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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33955?offset=20</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4314/postdocs-positions-in-computer-science-in-helsinki-finland</guid>
  <pubDate>Fri, 06 Sep 2013 10:11:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[PostDocs positions in computer science in HELSINKI, FINLAND]]></title>
  <description><![CDATA[
<p>Several university departments in the Helsinki region, Finland, are looking for postdoctoral researchers in the field of computer science and information technology. Jobs are available at:<br />·       Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki, http://www.hiit.fi<br />·       Department of Computer Science, University of Helsinki, http://www.cs.helsinki.fi<br />·       Department of Information and Computer Science, Aalto University, http://ics.aalto.fi<br />·       Department of Computer Science and Engineering, Aalto University, http://cse.aalto.fi<br />·       Department of Mathematics and Statistics, University of Helsinki, http://mathstat.helsinki.fi/english/<br /> <br />Why Helsinki?<br />The collaborating Aalto University and University of Helsinki form a leading hub of computer science and modelling, including Machine learning, Data mining, Algorithms, Computational Logic, Cloud computing, Distributed computing, Human-centric ubiquitous ICT, Bioinformatics, etc.<br />Helsinki region is a safe, pleasant and attractive place to live in, with well-functioning services such as public transport etc. Finland has a comprehensive social security and health care system, including exceptionally good parental leaves, and children's day care services.<br /> <br />Positions are offered in:<br />Algorithm engineering (String Algorithms group)<br />Algorithmic bioinformatics (Genome-Scale Algorithmics group)<br />Automated reasoning and search, especially propositional logic (Computational Logic group)<br />Computational astrophysics and/or data analysis (Computational Methods and Data Analysis for Astrophysics group)<br />Computational biology and statistical methods in bioinformatics (Computational Systems Biology group)<br />Computational creativity and data mining (Discovery group)<br />Dynamic and large-scale networked systems (Data Communications Software group)<br />Intelligent multimodal information access (Content-Based Image and Information Retrieval Group)<br />Machine learning and neuroscience (Statistical Machine Learning group)<br />Machine learning for structured data (Kernel Machines, Pattern Analysis and Computational Biology group)<br />Machine learning methods for infectious disease epidemiology (Bayesian Statistics Group)<br />Probabilistic modeling and machine learning (Complex Systems Computation group)<br />Statistical machine learning (Statistical Machine Learning group)<br />Analysing ubiquitous sensor data (HIIT-Wide Focus Area)<br />Interactive visualization (HIIT-Wide Focus Area)<br />Affective computing and BCI (HIIT-Wide Focus Area)<br />Intelligent user interfaces and/or recommender systems (HIIT-Wide Focus Area)<br />Information retrieval and HCI (HIIT-Wide Focus Area)<br />Machine learning and data analysis, especially information retrieval, HCI, text and context data (HIIT-Wide Focus Area)<br />Probabilistic modeling and data analysis for bioinformatics (HIIT-Wide Focus Area)</p>

