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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29276?offset=1230</link>
	<atom:link href="https://bioinformaticsonline.com/related/29276?offset=1230" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22297/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics</guid>
  <pubDate>Fri, 08 May 2015 00:24:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Appointment of two traineeships and two studentships in Bioinformatics]]></title>
  <description><![CDATA[
<p>Applications are invited for the appointment of two traineeships and two studentships in Bioinformatics for a period of six months sponsored by Department of Biotechnology, Government of India in the Bioinformatics Sub-DIC, Saraswathy Thangavelu Centre, JNTBGRI, Puthenthope, Thiruvananthapuram 695 586. The required qualifications and other details are given below.</p>

<p>Position 1: Traineeship<br />Monthly fellowship (in rupee): 5,000/-<br />No. of vacancies: Two<br />Required Qualification: First Class M.Sc Bioinformatics/ Biotechnology/ Botany</p>

<p>Position 2: Studentship<br />Monthly fellowship (in rupee): 5,000/-<br />No. of vacancies: Two<br />Required Qualification: M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.</p>

<p>Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.</p>

<p>Interested candidates may appear for walk-in-interview on 15th May 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am.</p>

<p>More at http://jntbgri.res.in/news/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</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/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file</guid>
	<pubDate>Mon, 23 Mar 2020 06:22:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file</link>
	<title><![CDATA[tinycov: standalone command line utility written in python to plot coverage from a BAM file]]></title>
	<description><![CDATA[<p>Tinycov is a small standalone command line utility written in python to plot the coverage of a BAM file quickly. This software was inspired by&nbsp;<a href="https://github.com/matted/genome_coverage_plotter">Matt Edwards' genome coverage plotter</a>.</p>
<p>To install the stable version:&nbsp;<code>pip3 install --user tinycov</code></p>
<p>To install the development version:</p>
<pre><code>git clone https://github.com/cmdoret/tinycov.git
cd tinycov
pip install .</code></pre><p>Address of the bookmark: <a href="https://github.com/cmdoret/tinycov" rel="nofollow">https://github.com/cmdoret/tinycov</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22431/genomic-scientist-at-udsc</guid>
  <pubDate>Thu, 28 May 2015 19:14:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Genomic Scientist at UDSC]]></title>
  <description><![CDATA[
<p>Centre for Genetic Manipulation of Crop Plants</p>

<p>Department of Genetics</p>

<p>University of Delhi South Campus</p>

<p>NEW DELHI – 110 021</p>

<p>WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT &amp; LAB / FIELD ATTENDANT</p>

