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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44292?offset=70</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41405/sequence-tube-maps-displays-multiple-genomic-sequences-in-the-form-of-a-tube-map</guid>
	<pubDate>Wed, 11 Mar 2020 01:12:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41405/sequence-tube-maps-displays-multiple-genomic-sequences-in-the-form-of-a-tube-map</link>
	<title><![CDATA[Sequence Tube Maps: displays multiple genomic sequences in the form of a tube map]]></title>
	<description><![CDATA[<p>A JavaScript module for the visualization of genomic sequence graphs. It automatically generates a "tube map"-like visualization of sequence graphs which have been created with <a href="https://github.com/vgteam/vg">vg</a>. (<a href="https://github.com/vgteam/vg">https://github.com/vgteam/vg</a>)</p>
<h3>Link to working demo: <a href="https://vgteam.github.io/sequenceTubeMap/">https://vgteam.github.io/sequenceTubeMap/</a></h3>
<p><img src="https://raw.githubusercontent.com/vgteam/sequenceTubeMap/master/images/header.png" alt="image" style="border: 0px; border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/vgteam/sequenceTubeMap" rel="nofollow">https://github.com/vgteam/sequenceTubeMap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</guid>
	<pubDate>Wed, 13 Aug 2025 19:56:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</link>
	<title><![CDATA[dna2bit: an ultra-fast and accurate genomic distance estimation software]]></title>
	<description><![CDATA[<p dir="auto">dna2bit: an ultra-fast and accurate genomic distance estimation software</p>
<div dir="auto"><a href="https://github.com/lijuzeng/dna2bit#compilation"></a></div>
<p dir="auto">dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/lijuzeng/dna2bit" rel="nofollow">https://github.com/lijuzeng/dna2bit</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9639/find-certain-filesdocuments-in-linux-os</guid>
	<pubDate>Sun, 06 Apr 2014 23:56:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9639/find-certain-filesdocuments-in-linux-os</link>
	<title><![CDATA[Find certain files/documents in Linux OS]]></title>
	<description><![CDATA[<p>As bioinformatician I know the fact that we usually handle the large dataset and lost in the huge numbers of files and folders. In order to search the missing file a strong search command is required. The Linux Find Command is one of the most important and much used command in Linux sytems. Find command used to search and locate list of files and directories based on conditions you specify for files that match the arguments. Find can be used in variety of conditions like you can find files by permissions, users, groups, file type, date, size and other possible criteria.<br /><br />Through this article we are sharing our day-to-day Linux find command experience and its usage in the form of examples. In this article we will show you the most used 35 Find Commands examples in Linux. We have divided the section into Five parts from basic to advance usage of find command.</p><p><strong>Part I &ndash; Basic Find Commands for Finding Files with Names</strong><br />1. Find Files Using Name in Current Directory<br /><br />Find all the files whose name is gene.txt in a current working directory.<br /><br /># find . -name gene.txt<br /><br />./gene.txt<br /><br />2. Find Files Under Home Directory<br /><br />Find all the files under /home directory with name gene.txt.<br /><br /># find /home -name gene.txt<br /><br />/home/gene.txt<br /><br />3. Find Files Using Name and Ignoring Case<br /><br />Find all the files whose name is gene.txt and contains both capital and small letters in /home directory.<br /><br /># find /home -iname gene.txt<br /><br />./gene.txt<br />./Gene.txt<br /><br />4. Find Directories Using Name<br /><br />Find all directories whose name is Gene in / directory.<br /><br /># find / -type d -name Gene<br /><br />/Gene<br /><br />5. Find fasta Files Using Name<br /><br />Find all php files whose name is gene.fasta in a current working directory.<br /><br /># find . -type f -name gene.fasta<br /><br />./gene.fasta<br /><br />6. Find all PHP Files in Directory<br /><br />Find all fasta files in a directory.<br /><br /># find . -type f -name "*.fasta"<br /><br />./gene.fasta<br />./cancer.fasta<br />./allgene.fasta<br /><br /><strong>Part II &ndash; Find Files Based on their Permissions</strong><br />7. Find Files With 777 Permissions<br /><br />Find all the files whose permissions are 777.