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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28112?offset=340</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</guid>
	<pubDate>Tue, 17 May 2016 01:43:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</link>
	<title><![CDATA[ORFfinder with smart BLAST]]></title>
	<description><![CDATA[<p><span>ORF Finder</span></p><p><span><a href="http://www.ncbi.nlm.nih.gov/orffinder">ORFfinder</a><span>&nbsp;is a graphical analysis tool for finding open reading frames (ORFs). We&rsquo;ve been working on a few updates, and we&rsquo;d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.</span></span></p><p>Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)</p><p>Select one or a group of ORFs and BLAST several databases at once, and use the newly developed&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/smartblast/">SmartBLAST</a>&nbsp;to verify protein names.&nbsp;Looking for the traditional results from&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">BLAST</a>? They&rsquo;re there too.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/27455/blosum50-matrix</guid>
	<pubDate>Sat, 21 May 2016 22:12:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/27455/blosum50-matrix</link>
	<title><![CDATA[BLOSUM50 Matrix]]></title>
	<description><![CDATA[]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/27455" length="2088" type="text/x-fortran" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27479/biogps</guid>
	<pubDate>Mon, 23 May 2016 03:15:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27479/biogps</link>
	<title><![CDATA[BioGPS]]></title>
	<description><![CDATA[<p>A free&nbsp;<em>extensible</em>&nbsp;and&nbsp;<em>customizable</em>&nbsp;<strong>gene annotation portal</strong>, a complete resource for learning about&nbsp;<strong>gene and protein function</strong>.</p>
<p>http://biogps.org/#goto=welcome</p><p>Address of the bookmark: <a href="http://biogps.org/#goto=welcome" rel="nofollow">http://biogps.org/#goto=welcome</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27679/cluego</guid>
	<pubDate>Thu, 02 Jun 2016 09:51:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27679/cluego</link>
	<title><![CDATA[ClueGO]]></title>
	<description><![CDATA[<p>ClueGO is a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network and it can be used in combination with GOlorize.</p><p>Address of the bookmark: <a href="http://www.ici.upmc.fr/cluego/" rel="nofollow">http://www.ici.upmc.fr/cluego/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27827/guest-faculty-centre-for-bioinformatics-at-pondicherry-university</guid>
  <pubDate>Wed, 15 Jun 2016 03:44:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Faculty Centre for Bioinformatics at Pondicherry University]]></title>
  <description><![CDATA[
<p>Guest Faculty Centre For Bioinformatics Jobs opportunity in Pondicherry University<br />Qualification : M.Phil. (with NET/SLET)/ M.Tech. / M.E. in Computer Science with a minimum of 55% of marks as per UGC norms.<br />Desirable : Ph.D and Teaching experience in Perl and Java programming.<br />Honorarium : Rs. 1,000/- per lecture (subject to a maximum of Rs. 25,000/- per month)<br />How to apply<br />Walk-in-Interview will be held on 29.06.2016 (Wednesday) at 2:30 P.M at the office of Centre for Bioinformatics, Pondicherry University, Puducherry — 605 014. Interested eligible candidates may attend the Walk-in-Interview along with all original certificates, self attested photocopies and testimonials with a copy of their bio-data. Candidates reporting after 2:30 P.M will not be entertained.</p>