<p>1 Research Scientist (RS) – 3</p>

<p>    DBT, Ph. D.</p>

<p>    Experience on DNA Markers, plant genome mapping and bioinformatics</p>

<p>    Salary: 60,000 (Consolidated) + 5% annual increment</p>

<p>    Date and time: 25.06.2015 at 10:30 AM</p>

<p>These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’</p>

<p>The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.</p>

<p>Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.</p>

<p>No TA/DA will be paid for attending the interview.</p>

<p>Advertisement:</p>

<p>www.du.ac.in/du/index.php?mact=News,cntnt01,detail,0&amp;cntnt01articleid=5492&amp;cntnt01returnid=83</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis</guid>
	<pubDate>Wed, 22 Mar 2023 02:10:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis</link>
	<title><![CDATA[Tools for Geospatial data analysis !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data, and other forms of spatial data. They can help you visualize data, perform complex analysis, and even create maps and other visualizations.</p><p>The list includes some of the most popular and widely used geospatial tools available in Python. These tools can help you work with data from a variety of sources and in a variety of formats. Some of the tools are focused on visualization, such as Cartopy, Folium, and Contextily, which allow you to create interactive maps and other visualizations. Other tools are more focused on data manipulation and analysis, such as Fiona, GeoPandas, and Rasterio, which allow you to manipulate and analyze spatial data in a variety of ways.</p><p>The list also includes some tools for working with specific types of geospatial data. For example, the H3 library is designed specifically for working with hexagonal grids, while PySAL is focused on spatial econometrics and spatial analysis. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.</p><p>In summary, this list is an excellent resource for anyone working with geospatial data in Python. It contains a wide range of tools for working with different types of data, and can help you visualize data, perform complex analysis, and create maps and other visualizations. If you're looking to enhance your skills in geospatial analysis, this list is definitely worth checking out.</p></div></div></div><div><p>These tools are:</p><ul>
<li>ArcGIS - <a href="https://lnkd.in/dgC6sKJH" target="_new">https://lnkd.in/dgC6sKJH</a></li>
<li>Cartopy - <a href="https://lnkd.in/dc8ijXRg" target="_new">https://lnkd.in/dc8ijXRg</a></li>
<li>Contextily - <a href="https://lnkd.in/dTdQsmKX" target="_new">https://lnkd.in/dTdQsmKX</a></li>
<li>Descartes - <a href="https://lnkd.in/dCJykxwW" target="_new">https://lnkd.in/dCJykxwW</a></li>
<li>Fiona - <a href="https://lnkd.in/d8sJ3Q5a" target="_new">https://lnkd.in/d8sJ3Q5a</a></li>
<li>Folium - <a href="https://lnkd.in/dfSsE-MB" target="_new">https://lnkd.in/dfSsE-MB</a></li>
<li>GDAL - <a href="https://lnkd.in/dYBJBaAY" target="_new">https://lnkd.in/dYBJBaAY</a></li>
<li>Geohash - <a href="https://lnkd.in/d_NxJ4_M" target="_new">https://lnkd.in/d_NxJ4_M</a></li>
<li>GeoJSON - <a href="https://lnkd.in/daGs2WYq" target="_new">https://lnkd.in/daGs2WYq</a></li>
<li>GeoPandas - <a href="https://lnkd.in/dBTFKKV3" target="_new">https://lnkd.in/dBTFKKV3</a></li>
<li>Geopy - <a href="https://lnkd.in/dfAzR8Xa" target="_new">https://lnkd.in/dfAzR8Xa</a></li>
<li>Gevent - <a href="http://www.gevent.org/" target="_new">http://www.gevent.org</a></li>
<li>H3 - <a href="https://h3geo.org/docs/" target="_new">https://h3geo.org/docs/</a></li>
<li>OSMnx - <a href="https://lnkd.in/dm3pHgUS" target="_new">https://lnkd.in/dm3pHgUS</a></li>
<li>PyQGIS - <a href="https://lnkd.in/dShWyWVr" target="_new">https://lnkd.in/dShWyWVr</a></li>
<li>PySAL - <a href="https://pysal.org/" target="_new">https://pysal.org</a></li>
<li>Pydeck - <a href="https://lnkd.in/dGBFu-iw" target="_new">https://lnkd.in/dGBFu-iw</a></li>
<li>Pyproj - <a href="https://lnkd.in/dNG9fdkm" target="_new">https://lnkd.in/dNG9fdkm</a></li>
<li>RTree - <a href="https://lnkd.in/dURMiYpU" target="_new">https://lnkd.in/dURMiYpU</a></li>
<li>Rasterio - <a href="https://lnkd.in/dEMC6ve6" target="_new">https://lnkd.in/dEMC6ve6</a></li>
<li>Scikit-mobility - <a href="https://lnkd.in/dpHhaX2J" target="_new">https://lnkd.in/dpHhaX2J</a></li>
<li>Shapely - <a href="https://lnkd.in/d568datK" target="_new">https://lnkd.in/d568datK</a></li>
</ul><p>These tools offer a wide range of capabilities for working with geospatial data, from visualizing and manipulating data to performing complex analysis and modeling. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.</p></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22432/walk-ins-for-jrf-ans-srf-post-in-assam-agricultural-university</guid>
  <pubDate>Thu, 28 May 2015 19:16:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk-ins for JRF ans SRF post in Assam Agricultural University]]></title>
  <description><![CDATA[
<p>Distributed Information Centre<br />Department of Agricultural Biotechnology<br />Assam Agricultural University<br />Jorhat – 785 013<br />Walk-in interview</p>

<p>(ABT/DIC/01/2014 (No. AAU/ABT/DIT/Advt. 01/2015/111 Dtd. 19-05-2015)</p>

<p>Walk in interview for the following position will be held on 6th June, 2015 at 10.00AM in the Office Chamber of the undersigned. Candidates may appear for the interview with bio-data, reprints / publication / thesis etc and passport size photographs, original and attested copies of all testimonials etc, which must be presented at the time of interview. The applicants may submit their resume in advance tomkmodi@aau.ac.in.</p>

<p>Research Associate</p>

<p>    Ph.D. in Biotechnology/ Bioinformatics. Or</p>

<p>    Masters degree in Biotechnology/Bioinformatics with minimum 3(three) years research experience</p>

<p>    Desirable : Experience in Bioinformatics as evidenced from published research</p>

