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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27459?offset=30</link>
	<atom:link href="https://bioinformaticsonline.com/related/27459?offset=30" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30701/harvest</guid>
	<pubDate>Tue, 31 Jan 2017 10:57:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30701/harvest</link>
	<title><![CDATA[Harvest]]></title>
	<description><![CDATA[<p>Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.</p>
<p><a href="http://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="http://harvest.readthedocs.io/en/latest/_images/screen.png" alt="_images/screen.png" style="border: 0px;"></a><span></span></p>
<p><strong>Tools</strong></p>
<ul>
<li><a href="http://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
</ul>
<p><strong>Citation</strong></p>
<blockquote>
<div>Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15 (11), 1-15 [<a href="http://www.biomedcentral.com/content/pdf/s13059-014-0524-x.pdf">PDF</a>]</div>
</blockquote><p>Address of the bookmark: <a href="http://harvest.readthedocs.io/en/latest/index.html" rel="nofollow">http://harvest.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32726/ergo-20-bioinformatics-suites</guid>
	<pubDate>Tue, 16 May 2017 08:14:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32726/ergo-20-bioinformatics-suites</link>
	<title><![CDATA[ERGO 2.0 Bioinformatics suites]]></title>
	<description><![CDATA[<p>ERGO 2.0 provides a systems biology informatics toolkit centered on comparative genomics to capture, query, and visualize sequenced genomes. &nbsp;Using Igenbio's proprietary algorithms, and the most comprehensive genomic database integrated with the largest collection of microbial metabolic and non-metabolic pathways, ERGO&trade; assigns functions to genes, integrates genes into pathways, and identifies previously unknown or mischaracterized genes, cryptic pathways, and gene products.&nbsp;</p><p>Address of the bookmark: <a href="https://www.igenbio.com/ergo/" rel="nofollow">https://www.igenbio.com/ergo/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43670/useful-bioinformatics-analysis-tools</guid>
	<pubDate>Thu, 23 Dec 2021 23:10:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43670/useful-bioinformatics-analysis-tools</link>
	<title><![CDATA[Useful Bioinformatics Analysis Tools !]]></title>
	<description><![CDATA[<h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=cometa&amp;subpage=about">CoMeta</a></h3><p><strong>Classificier of reads from metagenomic sequencing experiments.</strong></p><p><span>&bull;&nbsp;&nbsp;Kawulok, J., Deorowicz, S.,&nbsp;</span><em>CoMeta: Classification of Metagenomes Using k-mers</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0121453">PLOS ONE,&nbsp;</a><span>2015; 10(4):1&ndash;23,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=CoMSA&amp;subpage=about">CoMSA</a></h3><p><strong>Compressor of multiple sequence alignments of proteins.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Walczyszyn, J., Debudaj-Grabysz, A.,&nbsp;</span><em>CoMSA: compression of protein multiple sequence alignment files</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty619">Bioinformatics,&nbsp;</a><span>2019; 35(2):22&ndash;234,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=dsrc&amp;subpage=about">DSRC</a></h3><p><strong>Compressor of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Roguski, L., Deorowicz, S.,&nbsp;</span><em>DSRC 2: Industry-oriented compression of FASTQ files</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/30/15/2213">Bioinformatics,&nbsp;</a><span>2014; 30(15):2213&ndash;2215,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Compression of DNA sequences in FASTQ format</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/">Bioinformatics,&nbsp;</a><span>2011; 27(6):860&ndash;862,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=famsa&amp;subpage=about">FAMSA</a></h3><p><strong>Multiple sequence alignment designed for huge families of proteins (even containing hundreds of thousands of sequences).</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A.,&nbsp;</span><em>FAMSA: Fast and accurate multiple sequence alignment of huge protein families</em><span>,&nbsp;</span><a href="http://www.nature.com/articles/srep33964">Scientific Reports,&nbsp;</a><span>2016; 6(33964):</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=fastore&amp;subpage=about">FaStore</a></h3><p><strong>Compressor of FASTQ files.