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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29992?offset=550</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28168/sam-flags</guid>
	<pubDate>Wed, 29 Jun 2016 15:38:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28168/sam-flags</link>
	<title><![CDATA[SAM flags]]></title>
	<description><![CDATA[<p>Decoding SAM flags</p>
<p>This utility makes it easy to identify what are the properties of a read based on its SAM flag value, or conversely, to find what the SAM Flag value would be for a given combination of properties.</p>
<p>To decode a given SAM flag value, just enter the number in the field below. The encoded properties will be listed under Summary below, to the right.</p><p>Address of the bookmark: <a href="https://broadinstitute.github.io/picard/explain-flags.html" rel="nofollow">https://broadinstitute.github.io/picard/explain-flags.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43795/anchorwave</guid>
	<pubDate>Wed, 23 Feb 2022 08:14:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43795/anchorwave</link>
	<title><![CDATA[AnchorWave]]></title>
	<description><![CDATA[<p dir="auto">AnchorWave (Anchored Wavefront Alignment) identifies collinear regions via conserved anchors (full-length CDS and full-length exon have been implemented currently) and breaks collinear regions into shorter fragments, i.e., anchor and inter-anchor intervals. By performing sensitive sequence alignment for each shorter interval via a 2-piece affine gap cost strategy and merging them together, AnchorWave generates a whole-genome alignment for each collinear block. AnchorWave implements commands to guide collinear block identification with or without chromosomal rearrangements and provides options to use known polyploidy levels or whole-genome duplications to inform alignment.</p><p>Address of the bookmark: <a href="https://github.com/baoxingsong/AnchorWave" rel="nofollow">https://github.com/baoxingsong/AnchorWave</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</guid>
	<pubDate>Wed, 29 Jun 2016 07:33:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</link>
	<title><![CDATA[CSBB-v1.0]]></title>
	<description><![CDATA[<p>CSBB is a command line based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R and python in background for specific modules. Major focus of CSBB is to allow users from biology and bioinformatics community, to get benefited by performing down-stream analysis tasks while eliminating the need to write programming code. CSBB is currently available on Linux, UNIX, MAC OS and Windows platforms.</p>
<p>Currently CSBB provides 13 modules focused on analytical tasks like performing upper-quantile normalization on expression data or convert genome wide gene expression to z-scores when comparing expression data from different platforms.</p>
<p>More at&nbsp;https://github.com/skygenomics/CSBB-v1.0</p><p>Address of the bookmark: <a href="https://github.com/skygenomics/CSBB-v1.0" rel="nofollow">https://github.com/skygenomics/CSBB-v1.0</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</guid>
	<pubDate>Sat, 08 Jun 2024 16:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</link>
	<title><![CDATA[MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly]]></title>
	<description><![CDATA[<p><span>The MetaGraph framework</span><span>&nbsp;is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as&nbsp;</span><a href="https://metagraph.ethz.ch/#query">sequence search</a><span>&nbsp;or&nbsp;</span><a href="https://metagraph.ethz.ch/#assembly">differential assembly</a><span>.</span></p>
<p><span>Searcg link&nbsp;https://metagraph.ethz.ch/search&nbsp;</span></p>
<p><span>Pre-print&nbsp;https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4&nbsp;</span></p><p>Address of the bookmark: <a href="https://metagraph.ethz.ch/" rel="nofollow">https://metagraph.ethz.ch/</a></p>]]></description>
	<dc:creator>Abhi</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/bookmarks/view/33955/crocoblast-optimized-parallel-implementation-of-local-sequence-alignment-algorithms</guid>
	<pubDate>Tue, 25 Jul 2017 05:03:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33955/crocoblast-optimized-parallel-implementation-of-local-sequence-alignment-algorithms</link>
	<title><![CDATA[CrocoBLAST: Optimized parallel implementation of local sequence alignment algorithms]]></title>
	<description><![CDATA[<p><span>Local sequence alignment is a cornerstone of bioinformatics, allowing to compare the amino-acid sequences of different proteins, or the nucleotide sequences of different pieces of DNA. The Basic Local Alignment Search Tool (BLAST) has revolutionized the field of bioinformatics, and is currently implemented in all free and commercial bioinformatics packages. However, with the advent of Next Generation Sequencing (NGS) and the development of new sequencing techniques, the utility of traditional BLAST implementations is limited. CrocoBLAST combines the accuracy and general applicability of BLAST with computational efficiency, accessibility, and user experience, so that NGS data can be analyzed efficiently even when only modest computational resources are available.</span></p>
<p>https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST</p><p>Address of the bookmark: <a href="https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST" rel="nofollow">https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST</a></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/opportunity/view/28818/senior-manager-bioinformatics-operations-at-rgcb-india</guid>
  <pubDate>Wed, 17 Aug 2016 03:19:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Manager (Bioinformatics Operations) at RGCB, India]]></title>
  <description><![CDATA[
<p>No. RGCB/ADVT/ADMN&amp;TECH/01/2016</p>

