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	<link>https://bioinformaticsonline.com/related/34916?offset=850</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5220/paolo-ruggerone-lab</guid>
  <pubDate>Tue, 01 Oct 2013 14:15:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[Paolo Ruggerone Lab]]></title>
  <description><![CDATA[
<p>Efflux pumps (RND family)</p>

<p>Functioning of efflux systems in Gram-negative bacteria<br />Determinants of the compound-efflux system interactions<br />Action of inhibitors on efflux systems<br />Structural and dynamical features of the efflux systems</p>

<p>TatA<br />Assembly of the TatA system<br />Study of the dynamical features of the charge zipper</p>

<p>Methods<br />Setup of a kinetic Monte Carlo (KMC) scheme to study the flux of antibiotics through porins and efflux systems<br />Setup of protocol to integrate MD results in a ligand-based approach</p>

<p>Viral inhibitors<br />Interactions of selected compounds with RNA-dependent RNA polymerases (RdRps) of HCV and BVDV<br />Assessment of the role of mutations in RdRps<br />Antimicrobial peptides</p>

<p>Interactions of antimicrobial peptides with membranes: structure and dynamics<br />Interactions between antimicrobial peptides in the presence of different membranes<br />Protein-protein interactions<br />Effects of mutations</p>

<p>Lab Page<br />http://www.dsf.unica.it/~paolo/Site/Home.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5310/bergman-lab</guid>
  <pubDate>Thu, 03 Oct 2013 17:20:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bergman Lab]]></title>
  <description><![CDATA[
<p>Broad area of research:</p>

<p>Genome Annotation and Functional Genomics</p>

<p>Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences.  Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.</p>

<p>Genome and Molecular Evolution<br />Text and Data Mining</p>

<p>More @ http://bergmanlab.smith.man.ac.uk/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</guid>
	<pubDate>Fri, 08 Jun 2018 10:47:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</link>
	<title><![CDATA[HALC: High throughput algorithm for long read error correction]]></title>
	<description><![CDATA[HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach)

HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.<p>Address of the bookmark: <a href="https://github.com/lanl001/halc" rel="nofollow">https://github.com/lanl001/halc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5663/network-analysis-indian-statistical-institute</guid>
  <pubDate>Wed, 16 Oct 2013 08:06:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Network Analysis @ Indian Statistical Institute]]></title>
  <description><![CDATA[
<p>Indian Statistical Institute Kolkata invites applications for the following posts</p>

<p>2013 Oct Advertisement from Indian Statistical Institute</p>

<p>Post: Network Analysis</p>

<p>No. of Positions:  01</p>

<p>Educational Qualifications:</p>

<p>Candidate should have passed BE/B.Tech Or Equivalent in Computer Science / Electrical Engineering / Electronics / Information Technology / Bioinformatics / Biotechnology with throughout first Class<br />Experience:</p>

<p>(details of experience required)<br />Pay Scale: INR Rs.16000-20000/-P.M.</p>

<p>Walk-In-Interview : 22 Oct 2013 at 10:30 AM</p>

<p>Download Official Notification:<br />http://www.isical.ac.in/JobApplicationFiles/MIU_0310201311433700.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9673/now-time-is-come-to-revolutionize-amino-acid-sequencing-by-nanopore-technology</guid>
	<pubDate>Mon, 07 Apr 2014 08:01:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9673/now-time-is-come-to-revolutionize-amino-acid-sequencing-by-nanopore-technology</link>
	<title><![CDATA[Now time is come to revolutionize amino acid sequencing by Nanopore technology]]></title>
	<description><![CDATA[<p>Amino acid sequencing by Nanopore recognition tunneling method</p><p>Address of the bookmark: <a href="http://www.eurekalert.org/multimedia/pub/71198.php" rel="nofollow">http://www.eurekalert.org/multimedia/pub/71198.php</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5748/troyanskaya-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:57:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya  Lab]]></title>
  <description><![CDATA[
<p>In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.</p>

<p>Research Interest<br />Genomic Data Integration</p>

<p>Microarray Analysis</p>

<p>Gene and Protein Function Prediction</p>

<p>Detection and Analysis of Chromosomal Abnormalities and Functional Evolution</p>

