<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42985?offset=30</link>
	<atom:link href="https://bioinformaticsonline.com/related/42985?offset=30" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/19648/mit-computational-biology-group</guid>
  <pubDate>Thu, 18 Dec 2014 14:47:01 -0600</pubDate>
  <link></link>
  <title><![CDATA[MIT Computational Biology Group]]></title>
  <description><![CDATA[
<p>My research group consists primarily of computer science graduate students and postdocs with expertise in algorithms, statistical inferences and machine learning, and sharing a passion for understanding fundamental biological problems.</p>

<p>We work in a highly interdisciplinary environment at the interface of Computer Science and Biology. Since its inception, our lab has eagerly engaged in collaborative research partnerships with biological and experimental collaborators, facilitated by our affiliation with the Broad Institute and the Computational and Systems Biology initiative (CSBi) at MIT, our participation in the Epigenome Roadmap, ENCODE, and modENCODE consortia, and by several other ongoing collaborations at MIT, Harvard, and the Harvard Medical School affiliated hospitals.</p>

<p>http://compbio.mit.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22393/narcis-fernandez-fuentes-lab</guid>
  <pubDate>Mon, 25 May 2015 07:30:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[Narcis Fernandez-Fuentes Lab]]></title>
  <description><![CDATA[
<p>Welcome to our web-site compiling all the research-related activities of the group. Our research interests relate to a number of areas within Bioinformatics. We have a long-standing interest in protein structure prediction and structure-to-function relationships. We work in the study of biomolecular interactions, modeling of protein complexes, the study and characterization of protein-protein interactions, peptide design, modeling of genetic variation, structure-based protein design and different aspects of Plant Bioinformatics. Take a look at the our databases and servers and the list of publications for more information.</p>

<p>More at http://www.bioinsilico.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22414/x-shirley-liu-lab</guid>
  <pubDate>Tue, 26 May 2015 17:28:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[X. Shirley Liu Lab]]></title>
  <description><![CDATA[
<p>The research in our laboratories are focused on the following three areas: </p>

<p>Bioinformatics<br />Cancer<br />Epigenetics</p>

<p>More at http://liulab.dfci.harvard.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23209/bisr-jaipur</guid>
  <pubDate>Tue, 07 Jul 2015 23:12:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[BISR Jaipur]]></title>
  <description><![CDATA[
<p>The Bioinformatics Centre at BISR has created an infrastructure for providing facilities to the users working in the field of Biological Sciences. The users of Rajasthan, Jaipur in particular, are using facilities available at the Bioinformatics Centre extensively. The centre has leased line Internet connection as well latest Bioinformatics software for sequence and structure analysis. The centre provides the following services:</p>

<p>    Bioinformatics supports to researchers<br />    Customized training in Bioinformatics for researchers and faculty members<br />    Support in Installing, implementing and maintaining software on computer.<br />    Create awareness for taking preventive measure against data security<br />    Organize workshops on thrust ares of Bioinformatics<br />    Research Training to students of Biotechnology and Bioinformatics </p>

<p>More at http://bioinfo.bisr.res.in/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26322/liftover</guid>
	<pubDate>Mon, 08 Feb 2016 15:45:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26322/liftover</link>
	<title><![CDATA[liftover]]></title>
	<description><![CDATA[<p><span>Convenient conversions between genome assemblie.&nbsp;The liftover package makes it easy to remap genomic coordinates to a different genome assembly. </span></p>
<p><span>More at https://github.com/aaronwolen/liftover<br></span></p>
<p><span>https://www.bioconductor.org/help/workflows/liftOver/</span></p><p>Address of the bookmark: <a href="https://github.com/aaronwolen/liftover" rel="nofollow">https://github.com/aaronwolen/liftover</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</guid>
	<pubDate>Fri, 13 May 2016 05:25:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</link>
	<title><![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]></title>
	<description><![CDATA[<p>Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.<br> <br> Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs. <br> <br> You can find the manual <a href="http://satsuma.sourceforge.net/manual.html">here</a>.<br> Download the latest source code from <a href="https://sourceforge.net/projects/satsuma/">here.</a><br> Stable versions can also be downloaded from the <a href="https://www.broadinstitute.org/science/programs/genome-biology/spines">Broad Institute's</a> web site.<br> <br> An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is <a href="http://satsuma.sourceforge.net/faq.html">here</a>.<br> <br> If you use Satsuma in your research, please cite:<br> <a href="http://bioinformatics.oxfordjournals.org/content/26/9/1145.long">Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alf&ouml;ldi, J., Di Palma, F., &amp; Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51</a>.</p>
<p><strong>Tutorial at http://evomics.org/learning/genomics/satsuma/</strong></p><p>Address of the bookmark: <a href="http://satsuma.sourceforge.net/" rel="nofollow">http://satsuma.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab</guid>
	<pubDate>Fri, 30 Jun 2017 08:48:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab</link>
	<title><![CDATA[DIYA: a bacterial annotation pipeline for any genomics lab]]></title>
	<description><![CDATA[<p><span>DIY Genomics is an open source bioinformatics consortium intended to bring a collection of tools and libraries into the hands of small scale genomics labs for the process of sequence assembly and annotation. Projects include DIYA, MGAP, CRISPR, and DIYGV</span></p>
<p><span>http://gmod.org/wiki/Diya</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/diyg/" rel="nofollow">https://sourceforge.net/projects/diyg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</guid>
	<pubDate>Mon, 04 Dec 2017 07:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</link>
	<title><![CDATA[MetaSim A Sequencing Simulator for Genomics and Metagenomics.]]></title>
	<description><![CDATA[<p><span>Our software can be used to&nbsp;</span><strong>generate collections of synthetic reads</strong><span>&nbsp;that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to&nbsp;</span><strong>design a metagenome</strong><span>&nbsp;by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a&nbsp;</span><strong>simulation of a number of different sequencing technologies</strong><span>. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ab.inf.uni-tuebingen.de/software/metasim/" rel="nofollow">http://ab.inf.uni-tuebingen.de/software/metasim/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/36647/bioinformatics-jobs-at-nibmg</guid>
  <pubDate>Wed, 16 May 2018 02:57:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics jobs at NIBMG]]></title>
  <description><![CDATA[
<p>NIBMG are looking for bright and motivated people in our big projects on cutting edge biomedical genomics research</p>

<p>http://www.nibmg.ac.in/academic/SyMeC-ICGC/SyMeC%20&amp;%20ICGC_May%202018.pdf</p>

<p>http://www.nibmg.ac.in/academic/plp/15_05_2018/AdvertisementMay2018.pdf</p>
]]></description>
</item>

</channel>
</rss>