</strong></p><p><span>&bull;&nbsp;&nbsp;Roguski, L., Ochoa, I., Hernaez, M., Deorowicz, S.,&nbsp;</span><em>FaStore - a space-saving solution for raw sequencing data</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty205">Bioinformatics,&nbsp;</a><span>2018; 34(16):2748&ndash;2756,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=fqsqueezer&amp;subpage=about">FQSqueezer</a></h3><p><strong>Experimental high-end compressor of FASTQ files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S.,&nbsp;</span><em>FQSqueezer: k-mer-based compression of sequencing data</em><span>,&nbsp;</span><a href="https://www.nature.com/articles/s41598-020-57452-6">Scientific Reports,&nbsp;</a><span>2020; 10(578):</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gdc&amp;subpage=about">GDC</a></h3><p><strong>Compressor of collections of genome sequences.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A., Niemiec, M.,&nbsp;</span><em>GDC 2: Compression of large collections of genomes</em><span>,&nbsp;</span><a href="http://www.nature.com/srep/2015/150625/srep11565/full/srep11565.html">Scientific Reports,&nbsp;</a><span>2015; 5(11565):1&ndash;12,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Robust relative compression of genomes with random access</em><span>,&nbsp;</span><a href="http://sun.aei.polsl.pl/REFRESH/bioinformatics.oxfordjournals.org/content/27/21/2979.abstract">Bioinformatics,&nbsp;</a><span>2011; 27(21):2979&ndash;2986,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gtc&amp;subpage=about">GTC</a></h3><p><strong>Genotype databases compressor with support for fast queries.</strong></p><p><span>&bull;&nbsp;&nbsp;Danek, A., Deorowicz, S.,&nbsp;</span><em>GTC: how to maintain huge genotype collections in a compressed form</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty023">Bioinformatics,&nbsp;</a><span>2018; 34(11):1834&ndash;1840,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gtshark&amp;subpage=about">GTShark</a></h3><p><strong>Genotypes compressor.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A.,&nbsp;</span><em>GTShark: Genotype compression in large projects</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btz508">Bioinformatics,&nbsp;</a><span>2019; 35(22):4791&ndash;4793,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=kmc&amp;subpage=about">KMC</a></h3><p><strong>Memory frugal&nbsp;<em>k</em>-mer counter.</strong></p><p><span>&bull;&nbsp;&nbsp;Kokot, M., Długosz, M., Deorowicz, S.,&nbsp;</span><em>KMC 3: counting and manipulating k -mer statistics</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btx304">Bioinformatics,&nbsp;</a><span>2017; 33(17):2759&ndash;2761,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Kokot, M., Grabowski, Sz., Debudaj-Grabysz, A.,&nbsp;</span><em>KMC 2: Fast and resource-frugal k-mer counting</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btv022">Bioinformatics,&nbsp;</a><span>2015; 31(10):1569&ndash;1576,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Grabowski, Sz.,&nbsp;</span><em>Disk-based k-mer counting on a PC</em><span>,&nbsp;</span><a href="http://www.biomedcentral.com/1471-2105/14/160">BMC Bioinformatics,&nbsp;</a><span>2013; 14():Article no. 160,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=kmer-db&amp;subpage=about">Kmer-db</a></h3><p><strong>Tool for estimation of evolutionary distances in a collection of genomes.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Gudys, A., Dlugosz, M., Kokot, M., Danek, A.,&nbsp;</span><em>Kmer-db: instant evolutionary distance estimation</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty610">Bioinformatics,&nbsp;</a><span>2019; 35(1):133&ndash;136,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=mugi&amp;subpage=about">MuGI</a></h3><p><strong>Index allowing queries for a collection of multiple genome sequences.</strong></p><p><span>&bull;&nbsp;&nbsp;Danek, A., Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Indexes of Large Genome Collections on a PC</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0109384">PLOS ONE,&nbsp;</a><span>2014; 9(10):e109384,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=orcom&amp;subpage=about">ORCOM</a></h3><p><strong>Experimental compressor of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Grabowski, Sz., Deorowicz, S., Roguski, L.,&nbsp;</span><em>Disk-based compression of data from genome sequencing</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2014/12/22/bioinformatics.btu844.abstract">Bioinformatics,&nbsp;</a><span>2014; 31(9):1389&ndash;1395,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=pgsa&amp;subpage=about">PgSA</a></h3><p><strong>Index allowing queries for a collection of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Kowalski, T., Grabowski, Sz., Deorowicz, S.,&nbsp;</span><em>Indexing arbitrary-length k-mers in sequencing reads</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0133198">PLOS ONE,&nbsp;</a><span>2015; 10(7):1&ndash;16,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=quickprobs&amp;subpage=about">QuickProbs</a></h3><p><strong>Multiple sequence alignment designed especially for GPU.