<p>Integration of Computation and Experiments</p>

<p>Identification of Biological Networks and Pathways</p>

<p>Evaluation and Validation of Computational Predictions</p>

<p>Scalable Visualization-Based Data Analysis</p>

<p>More @ http://reducio.princeton.edu/cm/<br />PI page @ http://reducio.princeton.edu/cm/ogt</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35059/lrcstats-long-read-correction-statistics</guid>
	<pubDate>Fri, 05 Jan 2018 04:04:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35059/lrcstats-long-read-correction-statistics</link>
	<title><![CDATA[LRCstats: Long Read Correction Statistics]]></title>
	<description><![CDATA[<p>LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.</p>
<p>Of course, some long read correction algorithms are better than others, and developers of long read correction algorithms will wish to compare their algorithm with others currently available. LRCstats benchmarks long read correction algorithms using long reads produced by simulators (such as SimLoRD or PBSim) where the two-way alignments between the uncorrected long reads (uLR) and the corresponding sequences in the reference genome (Ref) are given in some sort of alignment file and then aligning the corrected long reads (cLR) to the Ref-uLR two-way alignments to create three-way alignments using a dynamic programming algorithm. Statistics on these three-way alignments are then collected, such as the overall error rates of the corrected long reads.</p>
<p>https://www.healthcare.uiowa.edu/labs/au/LSC/</p><p>Address of the bookmark: <a href="https://github.com/cchauve/lrcstats" rel="nofollow">https://github.com/cchauve/lrcstats</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5957/assistant-professor-in-molecular-synthesis-for-drug-discovery-and-development-cbmr-lucknow</guid>
  <pubDate>Wed, 30 Oct 2013 06:42:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor in Molecular Synthesis for Drug Discovery and Development @ CBMR, Lucknow]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT FOR FACULTY POSITIONS AT CENTRE OF BIOMEDICAL RESEARCH (CBMR), LUCKNOW</p>

<p>Details of the Positions and Pay Structure:</p>

<p>03 Posts for Assistant Professor in Molecular Synthesis for Drug Discovery and Development</p>

<p>Essential Qualifications and Requirements:</p>

<p>1. PhD in Synthetic Organic Chemistry/Medicinal Chemistry with research publications in high quality international journals and first class grade at the preceding degree from recognised University/Institute in India or abroad with consistently good academic record.<br />2. Three Yrs of Post-doctoral experience in relevant area.<br />3. Below 35 Yrs of age at the time of application</p>

<p>Desirable Experience: Candidates having strong research background in organic synthesis, total synthesis of structurally complex and medicinally important natural products/drugs related to cancer, neurodegenerative diseases (neurotropically active molecules for Alzheimer's, Parkinson’s, dementia etc) and infectious diseases such as malaria, TB etc. will be preferred.</p>

<p>Interested candidates may apply with:</p>

<p>1. Filled up Application Form (download from CBMR Website: http://www.cbmr.res.in) along with the Cover Letter, Curriculum Vitae including academic record (Bachelor degree onwards), awards, honours, list of Publications and reprints of 5 best publications.<br />2. Proposed research plan (max 3-4 pages).<br />3. Names and address (with valid e-mail and Phone number) of at least 3 academic referees.<br />4. Online Payment Receipt with transaction reference no. of Rs. 1000/- (USD 100 or equivalent foreign currency) on following details.<br />Account Number: 30054847814 Name: Director, Centre of Biomedical Research<br />Bank: STATE BANK OF INDIA, SGPGI Campus Branch, LUCKNOW</p>

<p>IFSC Code: SBIN0007789<br />MICR No: 22602034</p>

<p>Applications can be sent by registered/speed post or by e-mail to the following address:</p>

<p>The Director,<br />Centre of Biomedical Research (CBMR),<br />Sanjay Gandhi PGI Campus,<br />Raebareli Road, Lucknow-226014<br />e-mail: cbmr.admin@cbmr.res.in,<br />gp.pandey@cbmr.res.in</p>

<p>More Info:</p>

<p>http://www.cbmr.res.in/career/Advertisement%20for%20the%20post%20of%20Professors%20and%20Assistant%20Professors.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</guid>
	<pubDate>Fri, 10 Aug 2018 13:29:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</link>
	<title><![CDATA[FMLRC: a long-read error correction tool using the multi-string Burrows Wheeler Transform]]></title>
	<description><![CDATA[<p><span>FMLRC, or FM-index Long Read Corrector, is a tool for performing hybrid correction of long read sequencing using the BWT and FM-index of short-read sequencing data. Given a BWT of the short-read sequencing data, FMLRC will build an FM-index and use that as an implicit de Bruijn graph. Each long read is then corrected independently by identifying low frequency k-mers in the long read and replacing them with the closest matching high frequency k-mers in the implicit de Bruijn graph. In contrast to other de Bruijn graph based implementations, FMLRC is not restricted to a particular k-mer size and instead uses a two pass method with both a short "k-mer" and a longer "K-mer". This allows FMLRC to correct through low complexity regions that are computational difficult for short k-mers.</span></p><p>Address of the bookmark: <a href="https://github.com/holtjma/fmlrc" rel="nofollow">https://github.com/holtjma/fmlrc</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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