<p>More at http://www.hiit.fi/postdoc-call-2013</p>
]]></description>
</item>

<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/bookmarks/view/19631/rosalind-bioinformatics-problems</guid>
	<pubDate>Thu, 18 Dec 2014 10:32:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems</link>
	<title><![CDATA[Rosalind Bioinformatics problems !!!]]></title>
	<description><![CDATA[<p>Rosalind is a platform for learning bioinformatics and programming through problem solving. <a href="http://rosalind.info/problems/list-view/">Take a tour</a> to get the hang of how Rosalind works.</p>
<p>http://rosalind.info/problems/list-view/</p><p>Address of the bookmark: <a href="http://rosalind.info/problems/list-view/" rel="nofollow">http://rosalind.info/problems/list-view/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38702/quick-tour-of-genetic-algorithms</guid>
	<pubDate>Thu, 17 Jan 2019 03:42:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38702/quick-tour-of-genetic-algorithms</link>
	<title><![CDATA[Quick tour of Genetic Algorithms !]]></title>
	<description><![CDATA[<p><span>The R package&nbsp;</span><strong>GA</strong><span>&nbsp;provides a collection of general purpose functions for optimization using genetic algorithms. The package includes a flexible set of tools for implementing genetic algorithms search in both the continuous and discrete case, whether constrained or not. Users can easily define their own objective function depending on the problem at hand.&nbsp;</span></p>
<p><span>https://cran.r-project.org/web/packages/GA/vignettes/GA.html</span></p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/GA/vignettes/GA.html" rel="nofollow">https://cran.r-project.org/web/packages/GA/vignettes/GA.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23498/algorithms-for-dna-sequencing-course-offered-each-month</guid>
	<pubDate>Sun, 26 Jul 2015 01:57:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23498/algorithms-for-dna-sequencing-course-offered-each-month</link>
	<title><![CDATA[Algorithms for DNA Sequencing (course offered each month)]]></title>
	<description><![CDATA[<p>"<span>We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets."</span></p>
<p><span>Source :&nbsp;https://www.coursera.org/course/ads1</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.coursera.org/course/ads1" rel="nofollow">https://www.coursera.org/course/ads1</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30555/yaha</guid>
	<pubDate>Fri, 20 Jan 2017 05:38:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30555/yaha</link>
	<title><![CDATA[YAHA]]></title>
	<description><![CDATA[<p>YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.</p>
<p><strong>Availability:</strong> YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from <a href="http://faculty.virginia.edu/irahall/YAHA" target="pmc_ext">http://faculty.virginia.edu/irahall/YAHA</a>.</p>
<p><strong>Contact:</strong></p>
<p>http://genome.wustl.edu/people/groups/detail/hall-lab/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</guid>
	<pubDate>Fri, 17 Feb 2017 08:38:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</link>
	<title><![CDATA[GenomeComp]]></title>
	<description><![CDATA[<p>GenomeComp is a tool for summarizing, parsing and visualizing the genome wide sequence comparison results derived from voluminous BLAST textual output, so as to locate the rearrangements, insertions or deletions of genome segments between species or strains.<br><br>It can be easily used to compare, parsing and visualize large genomic sequences, especially closely related genomes such as inter-species or inter-strains. In addition, it can also show other sequence features like repeat sequence distributions in one whole-genome DNA sequence by comparing the genome to itself.<br><br>It is a stand-alone graphical user interface (GUI) program which runs on Linux, Unix, Mac OS X (tested on version 10.2.4 only) and Microsoft Windows platforms and is written in Perl/Tk.</p><p>Address of the bookmark: <a href="http://www.mgc.ac.cn/GenomeComp/" rel="nofollow">http://www.mgc.ac.cn/GenomeComp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</guid>
	<pubDate>Wed, 22 Feb 2017 05:14:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</link>
	<title><![CDATA[Cgaln]]></title>
	<description><![CDATA[<p>Cgaln (Coarse grained alignment) is a program designed to align a pair of whole genomic sequences of not only bacteria but also entire chromosomes of vertebrates on a nominal desktop computer. Cgaln performs an alignment job in two steps, at the block level and then at the nucleotide level. The former "coarse-grained" alignment can explore genomic rearrangements and reduce the regions to be analyzed in the next step. The latter is devoted to detailed alignment within the limited regions found in the first stage. The output of Cgaln is 'glocal' in the sense that rearrangements are taken into consideration while each alignable region is extended as long as possible. Thus, Cgaln is not only fast and memory-efficient, but also can filter noisy outputs without missing the most important homologous segment pairs.</p>
<p>http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</p><p>Address of the bookmark: <a href="http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/" rel="nofollow">http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</guid>
	<pubDate>Fri, 12 May 2017 10:50:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</link>
	<title><![CDATA[A Post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs]]></title>
	<description><![CDATA[<p>PAGIT addresses the need for software to generate high quality draft genomes. It is based on a series of programs that we developed:</p>
<p><a href="https://sourceforge.net/projects/abacas/files/">ABACAS</a>, that is able to contiguate contigs from a de novo assembly against a closely related reference.</p>
<p><a href="https://sourceforge.net/projects/image2/files/">IMAGE</a>, an iterative approach for closing gaps in assembled genomes using mate pair information. It is able to close gaps left open by the assembler in a draft genome, even when using the same data sets as used by the original assembler.</p>
<p><a href="http://icorn.sourceforge.net/">iCORN</a>, that enables errors in the consensus sequence to be corrected by iteratively mapping reads to the current assembly. An improved version, especially correction Pacfic Bioscience assemblies (PacBio) can be found&nbsp;<a href="ftp://ftp.sanger.ac.uk/pub4/resources/software/pagit/ICORN2/icorn2.V0.95.tgz">here</a>.</p>
<p><a href="https://ratt.svn.sourceforge.net/svnroot/ratt">RATT</a>, a tool to transfer the annotation from a reference genome, or an earlier assembly, onto the latest assembly.</p>
<p>PAGIT bundles these software and makes them more accessible for users.</p><p>Address of the bookmark: <a href="http://www.sanger.ac.uk/science/tools/pagit" rel="nofollow">http://www.sanger.ac.uk/science/tools/pagit</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33006/avid-a-global-alignment-program</guid>
	<pubDate>Wed, 24 May 2017 05:19:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33006/avid-a-global-alignment-program</link>
	<title><![CDATA[AVID: A Global Alignment Program]]></title>
	<description><![CDATA[<p>A new global alignment method called AVID. The method is designed to be fast, memory efficient, and practical for sequence alignments of large genomic regions up to megabases long. We present numerous applications of the method, ranging from the comparison of assemblies to alignment of large syntenic genomic regions and whole genome human/mouse alignments. We have also performed a quantitative comparison of AVID with other popular alignment tools. To this end, we have established a format for the representation of alignments and methods for their comparison. These formats and methods should be useful for future studies. The tools we have developed for the alignment comparisons, as well as the AVID program, are publicly available. See Web Site References section for AVID Web address and Web addresses for other programs discussed in this paper.</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>

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