<br /><br /># find . -type f -perm 0777 -print<br /><br />8. Find Files Without 777 Permissions<br /><br />Find all the files without permission 777.<br /><br /># find / -type f ! -perm 777<br /><br />9. Find SGID Files with 644 Permissions<br /><br />Find all the SGID bit files whose permissions set to 644.<br /><br /># find / -perm 2644<br /><br />10. Find Sticky Bit Files with 551 Permissions<br /><br />Find all the Sticky Bit set files whose permission are 551.<br /><br /># find / -perm 1551<br /><br />11. Find SUID Files<br /><br />Find all SUID set files.<br /><br /># find / -perm /u=s<br /><br />12. Find SGID Files<br /><br />Find all SGID set files.<br /><br /># find / -perm /g+s<br /><br />13. Find Read Only Files<br /><br />Find all Read Only files.<br /><br /># find / -perm /u=r<br /><br />14. Find Executable Files<br /><br />Find all Executable files.<br /><br /># find / -perm /a=x<br /><br />15. Find Files with 777 Permissions and Chmod to 644<br /><br />Find all 777 permission files and use chmod command to set permissions to 644.<br /><br /># find / -type f -perm 0777 -print -exec chmod 644 {} \;<br /><br />16. Find Directories with 777 Permissions and Chmod to 755<br /><br />Find all 777 permission directories and use chmod command to set permissions to 755.<br /><br /># find / -type d -perm 777 -print -exec chmod 755 {} \;<br /><br />17. Find and remove single File<br /><br />To find a single file called gene.txt and remove it.<br /><br /># find . -type f -name "gene.txt" -exec rm -f {} \;<br /><br />18. Find and remove Multiple File<br /><br />To find and remove multiple files such as .fa or .gb, then use.<br /><br /># find . -type f -name "*.fa" -exec rm -f {} \;<br /><br />OR<br /><br /># find . -type f -name "*.gb" -exec rm -f {} \;<br /><br />19. Find all Empty Files<br /><br />To file all empty files under certain path.<br /><br /># find /tmp -type f -empty<br /><br />20. Find all Empty Directories<br /><br />To file all empty directories under certain path.<br /><br /># find /tmp -type d -empty<br /><br />21. File all Hidden Files<br /><br />To find all hidden files, use below command.<br /><br /># find /tmp -type f -name ".*"<br /><br /><strong>Part III &ndash; Search Files Based On Owners and Groups</strong><br />22. Find Single File Based on User<br /><br />To find all or single file called gene.txt under / root directory of owner root.<br /><br /># find / -user root -name gene.txt<br /><br />23. Find all Files Based on User<br /><br />To find all files that belongs to user Rahul under /home directory.<br /><br /># find /home -user rahul<br /><br />24. Find all Files Based on Group<br /><br />To find all files that belongs to group Developer under /home directory.<br /><br /># find /home -group developer<br /><br />25. Find Particular Files of User<br /><br />To find all .txt files of user Rahul under /home directory.<br /><br /># find /home -user rahul -iname "*.txt"<br /><br /><strong>Part IV &ndash; Find Files and Directories Based on Date and Time</strong><br />26. Find Last 50 Days Modified Files<br /><br />To find all the files which are modified 50 days back.<br /><br /># find / -mtime 50<br /><br />27. Find Last 50 Days Accessed Files<br /><br />To find all the files which are accessed 50 days back.<br /><br /># find / -atime 50<br /><br />28. Find Last 50-100 Days Modified Files<br /><br />To find all the files which are modified more than 50 days back and less than 100 days.<br /><br /># find / -mtime +50 &ndash;mtime -100<br /><br />29. Find Changed Files in Last 1 Hour<br /><br />To find all the files which are changed in last 1 hour.<br /><br /># find / -cmin -60<br /><br />30. Find Modified Files in Last 1 Hour<br /><br />To find all the files which are modified in last 1 hour.<br /><br /># find / -mmin -60<br /><br />31. Find Accessed Files in Last 1 Hour<br /><br />To find all the files which are accessed in last 1 hour.<br /><br /># find / -amin -60<br /><br /><strong>Part V &ndash; Find Files and Directories Based on Size</strong><br />32. Find 50MB Files<br /><br />To find all 50MB files, use.<br /><br /># find / -size 50M<br /><br />33. Find Size between 50MB &ndash; 100MB<br /><br />To find all the files which are greater than 50MB and less than 100MB.<br /><br /># find / -size +50M -size -100M<br /><br />34. Find and Delete 100MB Files<br /><br />To find all 100MB files and delete them using one single command.<br /><br /># find / -size +100M -exec rm -rf {} \;<br /><br />35. Find Specific Files and Delete<br /><br />Find all .gb files with more than 10MB and delete them using one single command.<br /><br /># find / -type f -name *.gb -size +10M -exec rm {} \;</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40703/%CF%80-cyc-a-reference-free-snp-discovery-application-using-parallel-graph-search</guid>
