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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28884?offset=1660</link>
	<atom:link href="https://bioinformaticsonline.com/related/28884?offset=1660" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<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/videolist/watch/20585/dna-transcription-advanced</guid>
	<pubDate>Thu, 29 Jan 2015 05:31:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</link>
	<title><![CDATA[DNA Transcription (Advanced)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/SMtWvDbfHLo" frameborder="0" allowfullscreen></iframe><p>Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.</p>]]></description>
	
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	<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/20958/ra-bioinformatics-at-ciba</guid>
  <pubDate>Mon, 02 Feb 2015 22:52:50 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at CIBA]]></title>
  <description><![CDATA[
<p>The following posts are to be filled purely on temporary basis under CIBA Component of “Centre for Agricultural Bioinformatics (CABin)” project at this Institute.</p>

<p>Research Associate – one post</p>

<p>Date &amp; Time of Interview 18th Feb 2015 at 10.00 a.m.</p>

<p>Essential Qualification Ph.d / M.Sc./ M.Phil (Bioinformatics) With 1st division or 60% marks or equivalent overall grade point average with at least two years of research experience in the relevant subject.</p>

<p>Desirable qualification: Experience in Java/ C++/ PHP/ PERL/ Python etc. based application development using Linux, Apache and MySQL/Oracle.</p>

<p>Emoluments Rs.24000/- p.m. + 30% HRA for Ph.D holders / Rs.23000/- p.m. + 30% HRA for Master Degree holders A consolidated pay Rs.25000/- per month.</p>

<p>Age Limit Maximum 40 years for men and 45 years for women as on date of interview. Age limits are relaxable for SC / ST / OBC candidates as per rules. Maximum 40 years for men and 45 years for women as on date of interview. Age limits are relaxable for SC / ST / OBC candidates as per rules.</p>

<p>Eligible Candidates may appear for the Walk-in-interview with original Certificate of Ph.D. / Master’s / relevant degree, passport size photograph and bio-data enclosing attested copies of educational qualification &amp; experience certificates. TA / DA will not be paid for attending the interview.</p>

<p>Advertisement: www.ciba.res.in/attachments/jobs/CABin-3006.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42472/maftools-summarize-analyze-and-visualize-maf-files</guid>
	<pubDate>Wed, 23 Dec 2020 05:29:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42472/maftools-summarize-analyze-and-visualize-maf-files</link>
	<title><![CDATA[maftools : Summarize, Analyze and Visualize MAF Files]]></title>
	<description><![CDATA[<p><span>With advances in Cancer Genomics,&nbsp;</span><a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a><span>&nbsp;(MAF) is being widely accepted and used to store somatic variants detected.&nbsp;</span><a href="http://cancergenome.nih.gov/">The Cancer Genome Atlas</a><span>&nbsp;Project has sequenced over 30 different cancers with sample size of each cancer type being over 200.&nbsp;</span><a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">Resulting data</a><span>&nbsp;consisting of somatic variants are stored in the form of&nbsp;</span><a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a><span>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.</span></p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html" rel="nofollow">https://www.bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20957/jrf-in-bioinformatics-tezpur-university</guid>
  <pubDate>Mon, 02 Feb 2015 22:50:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF in Bioinformatics @ Tezpur University]]></title>
  <description><![CDATA[
<p>Applications are invited for one temporary position of Junior Research Fellow (JRF) in the DBT Twinning Project entitled ‘In-Silico design and evaluation of sequences for γD crystalline protein’ under the Principal Investigator Dr. Anupam Nath Jha, Assistant Professor, Department of Molecular Biology and Biotechnology, Tezpur University.</p>

<p>Educational Qualification: Candidate must possess a M.Sc. in Bioinformatics/ Biotechnology/ Computer Science/ Physics/ Chemistry or B.Tech. or M.Tech. in Bioinformatics/ Biotechnology/ Computer Science from a recognized University/ Institute with minimum 60% marks or equivalent CGPA for general category and for SC/ST/OBC relaxation will be given as per Govt. of India rules.</p>

<p>Fellowship: Rs 16,000/- (Rupees sixteen thousand) only + 10% HRA per month for NET/GATE/BET/BINC qualified candidates. Rs. 12,000/- (Rupees twelve thousand) only + 10% HRA per month for other candidates.</p>

<p>Duration: Initially for a period of six (06) months which may be extended depending upon status of the project or until further order, whichever is earlier.</p>

<p>Age: Candidate should not be more than 28 years of age on the date of interview. Upper age limit may be relaxed up to 5 years in the case of candidate belonging to SC/ ST /OBC /Women / Physically Challenged.</p>

<p>Interested candidates may send their application on plain paper by post along with his/her educational qualifications, recent passport/stamp size photograph and contact phone number to Dr. Anupam Nath Jha, Principal Investigator, Department of Molecular Biology and Biotechnology, Tezpur University, Napaam – 784028 or mail it to anjha@tezu.ernet.in within 20 days of publication of this advertisement.</p>

<p>Only shortlisted candidates will be informed by e-mail or phone for an interview. N.B. No TA/DA will be paid for attending the interview. For further details contact: Dr. Anupam Nath Jha, Assistant Professor, Principal Investigator Department of Molecular Biology &amp; Biotechnology Tezpur University, Napaam, Tezpur-784028 (Assam)</p>

<p>Advertisement: www.tezu.ernet.in/ProjectWalkin/Advt-ANJ-5323-A.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</guid>
	<pubDate>Sun, 15 Mar 2020 03:41:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</link>
	<title><![CDATA[GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns]]></title>
	<description><![CDATA[<p><span><span>GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.</span></span></p>
<p><span>GSP4PDB</span><span>&nbsp;is part of the services provided by the&nbsp;</span><a href="https://structuralbio.utalca.cl/" target="_blank">Bioinformatic Group</a><span>&nbsp;of the&nbsp;</span><a href="http://www.utalca.cl/" target="_blank">University of Talca</a></p>
<p><a href="http://gdblab.com/gsp4pdb/gsp4pdb2/">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3352-x</p><p>Address of the bookmark: <a href="http://gdblab.com/gsp4pdb/gsp4pdb2/" rel="nofollow">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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