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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/11030?offset=820</link>
	<atom:link href="https://bioinformaticsonline.com/related/11030?offset=820" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</guid>
	<pubDate>Tue, 21 Jan 2020 04:22:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</link>
	<title><![CDATA[Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.]]></title>
	<description><![CDATA[<p>Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the<span>&nbsp;</span><a href="http://deltarho.org/docs-trelliscope/deltarho.org">DeltaRho</a><span>&nbsp;</span>environment.</p>
<p>For those familiar with<span>&nbsp;</span><a href="http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/">Trellis Display</a>,<span>&nbsp;</span><a href="http://docs.ggplot2.org/0.9.3.1/facet_wrap.html">faceting in ggplot</a>, or the notion of<span>&nbsp;</span><a href="http://en.wikipedia.org/wiki/Small_multiple">small multiples</a>, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.</p><p>Address of the bookmark: <a href="http://deltarho.org/docs-trelliscope/#introduction" rel="nofollow">http://deltarho.org/docs-trelliscope/#introduction</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41043/postdoctoral-scientist-genome-analytics-genome-bioinformatics-mf</guid>
  <pubDate>Sun, 16 Feb 2020 02:57:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral scientist genome analytics/ genome bioinformatics (m/f/*)]]></title>
  <description><![CDATA[
<p>https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html<br />Your profile:<br />Degree in bioinformatics, biostatistics, or equivalent<br />Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance computing<br />Strong competence in working in Unix/Linux environments (shell)<br />Strong programming skills (in particular: Python, R, Perl)<br />Experience with using git and snakemake<br />Fluent English language skills, both spoken and written<br />Strong communication skills and motivation to work in a young, interdisciplinary, dynamic team</p>

