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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31881?offset=1360</link>
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	<description><![CDATA[]]></description>
	
	<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/opportunity/view/22615/jrf-position-%E2%80%93-bioinformatics-department-aravind-medical-research-foundation-amrf-madurai</guid>
  <pubDate>Fri, 12 Jun 2015 05:42:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Position – Bioinformatics Department, Aravind Medical Research Foundation (AMRF), Madurai.]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates for the post of Junior Research Fellow (JRF) to work at the Department of Bioinformatics, Aravind Medical Research Foundation in the following DST-SERB funded project “Clinical exome analysis pipeline for eye disease next-generation sequencing panel”.</p>

<p>Post: Junior Research Fellow (1 Position)</p>

<p>Duration: Three years</p>

<p>Qualification: First class in M.Sc/M.tech in Bioinformatics/Life Sciences/Biophysics/ Biostatistics/Bioengineering. Experience in Database development, NGS data analysis, Systems Biology and Structural Bioinformatics is desired. Preference will be given to the candidates with good computer programming skills in C, C++, R, Perl, PHP, Unix Scripting etc.</p>

<p>Selected candidates will be paid fellowship as per existing DST norms.</p>

<p>How to apply:</p>

<p>Candidates are requested to apply through one of the two modes given below<br />1. Online application – Click here to submit the online application https://docs.google.com/forms/d/16h2GLnQ-Ny-tLtlgfY3Bx3sCjeHJE30cfhJaDqW_uRs/viewform?c=0&amp;w=1<br />2. Application forms can be downloaded from here.https://docs.google.com/file/d/0BwwJEudQStxFWXdNWXl4NWtDaWc/edit<br /> Filled in application form should be sent by post to Dr. D. Bharanidharan, Department of Bioinformatics, Aravind Medical Research Foundation No 1, Anna Nagar Madurai – 625 020,</p>

<p>Candidates should apply by online or submit their applications by post on or before 15th June, 2015. Only Short listed candidates will be called for an interview. No TA/DA will be paid.</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/pages/view/22571/pattern-matching-problem-solution-with-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:58:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22571/pattern-matching-problem-solution-with-perl</link>
	<title><![CDATA[Pattern Matching Problem Solution with Perl]]></title>
	<description><![CDATA[<p>Problem at http://rosalind.info/problems/1c/</p><p>#Find all occurrences of a pattern in a string.<br />#Given: Strings Pattern and Genome.<br />#Return: All starting positions in Genome where Pattern appears as a substring. Use 0-based indexing.<br /><br />use strict;<br />use warnings;<br /><br />my $string="GATATATGCATATACTT";<br />my $subStr="ATAT";<br />my $kmer=length($subStr);<br /><br />kmerMatch ($string, $subStr, $kmer);<br /><br />sub kmerMatch { #Check the exact matching kmers with sliding window<br />my ($string, $myStr, $kmer)=@_;<br />for (my $aa=0; $aa&lt;=(length($string)-$kmer); $aa++) {<br />&nbsp;&nbsp;&nbsp; my $myWin=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp;&nbsp; if ($myWin eq $myStr) {<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; #print "$myWin eq $myStr\n";<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; print $aa;<br />&nbsp;&nbsp;&nbsp; }<br />}<br />}</p>]]></description>
	<dc:creator>Jit</dc:creator>
</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/news/view/22769/ensembl-27</guid>
	<pubDate>Tue, 16 Jun 2015 16:10:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22769/ensembl-27</link>
	<title><![CDATA[Ensembl 27]]></title>
	<description><![CDATA[<h3>What is new?</h3><ul>
<li>Expansion of Protists and Fungi with hundreds of annotated genomes</li>
<li>Variation data for bread wheat, rice, <em>Aedes aegypti</em>, and <em>Ixodes scapularis</em></li>
<li>Whole genome alignments for <em>O. longistaminata</em> and <em>T. cacao</em></li>
<li>Non-coding RNA gene models in <a href="http://bacteria.ensembl.org">Bacteria</a></li>
<li>New assembly of tomato (version 2.50)</li>
<li>Full support for UCSC Track Hub format for hosting your own data in Ensembl</li>
</ul><p>More at http://www.ensembl.info/blog/2015/06/16/ensembl-genomes-release-27-is-out/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data</guid>
	<pubDate>Thu, 14 Dec 2017 15:51:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data</link>
	<title><![CDATA[SVfinder: Tool for detecting genomic rearrangement form DNA-seq data]]></title>
	<description><![CDATA[<p><span>SVfinder provides genome-wide detection of structural variants from next generation paired-end sequencing reads.</span></p><p>Address of the bookmark: <a href="https://github.com/cauyrd/SVfinder" rel="nofollow">https://github.com/cauyrd/SVfinder</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22780/ra-bioinformatics-at-institution-centre-for-human-genetics-bangalore</guid>
  <pubDate>Wed, 17 Jun 2015 19:14:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Institution: Centre for Human Genetics,  Bangalore]]></title>
  <description><![CDATA[
<p>Institution: Centre for Human Genetics, <br />Bangalore <br />Discipline: Molecular Genetics of Human Disease Biology </p>

<p>Minimum qualification: MSc in any branch of life sciences</p>

<p>Applications are invited for the position of a Research Assistant in the Centre for Human Genetics, Bangalore. </p>

<p>The project involves identification of mutations in MPS (mucopolysaccharidosis) patients, and study of their predicted effects to understand how the mutations lead to disease. </p>

<p>Techniques used will be genomic DNA isolation, PCR, DNA sequencing and sequence analysis. Computational tools would also be used to analyse and interpret data. </p>

<p>Candidates may be assigned work in the ongoing project or in new ones. </p>

<p>The candidate who is selected and joins would acquire hands-on experience in research and the capability to conduct insightful research. </p>

<p>Candidates applying for the position should have an MSc in any branch of life sciences. Those with research experience in cell and molecular biology, and high NET/ GATE score would be preferred. </p>

<p>The successful applicant is expected to stay for at least one and a half years. </p>

<p>Please apply with CV to Sudha Srinivasan (sudha@ibab.ac.in), stating where you saw this ad.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</guid>
	<pubDate>Tue, 27 Nov 2018 04:43:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</link>
	<title><![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]></title>
	<description><![CDATA[<p><span>lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.</span></p>
<p>lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/lordfast" rel="nofollow">https://github.com/vpc-ccg/lordfast</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42204/g-nest-the-gene-neighborhood-scoring-tool</guid>
	<pubDate>Fri, 25 Sep 2020 20:09:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42204/g-nest-the-gene-neighborhood-scoring-tool</link>
	<title><![CDATA[G-NEST: The Gene NEighborhood Scoring Tool]]></title>
	<description><![CDATA[<p><span>The Gene NEighborhood Scoring Tool (G-NEST) combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all window sizes. Primary author of final code = William F. Martin. Example data files are in the separate repository.</span></p><p>Address of the bookmark: <a href="https://github.com/dglemay/G-NEST" rel="nofollow">https://github.com/dglemay/G-NEST</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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