	<pubDate>Tue, 28 Jan 2020 03:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40703/%CF%80-cyc-a-reference-free-snp-discovery-application-using-parallel-graph-search</link>
	<title><![CDATA[Π-cyc: A Reference-free SNP Discovery Application using Parallel Graph Search]]></title>
	<description><![CDATA[<p>Reference free SNP search for comparative population genomics: multiple samples run simultanously. **experimental phase, compiles and runs with OpenMPI-1.8.8 with Intel Compiler only</p>
<p><span>Cycles enumeration (aka Bubbles) as part of de novo de bruijn graphs assembly using colours can be unpractical for large error prone genomes which makes the assembly process produce an excessive number of false positive cycles.&nbsp; Our solution is to search the graph in multicores shared memory parallel mode using graph decomposition then use filtering method to generate good quality SNPs.</span></p>
<p><a href="https://arxiv.org/abs/1809.06700">https://arxiv.org/abs/1809.06700</a></p>
<p><a href="https://github.com/redayounsi/2KP2P">https://github.com/redayounsi/2KP2P</a></p>
<blockquote>
<p>/2kp2omp/bin/main_2kp2_K63_C2 -i fastq_files.txt -o fungus_bub.fasta -r stat_fungus.txt -c cov_fungus_hash.txt -k 63 -h 20 -b 100 -g 600 -l 100 -f 16 -t 5.0 -x 1 -v 0 -p 1 -y 1 -u 1</p>
<p>&nbsp;</p>
</blockquote><p>Address of the bookmark: <a href="https://github.com/redayounsi/2KP2P" rel="nofollow">https://github.com/redayounsi/2KP2P</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</guid>
	<pubDate>Fri, 01 Dec 2017 04:10:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</link>
	<title><![CDATA[PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool]]></title>
	<description><![CDATA[<p><strong>PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.</strong></p>
<p><strong>Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.</strong></p>
<p>PLAST stands for&nbsp;<em>Parallel Local Sequence Alignment Search Tool&nbsp;</em>and is was&nbsp;<a href="http://www.biomedcentral.com/1471-2105/10/329" target="_blank">published in BMC Bioinformatics.</a></p>
<p>PLAST is a general purpose sequence comparison tool providing the following benefits:</p>
<ul>
<li>PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),</li>
<li>Reduces the processing time of sequences comparisons while providing highest quality results,</li>
<li>Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),</li>
<li>Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,</li>
<li>Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.</li>
</ul>
<p>https://plast.inria.fr/</p><p>Address of the bookmark: <a href="https://plast.inria.fr/" rel="nofollow">https://plast.inria.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44301/carrot2-clustering-engine</guid>
	<pubDate>Fri, 07 Apr 2023 13:11:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44301/carrot2-clustering-engine</link>
	<title><![CDATA[Carrot2 clustering engine]]></title>
	<description><![CDATA[<h2>&nbsp;</h2>
<p>This is the demo application of the&nbsp;<a href="http://project.carrot2.org/" target="_blank">Carrot<sup>2</sup>&nbsp;clustering engine</a>. It uses Carrot<sup>2</sup>'s algorithms to organize search results into thematic folders.</p>
<h3>User interfaces</h3>
<ul>
<li><span><a href="https://search.carrot2.org/#/search/:source">Web Search Clustering</a></span>&nbsp;organizes search results from public search engines into clusters; offers treemap- and pie-chart visualizations of the clusters.</li>
<li><span><a href="https://search.carrot2.org/#/workbench">Clustering Workbench</a></span>&nbsp;clusters content from local files in JSON or Excel format, Solr or Elasticsearch; allows tuning of clustering parameters and exporting results as Excel or JSON.</li>
</ul>
<h3>Search engines</h3>
<ul>
<li><span>Web</span>:&nbsp;<span>web search results provided by&nbsp;<a href="https://etools.ch/" target="_blank">etools.ch</a>. Extensive use may require special arrangements with the&nbsp;<a href="mailto:sschmid@comcepta.com" target="_blank">owner</a>&nbsp;of the etools.ch service.</span></li>
<li><span>PubMed</span>:&nbsp;<span>abstracts of medical papers from the PubMed database provided by NCBI.</span></li>
