genome (chondriome). Nevertheless, you can upload any GenBank entry. The workflow is devided into three steps.&nbsp;</span></p>
<p><span>More at&nbsp;http://ogdraw.mpimp-golm.mpg.de/cgi-bin/ogdraw.pl</span></p><p>Address of the bookmark: <a href="http://ogdraw.mpimp-golm.mpg.de/index.shtml" rel="nofollow">http://ogdraw.mpimp-golm.mpg.de/index.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28844/teannot</guid>
	<pubDate>Thu, 18 Aug 2016 10:02:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28844/teannot</link>
	<title><![CDATA[TEannot]]></title>
	<description><![CDATA[<p>We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto" rel="nofollow">https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28870/genemania</guid>
	<pubDate>Mon, 22 Aug 2016 09:55:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28870/genemania</link>
	<title><![CDATA[GeneMANIA]]></title>
	<description><![CDATA[<p>Faster, more accurate algorithms function prediction "GeneMANIA (Multiple Association Network Integration Algorithm)" have however been developed in recent years and are publicly available on the web, indicating the future direction of function prediction.</p><p>Address of the bookmark: <a href="http://genemania.org/" rel="nofollow">http://genemania.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28903/genevalidator-identify-problems-with-predicted-genes</guid>
	<pubDate>Fri, 26 Aug 2016 06:00:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28903/genevalidator-identify-problems-with-predicted-genes</link>
	<title><![CDATA[GeneValidator - Identify problems with predicted genes]]></title>
	<description><![CDATA[<p>GeneValidator helps in identifing problems with gene predictions and provide useful information extracted from analysing orthologs in BLAST databases. The results produced can be used by biocurators and researchers who need accurate gene predictions.</p>
<p>If you would like to use GeneValidator on a few sequences, see our online&nbsp;<a href="http://genevalidator.sbcs.qmul.ac.uk/">GeneValidator Web App</a>&nbsp;-<a href="http://genevalidator.sbcs.qmul.ac.uk/">http://genevalidator.sbcs.qmul.ac.uk</a>.</p>
<p>If you use GeneValidator in your work, please cite us as follows:</p>
<blockquote>
<p><a href="http://bioinformatics.oxfordjournals.org/content/early/2016/02/26/bioinformatics.btw015">Dragan M<span>&Dagger;</span>, Moghul MI<span>&Dagger;</span>, Priyam A, Bustos C &amp; Wurm Y. 2016. GeneValidator: identify problems with protein-coding gene predictions.&nbsp;<em>Bioinformatics</em>, doi: 10.1093/bioinformatics/btw015</a>.</p>
<p>&nbsp;</p>
</blockquote>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/wurmlab/genevalidator" rel="nofollow">https://github.com/wurmlab/genevalidator</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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