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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30971?offset=460</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37496/gsearch-a-fast-and-flexible-general-search-tool-for-whole-genome-sequencing</guid>
	<pubDate>Mon, 06 Aug 2018 17:19:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37496/gsearch-a-fast-and-flexible-general-search-tool-for-whole-genome-sequencing</link>
	<title><![CDATA[gSearch: a fast and flexible general search tool for whole-genome sequencing]]></title>
	<description><![CDATA[<p><span>gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ml.ssu.ac.kr/gSearch/index.html" rel="nofollow">http://ml.ssu.ac.kr/gSearch/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</guid>
	<pubDate>Wed, 23 Jul 2014 07:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</link>
	<title><![CDATA[COSMOS, our workflow management system for NGS data]]></title>
	<description><![CDATA[<p><strong>COSMOS</strong>, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/06/29/bioinformatics.btu385.abstract">Advance Access</a> in <em>Bioinformatics</em> (<a href="http://scholar.harvard.edu/lancaster/publications/cosmos-python-library-massively-parallel-workflows">Gafni et al. 2014</a>).&nbsp; It is also available for download for non-commercial academic and research purposes at:</p>
<p><strong>&nbsp;<a href="http://cosmos.hms.harvard.edu/">http://cosmos.hms.harvard.edu/</a></strong>.</p><p>Address of the bookmark: <a href="https://cosmos.hms.harvard.edu/" rel="nofollow">https://cosmos.hms.harvard.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12995/national-center-for-bioinformatics-ncb</guid>
  <pubDate>Wed, 23 Jul 2014 14:10:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[National Center for Bioinformatics (NCB)]]></title>
  <description><![CDATA[
<p>NCB is offering M.Phil and Ph.D programs in the area of Bioinformatics. The major goal of NCB is to promote quality training and research in the area of Bioinformatics. Bioinformatics originated as a cross-disciplinary field as the need for computational sections to research problem raised in biomedicine. </p>

<p>More at http://ncb.qau.edu.pk/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Thu, 04 Oct 2018 16:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p>This is a tool for detecting structural variations using soft-clipping information From&nbsp;<a href="http://samtools.sourceforge.net/SAM1.pdf">SAM</a>&nbsp;files.</p>
<p>https://github.com/shinout/clipcrop</p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling</guid>
	<pubDate>Fri, 26 Jul 2019 01:11:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling</link>
	<title><![CDATA[Patterns: a modeling tool dedicated to biological network modeling]]></title>
	<description><![CDATA[<p>It is designed to work with <strong>patterned data</strong>. Famous examples of problems related to patterned data are:</p>
<ul>
<li>recovering <strong>signals</strong> in networks after a <strong>stimulation</strong> (cascade network reverse engineering),</li>
<li>analysing <strong>periodic signals</strong>.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/fbertran/Patterns" rel="nofollow">https://github.com/fbertran/Patterns</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</guid>
	<pubDate>Sun, 16 Feb 2020 08:47:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</link>
	<title><![CDATA[iSeqQC: a tool for expression-based quality control in RNA sequencing]]></title>
	<description><![CDATA[<p><span>iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers.</span></p>
<p><a href="http://cancerwebpa.jefferson.edu/iSeqQC/">http://cancerwebpa.jefferson.edu/iSeqQC/</a></p>
<p><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8</a></p><p>Address of the bookmark: <a href="https://github.com/gkumar09/iSeqQC" rel="nofollow">https://github.com/gkumar09/iSeqQC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14050/assistant-professor-in-bioinformatics-at-indian-institute-of-technology-delhi</guid>
  <pubDate>Fri, 15 Aug 2014 06:16:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor 	in Bioinformatics at Indian Institute of Technology Delhi]]></title>
  <description><![CDATA[
<p>Indian Institute of Technology Delhi Hauz Khas ,New Delhi – 110016</p>

<p>ROLLING ADVERTISEMENT NO. 01/2014(E-1)<br />ADVERTISEMENT FOR THE POSITIONS OF ASSISTANT PROFESSOR CANDIDATES CAN APPLY ANY TIME DURING THE YEAR.</p>

<p>IIT Delhi invites applications from qualified Indian Nationals, Persons of Indian Origin (PIOs) and Overseas Citizens of India (OCIs) for the following positions in the various Departments/Centres/Schools (in the fields<br />mentioned alongwith them):<br />Post Pay Band Assistant Professor and Assistant Professor (on Contract) Rs.15600-39100 (PB-3) (Minimum pay of Rs.30000/-)+ AGP Rs.8000/-</p>

<p>The following norms will be followed for fixing the basic pay + AGP for Assistant Professors appointed on<br />contract with Ph.D but experience of 3 years or less:-<br />Type Qualification &amp; Experience on the date of joining<br />Assistant Professor (Contract) PB3 (Rs. 15,600-39,100).</p>

<p>MINIMUM QUALIFICATIONS AND EXPERIENCE:<br />Ph.D. with First class at the preceding degree or equivalent in the appropriate branch with very good academic record throughout. A minimum of three years industrial/research/teaching experience, excluding however, the experience gained while Pursuing Ph. D. The candidates should preferably be below<br />35 years of age for male and 38 years for female ( to be relaxed by 5 years in case of persons with physical disability, SC/ST and 3 years in case of OBC-NCL).</p>

<p>Qualified persons include:<br />(a) Indian Nationals,<br />(b) Foreign Nationals who are “Persons of Indian Origin” (PIO) or Overseas<br />Citizens of India (OCI), in whose case, if selected, permission will be sought from Govt. of India<br />before he/she can join IIT Delhi, or<br />(c) Other Foreign Nationals, in whose case, if selected, appointment will be on a contract basis for up to 5 (five) years subject to permission from the Govt. of India before he/she can join IIT Delhi.<br />(d) Institute specifically encourages applicants from SC/ST/OBC category as well as persons<br />with disability to apply for these positions. </p>

<p>AMAR NATH &amp; SHASHI KHOSLA SCHOOL OF INFORMATION TECHNOLOGY:<br />Computational Neuroscience, Medical Applications of Information Technologies, Computational &amp; Systems Biology, Machine to Machine (M2M) Technologies, Embedded Systems &amp; Sensors, Computer Security.<br />KUSUMA SCHOOL OF BIOLOGICAL SCIENCES:<br />In-silico Biology Applications, Systems Biology, Infection Biology, Neurodegeneration. </p>

<p>More at http://www.iitd.ac.in/sites/default/files/jobs/faculty/spl-areas-rolling-advt.pdf</p>

<p>http://www.iitd.ac.in/content/faculty-positions</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</guid>
	<pubDate>Mon, 18 May 2020 10:53:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</link>
	<title><![CDATA[CAT/BAT: tool for taxonomic classification of contigs and metagenome-assembled genomes (MAGs)]]></title>
	<description><![CDATA[<p>Contig Annotation Tool (CAT) and Bin Annotation Tool (BAT) are pipelines for the taxonomic classification of long DNA sequences and metagenome assembled genomes (MAGs/bins) of both known and (highly) unknown microorganisms, as generated by contemporary metagenomics studies. The core algorithm of both programs involves gene calling, mapping of predicted ORFs against the nr protein database, and voting-based classification of the entire contig / MAG based on classification of the individual ORFs. CAT and BAT can be run from intermediate steps if files are formated appropriately (see <a href="https://github.com/dutilh/CAT#usage">Usage</a>).</p><p>Address of the bookmark: <a href="https://github.com/dutilh/CAT" rel="nofollow">https://github.com/dutilh/CAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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