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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43243?offset=70</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29654/randomness-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:17:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29654/randomness-and-probability</link>
	<title><![CDATA[Randomness and Probability]]></title>
	<description><![CDATA[<p>Randomness and Probability</p><p>Randomness and probability are two differnet concepts: probaility is a measure (according to measure theory) which measures the randomness. Randomness is the object to be measured by probability.&nbsp;For example, probability is a mapping from randomness to the real number between 0 and 1. The similar examples are that the entropy measures the uncertanity; product of length and width measures the area of rectangle etc.</p><p><strong>Please see &ldquo;A mathematical theory of ability measure&rdquo; by N. Kong ets for more examples to answer&nbsp;this question.</strong></p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29654" length="598559" type="application/pdf" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29683/method-in-comparative-genomics</guid>
	<pubDate>Wed, 09 Nov 2016 16:29:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29683/method-in-comparative-genomics</link>
	<title><![CDATA[Method in Comparative genomics !!]]></title>
	<description><![CDATA[<p>We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change.</p>
<p>We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on the genome-wide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs.</p>
<p>Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast, and will be invaluable in the study of complex genomes like that of human.</p><p>Address of the bookmark: <a href="http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf" rel="nofollow">http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29883/ra-bioinformatics-at-school-of-computational-integrative-sciences-jnu-india</guid>
  <pubDate>Fri, 18 Nov 2016 03:57:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at School of Computational &amp; Integrative Sciences, JNU, India]]></title>
  <description><![CDATA[
<p>School of Computational &amp; Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi – 110067</p>

<p>Date: Nov 11th. 2016                                                            Last Date:  Nov 25th. 2016</p>

<p>PROJECT ID: 632</p>

<p>The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh,  School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067</p>

<p>NB:For all Bioinformatics posts, preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.</p>

<p>RA / Research Associate (Metabolic engineering/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA<br />Vacancy: 1<br />Essential Qualifications: PhD in  Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/ system Biology/ Analysis of Network Biology. Published paper in the field is a must to prove the experience.<br />Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , managing the project portal, preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.</p>

<p>RA / Research Associate (Chemo-informatics/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA<br />Vacancy: 1<br />Essential Qualifications: PhD in Bioinformatics/ computational biology/ Biophysics/Computer Science. Computational and Chemical structure related experience is a necessary qualification proven by paper published and program developed. <br />Desired Skills:  Research experience in Chemical scaffold mapping, in silico Spectral analysis, Biological Database Designing &amp; Integration is required. Individual is responsible to develop methods related to metabolite identification, Testing and refining and integrate LIMS with IIIT Hyderabad and will be expected to communicate with user groups.</p>

<p>Project SRF (Bioinformatics/Programming)</p>

<p>Salary: As per DBT rules<br />Vacancy: 1<br />Essential Qualifications: Masters/B Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building &amp; maintenance ,high throughput data handling and analysis etc. For M.Sc/B.Tec, Published paper  in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must.</p>

<p>More at http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29917/gojs</guid>
	<pubDate>Tue, 22 Nov 2016 08:25:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29917/gojs</link>
	<title><![CDATA[GoJS]]></title>
	<description><![CDATA[<p><strong>GoJS</strong> is a feature-rich JavaScript library for implementing custom interactive diagrams and complex visualizations across modern web browsers and platforms. <strong>GoJS</strong> makes constructing JavaScript diagrams of complex nodes, links, and groups easy with customizable templates and layouts.</p>
<p><strong>GoJS</strong> offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.</p>
<p><strong>GoJS</strong> is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. <strong>GoJS</strong> normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. <strong>GoJS</strong> does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</p>
<p>More at&nbsp;http://gojs.net/latest/index.html</p><p>Address of the bookmark: <a href="http://gojs.net/latest/index.html" rel="nofollow">http://gojs.net/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</guid>
	<pubDate>Wed, 30 Nov 2016 04:09:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</link>
	<title><![CDATA[EXCAVATOR2tool]]></title>
	<description><![CDATA[<p><span>EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.</span><br><span>EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it&rsquo;s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavator2tool/" rel="nofollow">https://sourceforge.net/projects/excavator2tool/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30198/faculty-at-indian-institute-of-science-education-and-research-berhampur</guid>
  <pubDate>Mon, 19 Dec 2016 03:34:26 -0600</pubDate>
  <link></link>
  <title><![CDATA[Faculty at Indian Institute of Science Education and Research Berhampur]]></title>
  <description><![CDATA[
<p>Advt. No: IISERBPR/DoFA/2016/2</p>

<p>Advertisement for Faculty Positions</p>

<p>The IISER Berhampur, an Institute of national importance, established through an act of Parliament is an autonomous organization under the Ministry of HRD, Govt. of India, to promote quality education and cutting edge research in basic sciences and to provide a platform for the faculty to engage in high quality education, at undergraduate and postgraduate levels. The Institute invites applications for faculty positions at the level of Assistant Professor (C) /Assistant Professor in the following disciplines:</p>

