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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34715?offset=530</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</guid>
	<pubDate>Fri, 04 Mar 2022 00:14:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</link>
	<title><![CDATA[kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><tt>kebabs</tt><span>&nbsp;package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.</span></p>
<p>http://www.bioinf.jku.at/software/kebabs/</p>
<p>http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf</p><p>Address of the bookmark: <a href="http://www.bioinf.jku.at/software/kebabs/" rel="nofollow">http://www.bioinf.jku.at/software/kebabs/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44541/powerful-books-for-learning-data-analysis-with-r</guid>
	<pubDate>Tue, 28 May 2024 07:42:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44541/powerful-books-for-learning-data-analysis-with-r</link>
	<title><![CDATA[Powerful books for learning data analysis with R]]></title>
	<description><![CDATA[<p><span>R is powerful tool for data analysis, visualization, and machine learning. And it costs $0 to use! Here are six FREE books you can use to learn R today:</span></p>
<p><span>https://csgillespie.github.io/efficientR/</span></p>
<p><span>https://r-graphics.org/</span></p>
<p><span>https://rstudio-education.github.io/hopr/</span></p>
<p><span>https://r-pkgs.org/</span></p>
<p><span>https://r4ds.had.co.nz/</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://r-graphics.org/" rel="nofollow">https://r-graphics.org/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</guid>
	<pubDate>Tue, 25 Jul 2017 08:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</link>
	<title><![CDATA[MGRA: Breakpoint graphs and ancestral genome reconstructions]]></title>
	<description><![CDATA[<p>MGRA (Multiple Genome Rearrangements and Ancestors) is a tool for reconstruction of ancestor genomes and evolutionary history of extant genomes.</p>
<p>It takes as an input a set of genomes represented as sequences of genes (or synteny blocks) and produces such sequences for ancestral genomes at the internal nodes of the phylogenetic tree.</p>
<p>The phylogenetic tree may be also specified completely or partially, in the latter case MGRA can reconstruct conserved ancestral regions (CARs) of the ancestral genome of interest.</p>
<p>Since version 2 MGRA supports gene insertion and deletions in addition to genome rearrangements and allows the input genomes to have different gene content.</p>
<p>It also can reconstruct most plausible phylogenetic tree based on the rearrangement characters.</p><p>Address of the bookmark: <a href="http://mgra.cblab.org/" rel="nofollow">http://mgra.cblab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</guid>
	<pubDate>Sat, 18 Nov 2017 16:10:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</link>
	<title><![CDATA[Genomicus: genome browser that enables users to navigate in genomes in several dimensions]]></title>
	<description><![CDATA[<p>Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.</p>
<p>Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.</p>
<p>All the data on extant species displayed in this browser are from&nbsp;<a href="http://www.ensembl.org/">Ensembl</a>.</p><p>Address of the bookmark: <a href="http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl" rel="nofollow">http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</guid>
	<pubDate>Sat, 16 Dec 2017 17:37:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</link>
	<title><![CDATA[Tools for bacterial whole genome annotation]]></title>
	<description><![CDATA[<p><a href="http://rast.nmpdr.org/">RAST</a>&nbsp;&ndash;&nbsp;Web tool (upload contigs), uses the subsystems in the SEED database and&nbsp;provides detailed annotation and pathway analysis. Takes several hours per genome but I think this is the best way to get a high quality annotation (if you have only a few genomes to annotate).</p><p><a href="http://www.vicbioinformatics.com/software.prokka.shtml">Prokka</a>&nbsp;&ndash;&nbsp;Standalone command line tool, takes just a few minutes per genome.&nbsp;This is the best way to get good quality annotation in a flash, which is particularly useful if you have loads of genomes or need to annotate a pangenome or metagenome. Note however that the quality of functional information is not as good as RAST, and you&nbsp;will need several extra steps if you want to do&nbsp;functional profiling and pathway analysis of your genome(s)&hellip; which is in-built in RAST.</p><p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p><p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p><p><a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/">PGAP</a>: NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume.&nbsp; NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC453985">BEACON</a> (automated tool for Bacterial GEnome Annotation ComparisON), a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at:&nbsp;<a href="http://www.cbrc.kaust.edu.sa/BEACON/" target="pmc_ext">http://www.cbrc.kaust.edu.sa/BEACON/</a>.</p><p><a href="http://www.kegg.jp/blastkoala/">BlastKOLA</a>: Assigns K numbers to the user's sequence data by BLAST searches, respectively, against a nonredundant set of KEGG GENES. KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to this server and can be executed in an interactive mode. BlastKOALA is suitable for annotating fully sequenced genomes.