</strong></p><p><span>&bull;&nbsp;&nbsp;Gudys, A., Deorowicz, S.,&nbsp;</span><em>QuickProbs 2: towards rapid construction of high-quality alignments of large protein families</em><span>,&nbsp;</span><a href="http://www.nature.com/articles/srep41553">Scientific Reports,&nbsp;</a><span>2017; 7(41553):</span><br /><span>&bull;&nbsp;&nbsp;Gudys, A., Deorowicz, S.,&nbsp;</span><em>QuickProbs &ndash; A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors</em><span>,&nbsp;</span><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0088901">PLOS ONE,&nbsp;</a><span>2014; 9(2):e88901,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=reckoner&amp;subpage=about">RECKONER</a></h3><p><strong>Read error corrector.</strong></p><p><span>&bull;&nbsp;&nbsp;Maciej Długosz, M., Deorowicz, S.,&nbsp;</span><em>RECKONER: read error corrector based on KMC</em><span>,&nbsp;</span><a href="https://academic.oup.com/bioinformatics/article-abstract/33/7/1086/2843893/RECKONER-read-error-corrector-based-on-KMC">Bioinformatics,&nbsp;</a><span>2017; 33(7):1086&ndash;1089,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=tgc&amp;subpage=about">TGC</a></h3><p><strong>Compressor of collections of genomes given in Variant Call Format (VCF) files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A., Grabowski, Sz.,&nbsp;</span><em>Genome compression: a novel approach for large collections</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2013/08/29/bioinformatics.btt460">Bioinformatics,&nbsp;</a><span>2013; 29(20):2572&ndash;2578,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=vcfshark&amp;subpage=about">VCFShark</a></h3><p><strong>Compressor of VCF files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A.,&nbsp;</span><em>GTShark: Genotype compression in large projects</em><span>,&nbsp;</span><a href="https://www.biorxiv.org/content/10.1101/2020.12.18.423437v1">biorxiv.org,&nbsp;</a><span>2020; ():</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=whisper&amp;subpage=about">Whisper</a></h3><p><strong>Experimental mapper of whole genome sequencing data.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Gudys, A.,&nbsp;</span><em>Whisper 2: indel-sensitive short read mapping</em><span>,&nbsp;</span><a href="https://doi.org/10.1101/2019.12.18.881292">bioRxiv.org,&nbsp;</a><span>2019; :</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz.,&nbsp;</span><em>Whisper: read sorting allows robust robust mapping of DNA sequencing data</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty927">Bioinformatics,&nbsp;</a><span>2019; 35(12):2043&ndash;2050,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz.,&nbsp;</span><em>Robust mapping of whole genome sequencing data</em><span>,&nbsp;</span><a href="https://meetings.cshl.edu/abstracts.aspx?meet=GENOME&amp;year=17">Poster at The Biology of Genomes Conference,&nbsp;</a><span>2017;</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44618/important-bioinformatics-tools</guid>
	<pubDate>Tue, 30 Jul 2024 05:03:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44618/important-bioinformatics-tools</link>
	<title><![CDATA[Important Bioinformatics Tools !]]></title>
	<description><![CDATA[<p><span>1. Ktrim: An extra-fast, accurate adapter trimmer for sequencing data. It processes FASTQ files from multiple lanes with minimal mismatching and over-trimming of adapters.</span><span><br /></span><span><br /></span><span>2. BWA MEM: A reliable alignment tool (particularly for mapping ALT contigs and HLA genes, which are not fully addressed in BWA-MEM2).</span><span><br /></span><span><br /></span><span>3. Sambamba markdup: Quickly marks or removes duplicate reads using Picard's criteria.</span><span><br /></span><span><br /></span><span>4. ichorCNA: Estimates the tumor DNA fraction in cell-free DNA from ultra-low-pass whole genome sequencing (0.1x coverage) based on copy number alterations (CNA).</span><span><br /></span><span><br /></span><span>5. Fragle: A deep learning method for quantifying ctDNA levels from cell-free DNA fragmentomic profiles. It detects TF as low as ~1% ctDNA and works with targeted genomic panel sequencing data.