<p>    Rs 36,000+HRA for the 1st two years and 38,000+HRA for the 3rd year.</p>

<p>Senior Research Fellow</p>

<p>    Master Degree in Biotechnology/ Bioinformatics. With 2 (two) years  Experience in Bioinformatics as evidenced from Course work/ Diploma/Published research</p>

<p>    Rs 28,000+HRA for NET qualified candidate/Professional degree holder</p>

<p>    Rs 18,000+HRA for non-NET qualified general degree holder</p>

<p>Junior Research Fellow</p>

<p>    Master Degree in Biotechnology/ Bioinformatics/Computer Science/Computer Application</p>

<p>    Desirable: Experience in Bioinformatics as evident from Course work/ Diploma/Published research</p>

<p>    Rs 25,000+HRA for NET qualified candidate/Professional degree holder</p>

<p>    Rs 16,000+HRA for non-NET qualified general degree holder</p>

<p>Note: Term and conditions will be as per the DBT, Govt of India guidelines.</p>

<p>Advertisement: http://14.139.222.145/classified/biotech46.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</guid>
	<pubDate>Wed, 09 Aug 2017 07:16:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</link>
	<title><![CDATA[orthodotter: Synteny plots (oxford grid)]]></title>
	<description><![CDATA[<pre><code>orthodotter -h
--------------------------------------------------------------------------------
orthodotter - Plot orthologous genes on an oxford grid.
       -f &lt;file&gt;     : input file, containing orthologous genes, default is stdin
                       species chr-name start end species chr-name start end
       -toPlot &lt;arg&gt; : give the x and y sets and the color separated by double-dots,
                       for example set1:set2:red will plot set1 on x, set2 on y with
                       red points. Could give several -toPlot arguments.
                       To launch the clustering of dots, use extra-option 1=dist,min_nb_genes
                       where dist is the minimal distance (euclidian) between two points and min_nb_genes the minimal
                       number of genes in a cluster to be valid.
       -o &lt;file&gt;     : output file, default is stdout
       -x &lt;int&gt;      : resolution of x axis, default is 600
       -y &lt;int&gt;      : resolution on y axis, default is 600
       -r &lt;int&gt;      : radius of circle representing orthologous genes
       -format       : could be png, gif, jpg, pdf or ps. Default is png.
       -fg           : foreground color, default is black
       -bg           : background color, default is transparent
       -fSize &lt;int&gt;  : fontSize, default is 1
       -filter       : check chromosome names
       -h            : help
--------------------------------------------------------------------------------
orthodotter -f Vigne_Banane.ortho -toPlot Vigne:Banane:black:1=10,5 -x 1200 -y 1200 -bg white -o Vigne_vs_Banane.png &gt; Vigne_vs_Banane.clusters
--------------------------------------------------------------------------------</code></pre><p>Address of the bookmark: <a href="https://github.com/institut-de-genomique/orthodotter" rel="nofollow">https://github.com/institut-de-genomique/orthodotter</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22512/srf-post-in-nehu-shillong</guid>
  <pubDate>Wed, 03 Jun 2015 13:15:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF post in NEHU, Shillong]]></title>
  <description><![CDATA[
<p>Dept of Biochemistry <br />North-Eastern Hill University<br />(A University with Potential for Excellence) <br />Umshing, Shillong- 793 022</p>

<p>Applications are invited for the post of Senior Research Fellow- SRF (1) and Junior Research Fellow- JRF (1) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong. </p>

<p>Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite. </p>

<p>For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by atleast one good publication. </p>

<p>For JRF position, freshers can also apply. </p>

<p>Stipend: As per SERB norms. </p>

<p>Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 20.06.15. The hard copy is not required. The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com</p>

<p>Advertisement: http://www.nehu.ac.in/Advertisements/BiochemSERB_Advt_020615.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34038/quota-synteny-alignment</guid>
	<pubDate>Mon, 31 Jul 2017 04:11:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34038/quota-synteny-alignment</link>
	<title><![CDATA[Quota synteny alignment]]></title>
	<description><![CDATA[<p><span>Typically in comparative genomics, we can identify anchors, chain them into syntenic blocks and interpret these blocks as derived from a common descent. However, when comparing two genomes undergone ancient genome duplications (plant genomes in particular), we have large number of blocks that are not orthologous, but are paralogous. This has forced us sometimes to use&nbsp;</span><em>ad-hoc</em><span>&nbsp;rules to screen these blocks. So the question is:&nbsp;</span><span>given the expected depth (quota) along both x- and y-axis, select a subset of the anchors with maximized total score</span><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/quota-alignment" rel="nofollow">https://github.com/tanghaibao/quota-alignment</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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