<p>Additional Information:</p>

<p>If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).</p>

<p>Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).</p>

<p>Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.</p>

<p>Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/41496/new-machine-learning-packages-in-r</guid>
	<pubDate>Fri, 27 Mar 2020 12:11:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/41496/new-machine-learning-packages-in-r</link>
	<title><![CDATA[New Machine Learning Packages in R]]></title>
	<description><![CDATA[<h3 id="machine-learning">Machine Learning</h3><p><a href="https://cran.r-project.org/package=autokeras">autokeras</a>&nbsp;v1.0.1: Implements an interface to&nbsp;<a href="https://autokeras.com/">AutoKeras</a>, an open source software library for automated machine learning. See&nbsp;<a href="https://cran.r-project.org/web/packages/autokeras/readme/README.html">README</a>&nbsp;for an example.</p><p><a href="https://cran.r-project.org/package=MTPS">MTPS</a>&nbsp;v0.1.9: Implements functions to predict simultaneous multiple outcomes based on revised stacking algorithms as described in&nbsp;<a href="denied:doi:10.1093/bioinformatics/btz531">Xing et al. (2019)</a>. See the&nbsp;<a href="https://cran.r-project.org/web/packages/MTPS/vignettes/Guide.html">vignette</a>&nbsp;to get started.</p><p><a href="https://cran.r-project.org/package=quanteda.textmodels">quanteda.textmodels</a>&nbsp;v0.9.1: Implements methods for scaling models and classifiers based on sparse matrix objects representing textual data. It includes implementations of the&nbsp;<a href="denied:doi:10.1017/S0003055403000698">Laver et al. (2003)</a>&nbsp;wordscores model, the&nbsp;<a href="denied:arxiv:1710.08963">Perry &amp; Benoit&rsquo;s (2017)</a>&nbsp;class affinity scaling model, and the&nbsp;<a href="denied:doi:10.1111/j.1540-5907.2008.00338.x">Slapin &amp; Proksch (2008)</a>&nbsp;wordfish model. See the&nbsp;<a href="https://cran.r-project.org/web/packages/quanteda.textmodels/vignettes/textmodel_performance.html">vignette</a>&nbsp;to get started.</p><p><a href="https://cran.r-project.org/package=SeqDetect">SeqDetect</a>&nbsp;v1.0.7: Implements the automaton model found in&nbsp;<a href="https://ieeexplore.ieee.org/document/8910574">Krleža, Vrdoljak &amp; Brčić (2019)</a>&nbsp;to detect and process sequences. See the&nbsp;<a href="https://cran.r-project.org/web/packages/SeqDetect/vignettes/SequentialDetector.pdf">vignette</a>&nbsp;for examples and theory.</p><p><a href="https://cran.r-project.org/package=studyStrap">studyStrap</a>&nbsp;v1.0.0: Implements multi-Study Learning algorithms such as Merging, Study-Specific Ensembling (Trained-on-Observed-Studies Ensemble), the Study Strap, and the Covariate-Matched Study Strap. and offers over 20 similarity measures. See&nbsp;<a href="denied:doi:10.1101/856385">Kishida, et al. (2019)</a>&nbsp;for background and the&nbsp;<a href="https://cran.r-project.org/web/packages/studyStrap/vignettes/vignette.html">vignette</a>&nbsp;for how to use the package.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</guid>
	<pubDate>Fri, 13 Aug 2021 07:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</link>
	<title><![CDATA[QuasR: Quantification and annotation of short reads in R]]></title>
	<description><![CDATA[<p>The <em><a href="https://bioconductor.org/packages/3.14/QuasR">QuasR</a></em> package (short for <em>Qu</em>antify and <em>a</em>nnotate <em>s</em>hort reads in <em>R</em>) integrates the functionality of several <strong>R</strong> packages (such as <em><a href="https://bioconductor.org/packages/3.14/IRanges">IRanges</a></em> <span>(Lawrence et al. 2013)</span> and <em><a href="https://bioconductor.org/packages/3.14/Rsamtools">Rsamtools</a></em>) and external software (e.g.&nbsp;<code>bowtie</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rbowtie">Rbowtie</a></em> package, and <code>HISAT2</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rhisat2">Rhisat2</a></em> package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single <strong>R</strong> script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44362/biostats-book</guid>
	<pubDate>Mon, 14 Aug 2023 03:11:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44362/biostats-book</link>
	<title><![CDATA[Biostats book !]]></title>
	<description><![CDATA[<p>https://practical-stats-med-r.netlify.app/</p><p>Address of the bookmark: <a href="https://practical-stats-med-r.netlify.app/" rel="nofollow">https://practical-stats-med-r.netlify.app/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</guid>
	<pubDate>Tue, 17 Sep 2024 02:34:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</link>
	<title><![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]></title>
	<description><![CDATA[<p dir="auto">R Package to visualize alignments between two or multiple DNA sequences including<br>a number of functionalities to facilitate processing of alignments in PAF format.</p>
<p dir="auto"><span>SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.</span></p>
<p dir="auto">Author: David Porubsky</p><p>Address of the bookmark: <a href="https://github.com/daewoooo/SVbyEye" rel="nofollow">https://github.com/daewoooo/SVbyEye</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37509/vcftools-perform-common-tasks-with-vcf-files-such-as-file-validation-file-merging-intersecting-complements</guid>
	<pubDate>Tue, 07 Aug 2018 10:01:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37509/vcftools-perform-common-tasks-with-vcf-files-such-as-file-validation-file-merging-intersecting-complements</link>
	<title><![CDATA[VCFtools: perform common tasks with VCF files such as file validation, file merging, intersecting, complements]]></title>
	<description><![CDATA[<p>VCFtools contains a Perl API (<a href="http://vcftools.sourceforge.net/perl_module.html#Vcf.pm">Vcf.pm</a>) and a number of Perl scripts that can be used to perform common tasks with VCF files such as file validation, file merging, intersecting, complements, etc. The Perl tools support all versions of the VCF specification (3.2, 3.3, 4.0, 4.1 and 4.2), nevertheless, the users are encouraged to use the latest versions VCFv4.1 or VCFv4.2. The VCFtools in general have been used mainly with diploid data, but the Perl tools aim to support polyploid data as well. Run any of the Perl scripts with the&nbsp;<strong>--help</strong>&nbsp;switch to obtain more help.</p>
<p>Many of the&nbsp;<strong>Perl scripts require that the VCF files are compressed by&nbsp;<span>bgzip</span>&nbsp;and indexed by&nbsp;<span>tabix</span></strong>&nbsp;(both tools are part of the tabix package, available for&nbsp;<a href="https://sourceforge.net/projects/samtools/files/tabix/">download here</a>). The VCF files can be compressed and indexed using the following commands</p>
<p>bgzip my_file.vcf<br>tabix -p vcf my_file.vcf.gz</p>
<p>&nbsp;</p>
<p>http://vcftools.sourceforge.net/perl_module.html</p><p>Address of the bookmark: <a href="http://vcftools.sourceforge.net/perl_module.html" rel="nofollow">http://vcftools.sourceforge.net/perl_module.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21471/opening-for-raextended-srf-in-bioinformatics-project-by-dbt-at-bose-institute</guid>
  <pubDate>Sun, 01 Mar 2015 00:50:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Opening for RA/extended SRF in Bioinformatics project by DBT at Bose Institute]]></title>
  <description><![CDATA[
<p>The institute has evolved over the years into a multi-disciplinary research organization with stress on fundamental research in its pursuit of advancement of knowledge in Science and technology and at the same time developing highly competent and able scientific manpower for the country. The institute has on its staff highly qualified and experienced scientists working in the field of Biological, biochemical, Chemical and Physical sciences placed in long established departments of Physics, Chemistry, Botany, Microbiology, Biochemistry, and Biophysics, and the research sections on plant Molecular &amp; Cellular Genetics, Animal Physiology, Immunotechnology and Environmental science</p>