<p>1. Biological Sciences</p>

<p>2. Chemistry</p>

<p>3. Computer Sciences</p>

<p>4. Mathematics</p>

<p>5. Physics</p>

<p>Only hard copy of application in the prescribed format, via Speed Post should be sent to the Dean, Faculty Affairs, IISER Berhampur, Industrial Training Institute (ITI) Berhampur, Engineering School Road, Berhampur - 760 010, Ganjam District, Odisha, before 1700 hrs., December 30, 2016.</p>

<p>http://www.iiserbpr.ac.in</p>

<p>More Info : http://www.iiserbpr.ac.in/vacancies/Advertisement%20for%20Faculty%20Positions%20at%20IISER%20Berhampur.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30076/sga-string-graph-assembler</guid>
	<pubDate>Thu, 08 Dec 2016 05:08:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30076/sga-string-graph-assembler</link>
	<title><![CDATA[SGA: String Graph Assembler]]></title>
	<description><![CDATA[<p><span>SGA is a de novo genome assembler based on the concept of string graphs. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads.</span></p>
<p><span>More at</span></p>
<p><span>https://github.com/jts/sga</span></p>
<p>SGA dependencies:<br> -google sparse hash library (http://code.google.com/p/google-sparsehash/)<br> -the bamtools library (https://github.com/pezmaster31/bamtools)<br> -zlib (http://www.zlib.net/)<br> -(optional but suggested) the jemalloc memory allocator (http://www.canonware.com/jemalloc/download.html)</p><p>Address of the bookmark: <a href="https://github.com/jts/sga" rel="nofollow">https://github.com/jts/sga</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial</guid>
	<pubDate>Fri, 09 Dec 2016 04:19:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial</link>
	<title><![CDATA[Velvet tutorial]]></title>
	<description><![CDATA[<p><span>The objective of this activity is to help you understand how to run&nbsp;</span><a href="http://evomics.org/resources/software/genomics-software/assembly/velvet/" title="Velvet">Velvet</a><span>&nbsp;in general, how to accurately estimate the insert size of a paired-end library through the use of&nbsp;</span><a href="http://evomics.org/resources/software/genomics-software/assembly/bowtie/" title="Bowtie">Bowtie</a><span>, the primary parameters of velvet, and the process involved in producing a&nbsp;</span><em>de novo</em><span>&nbsp;assembly from Illumina reads.</span></p>
<p>http://evomics.org/learning/assembly-and-alignment/velvet/</p><p>Address of the bookmark: <a href="http://evomics.org/learning/assembly-and-alignment/velvet/" rel="nofollow">http://evomics.org/learning/assembly-and-alignment/velvet/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30124/understanding-greedy-algorithms</guid>
	<pubDate>Mon, 12 Dec 2016 04:37:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30124/understanding-greedy-algorithms</link>
	<title><![CDATA[Understanding Greedy Algorithms]]></title>
	<description><![CDATA[<p>Learning greedy algo for biologist.&nbsp;</p>
<p>https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/</p>
<p>This webpage is also useful for the same:</p>
<p>http://learninglover.com/examples.php?id=59</p>
<p>http://www.cs.rpi.edu/~magdon/ps/conference/super_biokdd.pdf</p>
<p>https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/lecture-slides/MIT7_91JS14_Lecture6.pdf</p>
<p>http://schatzlab.cshl.edu/teaching/AssemblyClass/01.%20Assembly%20Intro.pdf</p>
<p>http://lsl.sinica.edu.tw/Services/Class/files/20150612449.pdf</p>
<p>http://www.cs.jhu.edu/~langmea/resources/lecture_notes/assembly_scs.pdf</p>
<p>https://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-43.pdf</p><p>Address of the bookmark: <a href="https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/" rel="nofollow">https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30149/mypro-a-seamless-pipeline-for-automated-prokaryotic-genome-assembly-and-annotation</guid>
	<pubDate>Thu, 15 Dec 2016 05:47:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30149/mypro-a-seamless-pipeline-for-automated-prokaryotic-genome-assembly-and-annotation</link>
	<title><![CDATA[MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation]]></title>
	<description><![CDATA[<p>MyPro is an improved genomics software pipeline for prokaryotic genomes. MyPro is user-friendly and requires minimal programming skills. High-quality prokaryotic genome assembly and annotation can be obtained with ease. It performed better than de novo assemblers and contig integration software. Produces more contiguous assemblies, higher N50 values and lower number of contigs.</p>
<p>More at https://sourceforge.net/projects/sb2nhri/files/MyPro/</p><p>Address of the bookmark: <a href="http://www.sciencedirect.com/science/article/pii/S0167701215001207" rel="nofollow">http://www.sciencedirect.com/science/article/pii/S0167701215001207</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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