</span><span><br /></span><span><br /></span><span>6. AlfredQC: A quality control tool for high-throughput sequencing data. It assesses metrics like read quality scores, GC content, and duplication rates, visualized through detailed plots and summary statistics.</span><span><br /></span><span><br /></span><span>7. Mosdepth: A fast tool for calculating sequencing coverage depth, offering a quicker alternative to samtools/sambamba depth by processing BAM and CRAM files.</span><span><br /></span><span><br /></span><span>8. Bedtools: A versatile toolkit for genomics, enabling operations like intersect, merge, count, and shuffle on genomic intervals across formats such as BAM, BED, GFF/GTF, and VCF.</span><span><br /></span><span><br /></span><span>9. Datamash: A command-line tool for basic numeric, textual, and statistical operations on input data streams. It supports operations such as grouping, sorting, transposing, and performing arithmetic calculations on tabular data.</span><span><br /></span><span><br /></span><span>10.</span><span> </span><a href="http://gwf.app/" target="_self">gwf.app</a><span>: A pragmatic alternative to Snakemake. Developed at</span><span> </span><a href="https://www.linkedin.com/company/aarhus-university-denmark-/" target="_self"><span>Aarhus University</span></a><span>, this flexible, generic workflow tool builds and runs large scientific workflows.</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/7387/bioinformatics-software-for-biologists-in-the-genomics-era</guid>
	<pubDate>Sun, 22 Dec 2013 17:31:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/7387/bioinformatics-software-for-biologists-in-the-genomics-era</link>
	<title><![CDATA[Bioinformatics software for biologists in the genomics era]]></title>
	<description><![CDATA[<p>The genome sequencing revolution is approaching a landmark figure of 1000 completely sequenced genomes. Coupled with fast-declining, per-base sequencing costs, this influx of DNA sequence data has encouraged laboratory scientists to engage large datasets in comparative sequence analyses for making evolutionary, functional and translational inferences. However, the majority of the scientists at the forefront of experimental research are not bioinformaticians, so a gap exists between the user-friendly software needed and the scripting/programming infrastructure often employed for the analysis of large numbers of genes, long genomic segments and groups of sequences. We see an urgent need for the expansion of the fundamental paradigms under which biologist-friendly software tools are designed and developed to fulfill the needs of biologists to analyze large datasets by using sophisticated computational methods. We argue that the design principles need to be sensitive to the reality that comparatively small teams of biologists have historically developed some of the most popular biological software packages in molecular evolutionary analysis. Furthermore, biological intuitiveness and investigator empowerment need to take precedence over the current supposition that biologists should re-tool and become programmers when analyzing genome scale datasets.</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/23/14/1713.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/23/14/1713.full</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata</guid>
	<pubDate>Tue, 11 Jun 2019 21:27:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata</link>
	<title><![CDATA[Amity University Bioinformatics Summer Program - Kolkata]]></title>
	<description><![CDATA[<p>Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.</p><p>Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</guid>
	<pubDate>Sun, 09 Dec 2018 19:06:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</link>
	<title><![CDATA[DECIPHER; a software toolset for deciphering and managing biological sequences efficiently using the R]]></title>
	<description><![CDATA[<p><span>DECIPHER is a software toolset that can be used for deciphering and managing biological sequences efficiently using the&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;programming language. The&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;package is distributed as platform independent source code under the&nbsp;</span><a href="http://www.gnu.org/copyleft/gpl.html">GPL version 3 license</a><span>. Some functionality of the program is accessible online through web tools.</span></p>
<p><span style="font-size: medium; text-align: justify;">&nbsp;</span></p><p>Address of the bookmark: <a href="http://www2.decipher.codes/" rel="nofollow">http://www2.decipher.codes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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