<p>Walk-in-Interview will be held on 04th March 2015 at 11.30 A.M. in the Bio- Informatics Centre of Bose Institute, P-1/12, C.I.T. Scheme VII-M, Kolkata- 700054 for two (02) positions of Research Associate/ Extended Senior Research Fellow in the DBT sponsored following two projects running under the CoE- Bioinformatics under the guidance of Prof. Pinakpani Chakrabarti, Bioinformatics Centre.</p>

<p>Position : RA/SRF<br />Project title : 1. "Centre of Excellence (CoE) in Bioinformatics at Bose Institute”,2. Project entitled “Setting up of National Facility on Interactive Graphysics Computer System (IGCS) for Biomolecular Modeling, Molecular Dynamics &amp; Structures”</p>

<p>Desired Profile : Ph.D degree in Biological or Chemical Sciences with in-depth understanding of protein structure and dynamics for R.A. position.Those who have submitted thesis can be considered for Extended SRF position<br />Preferred : Knowledge of computer programming and bioinformatics softwares.<br />Stipend : For R.A- Rs. 22,000/- p.m., plus admissible H.R.A. and Medical benefit. For Extended SRF - Rs. 20,000/- p.m., plus admissible H.R.A.and Medical benefit.<br />Age : For R.A- Below 35 years; For Extended SRF - Below 33 years<br />Interested and eligible candidates should appear before the Selection Committee with atyped application addressed to the Sr.Prof. &amp; In-Charge, Registrar's Office, Bose Institute, P- 1/12, CIT Scheme VII-M, Kankurgachi, Kolkata-700054 along with Bio-data giving details of qualification i.e. examination passed, year, division, percentage of marks from Secondary onwards with attested copies of Certificates, Mark-Sheet and testimonials. The candidates should also bring the original mark-sheets, certificates etc. at the time of Interview.</p>

<p>Walk in Interview : 04.03.15</p>

<p>More at http://www.boseinst.ernet.in/ADVT/14/p_34.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21619/research-associate-biotechnologyjrflab-assistant-indian-institute-of-vegetable-research-iivr-varanasi-uttar-pradesh</guid>
  <pubDate>Wed, 11 Mar 2015 08:59:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Biotechnology/JRF/Lab. Assistant  Indian Institute of Vegetable Research (IIVR) - Varanasi, Uttar Pradesh]]></title>
  <description><![CDATA[
<p>F. No.: 2-19/2011-Adm.I </p>

<p>Research Associate Biotechnology /JRF / Lab. Assistant recruitment in Indian Institute of Vegetable Research </p>

<p>Project:<br />Genomics assisted selection of Solanum chilense introgression lines for enhancing drought tolerance in tomato <br />Post Name : Research Associate <br />Qualification : Ph.D in Biotechnology/ Bioinformatics/Genetics &amp; Plant Breeding. M. Tech in Computer Science with at least one research paper in science citation indexed journal. Desirable: Experience in bioinformatics and next generation sequence data handling. Familiarity in Linux, R, Perl/Phython or other programming languages. Willingness to travel to European partner centers. </p>

<p>Pay Scale : Rs. 36000 for 1st and 2nd year as per rules for Research Associate. Rs. 25000/- for 1st and 2nd year and Rs. 28000 as per rules for Junior Research Fellow. Rs. 7000/- for Lab. Assistant. </p>

<p>Age : Not more than 35 years for Men and 40 years for Women (Relaxable for SC/ST/OBC/PH candidates as per rules) for Research Associate/ Junior Research Fellow. Minimum age will be 21 years and maximum age will be 45 years (Relaxable for SC/ST/OBC/PH candidates as per rules) for Lab.Assistant.</p>

<p>More at http://iivr.org.in/Job%20Oppurtunities/RA20.03.2015.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24462/icar-project-ra-position-institute-of-bioinformatics-iob-bangalore</guid>
  <pubDate>Tue, 22 Sep 2015 23:41:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[ICAR project RA position @ Institute of Bioinformatics (IOB) Bangalore]]></title>
  <description><![CDATA[
<p>Applications are invited for the post of Research Associate (RA) in the ICAR project on "Lactation stress associated postpartum anestrus SNP array in buffaloes". We are looking for a motivated candidate for handling Next Generation sequencing data analysis with a strong background in bioinformatics and programming.</p>

<p>The position is open for immediate appointment and available for two years and then extendable for additional one year. The applicant will be appointed as Research Associate based on qualifications as detailed below:</p>

<p>Research Associate:</p>

<p>-Master’s degree with bioinformatics with at least 2 years of research experience in Next Generation sequencing data analysis as evidence from Fellowship/ Associateship / Training / other engagements.</p>

<p>-Familiarity with bioinformatics tools, database development, programming skills</p>

<p>-Minimum 1 publication in any peer reviewed journal</p>

<p>Salary will be as per ICAR rules and guidelines. Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.</p>

<p>Interested candidates may send a Letter of Interest and CV by email to: keshav@ibioinformatics.org before September 29, 2015.</p>
]]></description>
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