<li><span>Local file</span>:&nbsp;<span>content read from a local file in Carrot2 XML, JSON, CSV or Excel format.</span></li>
<li><span>Solr</span>:&nbsp;<span>queries an Apache Solr instance.</span></li>
<li><span>Elasticsearch</span>:&nbsp;<span>queries an Elasticsearch instance.</span></li>
</ul>
<h3>Clustering algorithms</h3>
<ul>
<li><span>Lingo</span>:&nbsp;<span>creates well-described flat clusters. Does not scale beyond a few thousand search results. Available as part of the open source&nbsp;<a href="http://project.carrot2.org/" target="_blank">Carrot<sup>2</sup>&nbsp;framework</a>.</span></li>
<li><span>STC</span>:&nbsp;<span>the classic search results clustering algorithm. Produces flat cluster with adequate description, very fast. Available as part of the open source&nbsp;<a href="http://project.carrot2.org/" target="_blank">Carrot<sup>2</sup>&nbsp;framework</a></span></li>
<li><span>k-means</span>:&nbsp;<span>base line clustering algorithm, produces bag-of-words style cluster descriptions. Available as part of the open source&nbsp;<a href="http://project.carrot2.org/" target="_blank">Carrot<sup>2</sup>&nbsp;framework</a></span></li>
</ul><p>Address of the bookmark: <a href="https://search.carrot2.org/#/search/web" rel="nofollow">https://search.carrot2.org/#/search/web</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</guid>
	<pubDate>Thu, 23 Nov 2017 09:55:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</link>
	<title><![CDATA[poRe: an R package for the visualization and analysis of nanopore sequencing data]]></title>
	<description><![CDATA[<p><strong>Motivation:</strong>&nbsp;The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.</p>
<p><strong>Results:</strong>&nbsp;Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.</p>
<p><strong>Availability and implementation:</strong>&nbsp;poRe is released as a package for R at&nbsp;<a href="http://sourceforge.net/projects/rpore/" target="">http://sourceforge.net/projects/rpore/</a>&nbsp;. A tutorial and further information are available at&nbsp;<a href="https://sourceforge.net/p/rpore/wiki/Home/" target="">https://sourceforge.net/p/rpore/wiki/Home/</a></p>
<p><strong>Contact:</strong><a href="mailto:mick.watson@roslin.ed.ac.uk" target="">mick.watson@roslin.ed.ac.uk</a></p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/1/114/2365693" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/1/114/2365693</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35249/gpopsim-a-simulation-tool-for-whole-genome-genetic-data</guid>
	<pubDate>Wed, 17 Jan 2018 03:47:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35249/gpopsim-a-simulation-tool-for-whole-genome-genetic-data</link>
	<title><![CDATA[GPOPSIM: a simulation tool for whole-genome genetic data]]></title>
	<description><![CDATA[<p><span>GPOPSIM is a simulation tool for pedigree, phenotypes, and genomic data, with a variety of population and genome structures and trait genetic architectures. It provides flexible parameter settings for a wide discipline of users, especially can simulate multiple genetically correlated traits with desired genetic parameters and underlying genetic architectures.</span></p><p>Address of the bookmark: <a href="https://github.com/SCAU-AnimalGenetics/GPOPSIM" rel="nofollow">https://github.com/SCAU-AnimalGenetics/GPOPSIM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</guid>
	<pubDate>Thu, 31 May 2018 09:35:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</link>
	<title><![CDATA[BFC: a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data]]></title>
	<description><![CDATA[BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes.

The BFC algorithm is a variant of the classical spectrum alignment algorithm introduced by Pevzner et al (2001). It uses an exhaustive search to find a k-mer path through a read that minimizes a heuristic objective function jointly considering penalties on correction, quality and k-mer support. This algorithm was first implemented in my fermi assembler and then refined a few times in fermi, fermi2 and now in BFC. In the k-mer counting phase, BFC uses a blocked bloom filter to filter out most singleton k-mers and keeps the rest in a hash table (Melsted and Pritchard, 2011). The use of bloom filter is how BFC is named, though other correctors such as Lighter and Bless actually rely more on bloom filter than BFC.

https://github.com/lh3/bfc<p>Address of the bookmark: <a href="https://github.com/lh3/bfc" rel="nofollow">https://github.com/lh3/bfc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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