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	<title><![CDATA[BOL: All Files]]></title>
	<link>https://bioinformaticsonline.com/file/search?offset=60</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/1970/indias-own-first-drug-from-biocon</guid>
	<pubDate>Sun, 11 Aug 2013 16:05:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/1970/indias-own-first-drug-from-biocon</link>
	<title><![CDATA[India&#039;s own first drug - from Biocon.]]></title>
	<description><![CDATA[<p><span><span>Psoriasis is immune-mediated disease that effects the skin. the Disease on an average affects about 10-20 million Indians and it attacks the immune system of human beings. In generally occurs, when the immune system mistakes a normal skin cell for a pathogen, and sends out faulty signals that cause overproduction of new skin cells. <a href="http://en.wikipedia.org/wiki/Psoriasis">More at &gt;&gt;</a><br /></span></span></p><p><span><span>Biocon, India's largest publicly-held biotechnology firm, launched its second novel 'lab-to-market' molecule,<strong> Alzumab</strong>, to treat chronic plaque <strong>psoriasis</strong> at a cost 50 per cent lower than the existing one. </span></span></p><p><span><span><span><span>Biocon is bringing Alzumab (a biologic) in the form of a vial after working on it for nearly a decade. The work had initially started in a joint effort with the Center of Molecular Immunology, Havana, but Biocon took control of the programme soon after and also bought out its partner a few years ago. Biocon tell to the media that genotypic played a critical role in functional studies and clinical trial Genomics. </span></span><br /><br />The Biocon drug, at around&nbsp;₹ 7,500 a vial, will cost half as much as the currently available drugs - from Pfizer and J&amp;J - to treat psoriasis, a skin disease that causes rough red areas where the skin comes off in small pieces. A patient is usually prescribed to consume more than 40 vials in a 24-week course.<br /><br /></span></span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/1970" length="90484" type="image/jpeg" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/991/master-thesis-trans-membrane-topology-prediction-through-markov-based-decoders</guid>
	<pubDate>Wed, 17 Jul 2013 16:16:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/991/master-thesis-trans-membrane-topology-prediction-through-markov-based-decoders</link>
	<title><![CDATA[Master Thesis: Trans-membrane topology prediction through Markov based decoders]]></title>
	<description><![CDATA[<p dir="ltr"><span>Abstract:</span></p><p dir="ltr"><span></span><span>Background/Motivation: </span></p><p dir="ltr"><span>The dearth of structural information on alpha helical membrane protein (MPs) has hindered thus far the development of reliable knowledge &ndash;based potentials that can be used for automatic prediction of trans-membrane (TM) protein structure. While algorithm for identification of TM segments is available, modelling of the domains of alpha helical MPs involves assembling the segments into a bundle. This requires the correct assignment of the buried and lipid-exposed faces of the TM domains.</span><span>&nbsp;</span></p><p dir="ltr"><span>Results: </span><span><span><span>In a cross validated test on single sequences, our trans-membrane MM, correctly predicts the entire topology for 77% of the sequences in a standard dataset of 86 proteins with supervised topology. These results compare favorably with existing methods.</span></span></span><span>&nbsp;</span></p><p dir="ltr"><span><strong>Source Code</strong>: Matlab</span></p><p dir="ltr"><span></span><span>Conclusion/Implementation</span><span><span><span>: Here discriminant data mining approach was used to predict the location and orientation of alpha helices in membrane-spanning proteins. It is based on a first order Markov model (MM) with an architecture that corresponds closely to the biological systems. The model is enriched with three types of states for the loop on the cytoplasmic side (outer loop), loop for the non-cytoplasmic side (inner side), and trans-membrane part. The closed association between the biological and Markov states allows us to infer which part of the model architecture are important to capture the information which encodes the membrane topology, and gain a better understanding of the mechanism and constraints involved. Predictor Model was established by various &nbsp;Markov decoder , and assignment of the membrane helix boundaries was apparent.</span></span></span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/989/bioinformatics-approach-to-boar-taint</guid>
	<pubDate>Wed, 17 Jul 2013 15:50:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/989/bioinformatics-approach-to-boar-taint</link>
	<title><![CDATA[Bioinformatics approach to Boar Taint]]></title>
	<description><![CDATA[<p><span>Meat products obtained from intact male pigs often produce offensive smell or odour which is recognized as a complex genetic trait called boar taint.Androstenone and Skatole&nbsp;in the fat primarily cause boar taint. Metabolism of androstenone and sex steroids share a common pathway which makes removal of boar taint a very challenging task. Castration is a traditional solution to remove boar taint but it also results in bad quality of meat due to low level of steroids which is objectionable to many consumers. Detected functional variant(s) underlying boar taint compounds can be used as genetic markers in selection of male pigs with reduced boar taint levels. Resequencing of a total of 47 samples belong to Norwegian Landrace (NL) and Duroc (D) pigs with varied boar taint levels were done in Illumina HiSeq2000 to &gt;10X average coverage. Short reads generated from these samples mapped to&nbsp;<em>Sus Scrofa</em>&nbsp;version 10.2 reference assembly using Bowtie2. Alignment file then used for calling SNPs and InDels inside previousy identified QTL regions on SSC5,13, and 7 with the aid of FreeBayes , a variant caller tool. A final list of SNPs was prepared after filtering SNPs on the basis of SNP quality, coverage of SNP allele, functional and structural annotation, and repeats, etc. Selected SNPs will be genotyped in sample population for validation and then used for constructing SNPs haplotypes in close linkage disequilibrium with QTLs and fine mapping of QTLs through association mapping of genotyped SNPs.</span><span>&nbsp;</span></p><p><span>&nbsp;</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/88/regular-expression-cheat-sheet</guid>
	<pubDate>Tue, 09 Jul 2013 17:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/88/regular-expression-cheat-sheet</link>
	<title><![CDATA[Regular Expression Cheat Sheet]]></title>
	<description><![CDATA[<p><span>The Regular Expression are the sole of Perl language, and for bioinformatician it is just a magical stick to resolve gingatic string data. We did not find any good and user friendly regular expression cheat sheet, hence write our own cheat sheet.&nbsp;</span><span>The Regular Expressions Cheat Sheet, a quick reference guide for regular expressions, including symbols, ranges, grouping, assertions and some sample patterns to get you started.</span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/88" length="14944" type="application/pdf" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/87/linux-cheat-sheet</guid>
	<pubDate>Tue, 09 Jul 2013 17:30:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/87/linux-cheat-sheet</link>
	<title><![CDATA[Linux Cheat Sheet]]></title>
	<description><![CDATA[<p><span>In an attempt to find a good Linux reference for bioinformatician and BOL readers, I was unsuccessful at finding a decent one on the Internet. So, we decided to make a cheat sheet for biological programmers.</span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/87" length="81260" type="application/pdf" />
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