<p>August 17, 2016</p>

<p>RGCB invites applications for the following positions from Indian citizens with prescribed qualifications. Full details including job description, additional desirable qualifications, etc. are described below.</p>

<p>Code No. 1</p>

<p>Senior Manager (Bioinformatics Operations)</p>

<p>(To download application format, click here )</p>

<p>Scale of Pay</p>

<p>PB-3 Rs.15600-39100 + Grade Pay Rs.6600/-</p>

<p>Number of Positions</p>

<p>1 (General)</p>

<p>Minimum Qualifications</p>

<p>PhD in Bioinformatics, Biotechnology, Life Sciences or Computer Science applied to biological questions.<br />A minimum of 5 years documented experience in national or state government R&amp;D centers or state and central universities.<br />Track record of research funding and peer reviewed publications.<br />Proficiency using statistical analysis software or libraries such as R or Matlab.<br />Experience with a general scripting language such as Python, Ruby, or Pearl<br />Experience working with Next Generation Sequencing data<br />Proficiency with data visualization tools (Spotfire, Tableau, R, Python, etc.)<br />Experience with an object-oriented language such as Java, C++ or C# and familiarity with standard software development best practices: source code control, unit testing, in-code documentation and automated build environments.<br />Excellent listening, time management, organizational and interpersonal skills<br />Excellent communication skills, including the ability to illustrate problems and generate solutions<br />Management skills – demonstrated through the successful management of a team or large projects.<br />Broad and deep knowledge of computational methods for high-throughput sequence analysis and interpretation.<br />Extensive experience in delivering bioinformatics as a service and conducting training programs.<br />Experience of working with a production, customer-focused environment and business development projects.<br />Experience with management of funding and financial sustainability.<br />Demonstrated ability to work in a team environment and ability to lead and motivate an effective team, and also work as a good team player.<br />Good problem solver, able to logically identify solutions to technical problems.<br />Able to see the bigger picture and contribute towards strategic direction of Platforms and Pipelines teams.<br />Responsibilities</p>

<p>This position will involve cross-functional teamwork to build and develop bioinformatics tools and provide analysis for ongoing clinical trials.<br />Collaborate with biomarker scientists, clinical investigators and pipeline teams to build analytical tools.<br />Implement and evaluate new algorithms for R&amp;D.<br />Support Research and Development teams by analyzing NGS data to identify predictive response markers<br />Lead training programs in Computational Biology and Bioinformatics.</p>

<p>More at http://rgcb.res.in/positions.php</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</guid>
	<pubDate>Sat, 03 Feb 2018 04:59:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</link>
	<title><![CDATA[MUMmer4: A fast and versatile genome alignment system]]></title>
	<description><![CDATA[<p><span>MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the&nbsp;</span><span>nucmer</span><span>&nbsp;program in MUMmer4 is easily able to handle alignments of large genomes;&nbsp;</span></p><p>Address of the bookmark: <a href="https://mummer4.github.io/" rel="nofollow">https://mummer4.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28819/research-project-at-iit-madras</guid>
  <pubDate>Wed, 17 Aug 2016 03:26:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Project at IIT, Madras]]></title>
  <description><![CDATA[
<p>Two project positions are available to work on (i) molecular modeling and molecular dynamics simulations and (ii) development of bioinformatics databases and tools at Protein Bioinformatics Lab, Department of Biotechnology, IIT Madras.</p>

<p>Duration : Initially for a period of one year. Extendable based on the performance.</p>

<p>Qualification: (i) MSc in Bioinformatics, Biotechnology, Physics, Biophysics, Biochemistry,Computer Science with NET (UGC/CSIR/GATE/BINC/INSPIRE etc) qualification. (OR) (ii) M. Tech in Bioinformatics, Biotechnology</p>

<p>Additional qualification: Programming skills</p>

<p>Candidates who fulfill the requirements of IIT have the possibility to register for PhD.</p>

<p>Fellowship: Rs.25,000 and HRA.</p>

<p>Applicants are encouraged to send the CV to the coordinator by postal mail and e-mail. The deadline to receive the applications is 31st August 2016. The project coordinator has the discretion to restrict the number of candidates to be called for interview to a reasonable limit on the basis of qualifications and experience higher than the minimum prescribed in the announcement.</p>

<p>Project Co-ordinator:</p>

<p>Dr. M. Michael Gromiha <br />Department of Biotechnology <br />Indian Institute of Technology Madras <br />Chennai 600036 <br />Email: gromiha@iitm.ac.in</p>
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