<p>More at http://www.pondiuni.edu.in/news?quicktabs_2=5#quicktabs-2</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</guid>
	<pubDate>Wed, 22 Jun 2016 05:37:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</link>
	<title><![CDATA[DarkHorse]]></title>
	<description><![CDATA[<p><em>DarkHorse</em>&nbsp;is a bioinformatic method for rapid, automated identification and ranking of phylogenetically atypical proteins on a genome-wide basis. It works by selecting potential ortholog matches from a reference database of amino acid sequences, then using these matches to calculate a lineage probability index (LPI) score for each genome protein.</p>
<p>LPI scores are inversely proportional to the phylogenetic distance between database match sequences and the query genome. These scores are useful not only for large-scale<em>de novo</em>&nbsp;predictions of horizontally transferred proteins, but can also serve as an independent quality control test for potential horizontal transfer candidates identified by alternative methods, especially those based on nucleic acid signatures. Candidates having high LPI scores are unlikely to have been horizontally transferred, since they are highly conserved among closely related organisms.</p>
<p>One unique and powerful feature of the DarkHorse HGT Candidate database is the opportunity to explore the phylogenetic background of potential HGT donors as well as recipients. The breadth of the database allows not only query sequences, but also their database match partners to be evaluated for sequence similarity or novelty compared to taxonomically related organisms.</p>
<p><em>DarkHorse</em>&nbsp;is configurable for varying degrees of phylogenetic granularity and protein sequence conservation. Users should consult the&nbsp;<a href="http://darkhorse.ucsd.edu/#references">references</a>&nbsp;cited below for a complete explanation of parameter selection and result interpretation. A brief&nbsp;<a href="http://darkhorse.ucsd.edu/tutorial.html">tutorial</a>&nbsp;page is also available on-line.</p><p>Address of the bookmark: <a href="http://darkhorse.ucsd.edu/download.html" rel="nofollow">http://darkhorse.ucsd.edu/download.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27961/nearhgt</guid>
	<pubDate>Wed, 22 Jun 2016 05:41:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27961/nearhgt</link>
	<title><![CDATA[NearHGT]]></title>
	<description><![CDATA[<p>Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive.</p>
<p>We developed a novel, self-contained technique named&nbsp;<em>Near HGT</em>, based on the&nbsp;<em>synteny index</em>, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the&nbsp;<em>constant relative mutability</em>&nbsp;(CRM). Using CRM, the algorithm assigns a confidence score based on &ldquo;unusual&rdquo; sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three&nbsp;<em>E. coli</em>&nbsp;strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set.</p>
<p>When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain.</p>
<p><strong>Availability:</strong><span>&nbsp;The method is publicly available at</span><a href="http://research.haifa.ac.il/~ssagi/software/nearHGT.zip">http://research.haifa.ac.il/~ssagi/software/nearHGT.zip</a></p><p>Address of the bookmark: <a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004408" rel="nofollow">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004408</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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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>
</item>
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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/opportunity/view/28577/research-associate-computer-sciences-recruitment-in-national-bureau-of-plant-genetic-resources</guid>
  <pubDate>Thu, 28 Jul 2016 04:39:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate (Computer Sciences) recruitment in National Bureau of Plant Genetic Resources]]></title>
  <description><![CDATA[
<p>Research Associate (Computer Sciences) recruitment in National Bureau of Plant Genetic Resources</p>

<p>Project: Indo-UK Centre for improvement of Nitrogen use efficiency in wheat Dr. Soma S. Marla, Pr. Scientist (Bioinformatics), Division of Genomic Resources, ICAR, NBPGR, ND.</p>

<p>Qualification: Ph.D. Degree in Computer Sciences/Bioinformatics OR 1. First class Master’s degree in any discipline of Plant Sciences with specialization in Computer Sciences/ Bioinformatics having 1st division or 60% marks or equivalent overall grade point average with at least two years of research experience as evidenced from Fellowship/ Associate ship. 2. NET qualification is essential for the candidates with 3+2 years B.Sc.+ M.Sc. Desirable: Demonstrated experience &amp; skills in database design, management, UNIX OS, in NGS data analysis. Experience substantiated by publications of high quality will be preferred.</p>

<p>No.of Post: 1</p>

<p>Pay Scale: Rs. 40,000 (Ph.D)/ Rs + 30 % HRA; Rs.38,000 ( Masters Degree 0 + 30 % HRA).</p>

<p>Age Limit : below 40 years for RA position<br />How to apply<br />Applicants for RA post should send their complete CV (Advance copy of the application may be sent by email to :soma.marla@icar.gov.in or ssmarl@yahoo.com, should enclose the copy of the research publications; one page summary of their achievement relevant to the post applied for; and should enclose two reference letters (one must be from the person with whom worked latest). Shortlisted candidate will be intimated for interview by email.</p>

<p>The candidates who wish to attend the walk-in interview are requested to bring with them five copies of the CV (one copy with photograph) as per the format given below. Also, the candidates should bring the original documents such as degree certificates, marks sheets, publications, thesis, experience certificate etc. for verification. </p>

<p>Date of Interview: 17.8.2016.</p>

<p>More at http://www.nbpgr.ernet.in/Downloadfile.aspx?EntryId=7133</p>
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