</p><p><a href="http://www.sanger.ac.uk/science/tools/pagit">PAGIT</a>: Provides a toolkit for improving the quality of genome assemblies created via an assembly software. PAGIT compiled four tools: (i) ABACAS which classifies and orientates contigs and estimates the sizes of gaps between them; (ii) IMAGE uses paired-end reads to extend contigs and close gaps within the scaffolds; (iii) ICORN for identifying and correcting small errors in consensus sequences and; (iv) RATT for help annotation. The software was mainly created to analyze parasite genomes of up to about 300 Mb.</p><p><a href="http://www.yandell-lab.org/software/maker.html">MAKER: </a>A portable and easily configurable genome annotation pipeline. MAKER allows smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. It identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER's inputs are minimal and its ouputs can be directly loaded into a Generic Model Organism Database (GMOD). They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER is available for download and can be tested online via the MAKER Web Annotation Service (MWAS).</p><p><a href="https://www.sciencedirect.com/science/article/pii/S0167701215001207">MyPro</a> is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35883/arcs-scaffolding-genome-drafts-with-linked-reads</guid>
	<pubDate>Tue, 06 Mar 2018 16:35:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35883/arcs-scaffolding-genome-drafts-with-linked-reads</link>
	<title><![CDATA[ARCS: scaffolding genome drafts with linked reads]]></title>
	<description><![CDATA[<p><span>ARCS, an application that utilizes the barcoding information contained in linked reads to further organize draft genomes into highly contiguous assemblies. We show how the contiguity of an ABySS&nbsp;</span><em>H.sapiens</em><span>genome assembly can be increased over six-fold, using moderate coverage (25-fold) Chromium data. We expect ARCS to have broad utility in harnessing the barcoding information contained in linked read data for connecting high-quality sequences in genome assembly drafts.</span></p><p>Address of the bookmark: <a href="https://github.com/bcgsc/ARCS/" rel="nofollow">https://github.com/bcgsc/ARCS/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 11 May 2018 05:07:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads]]></title>
	<description><![CDATA[<p>MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>. MECAT performance were compared with&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>,&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>&nbsp;and&nbsp;<a href="http://canu.readthedocs.io/en/latest/">Canu(v1.3)</a>&nbsp;in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>&nbsp;and&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>.&nbsp;</p>
<p>https://www.nature.com/articles/nmeth.4432</p><p>Address of the bookmark: <a href="https://github.com/xiaochuanle/MECAT" rel="nofollow">https://github.com/xiaochuanle/MECAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36918/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Tue, 12 Jun 2018 08:14:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36918/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[P_RNA_scaffolder, a fast and accurate tool using paired-end RNA-sequencing reads to scaffold genomes. This tool aims to improve the completeness of both protein-coding and non-coding genes. After this tool was applied to scaffolding human contigs, the structures of both protein-coding genes and circular RNAs were almost completely recovered and equivalent to those in a complete genome, especially for long proteins and long circular RNAs.<p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies</guid>
	<pubDate>Thu, 26 Jul 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37416/gfinisher-a-new-strategy-to-refine-and-finish-bacterial-genome-assemblies</link>
	<title><![CDATA[GFinisher: a new strategy to refine and finish bacterial genome assemblies]]></title>
	<description><![CDATA[<p>GFinisher is an application tools for refinement and finalization of prokaryotic genomes assemblies using the bias of GC Skew to identify assembly errors and organizes the contigs/scaffolds with genomes references.</p>
<pre>java -Xms2G -Xmx4G -jar GenomeFinisher.jar  \
    -i target_contigs.fasta  \
    -ds alternative_assemblies.fasta -ref reference.fasta  \
    -o outputDirectory</pre><p>Address of the bookmark: <a href="http://gfinisher.sourceforge.net" rel="nofollow">http://gfinisher.sourceforge.net</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38023/mitos-improved-de-novo-metazoan-mitochondrial-genome-annotation</guid>
	<pubDate>Fri, 26 Oct 2018 08:25:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38023/mitos-improved-de-novo-metazoan-mitochondrial-genome-annotation</link>
	<title><![CDATA[MITOS: improved de novo metazoan mitochondrial genome annotation]]></title>
	<description><![CDATA[<p><span>Allows automatic annotation of metazoan mitochondrial genomes. MITOS is a pipeline designed to compute a consistent de novo annotation of the mitogenomic sequences. The software allows for a systematic error screening, the standardisation of gene name and gene boundary designation, anticodon labelling of tRNAs, and provides the means for the assessment of the validity of a gene assignment.</span></p><p>Address of the bookmark: <a href="http://mitos.bioinf.uni-leipzig.de/index.py" rel="nofollow">http://mitos.bioinf.uni-leipzig.de/index.py</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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