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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35059?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/35059?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</guid>
	<pubDate>Thu, 26 Jul 2018 04:51:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</link>
	<title><![CDATA[Nanopolis: polish a genome assembly]]></title>
	<description><![CDATA[<p><span>Software package for signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more (see Nanopolish modules, below).</span></p>
<p>Quickstart</p>
<p>http://nanopolish.readthedocs.io/en/latest/quickstart_consensus.html</p>
<p>Algorithms</p>
<p>http://simpsonlab.github.io/2017/06/30/nanopolish-v0.7.0/</p><p>Address of the bookmark: <a href="https://github.com/jts/nanopolish" rel="nofollow">https://github.com/jts/nanopolish</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36758/pbalign-maps-pacbio-reads-to-reference-sequences-and-saves-alignments-to-a-bam-file</guid>
	<pubDate>Thu, 24 May 2018 10:06:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36758/pbalign-maps-pacbio-reads-to-reference-sequences-and-saves-alignments-to-a-bam-file</link>
	<title><![CDATA[pbalign: maps PacBio reads to reference sequences and saves alignments to a BAM file]]></title>
	<description><![CDATA[pbalign aligns PacBio reads to reference sequences, filters aligned reads according to user-specific filtering criteria, and converts the output to either the SAM format or PacBio Compare HDF5 (e.g., .cmp.h5) format. The output Compare HDF5 file will be compatible with Quiver if --forQuiver option is specified.<p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/pbalign" rel="nofollow">https://github.com/PacificBiosciences/pbalign</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41148/pbmm2a-minimap2-frontend-for-pacbio-native-data-formats</guid>
	<pubDate>Tue, 18 Feb 2020 03:36:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41148/pbmm2a-minimap2-frontend-for-pacbio-native-data-formats</link>
	<title><![CDATA[pbmm2:A minimap2 frontend for PacBio native data formats]]></title>
	<description><![CDATA[<p><em>pbmm2</em> is a SMRT C++ wrapper for <a href="https://github.com/lh3/minimap2">minimap2</a>'s C API. Its purpose is to support native PacBio in- and output, provide sets of recommended parameters, generate sorted output on-the-fly, and postprocess alignments. Sorted output can be used directly for polishing using GenomicConsensus, if BAM has been used as input to <em>pbmm2</em>. Benchmarks show that <em>pbmm2</em> outperforms BLASR in sequence identity, number of mapped bases, and especially runtime. <em>pbmm2</em> is the official replacement for BLASR.</p><p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/pbmm2" rel="nofollow">https://github.com/PacificBiosciences/pbmm2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</guid>
	<pubDate>Mon, 10 Apr 2017 04:45:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</link>
	<title><![CDATA[WGS Celera Assembler version 8.3rc2]]></title>
	<description><![CDATA[<p>These are release notes for Celera Assembler version 8.3rc2, which was released on May 24, 2015.<br><br>This distribution package provides a stable, tested, documented version of the software.&nbsp; The distribution is usable on most Unix-like platforms, and some platforms have pre-compiled binary distributions ready for installation.<br><br>The source code package includes full source code (revision 4627), Makefiles, and scripts.&nbsp; A subset of the kmer package (http://kmer.sourceforge.net/, version r1994), used by some modules of Celera Assembler, is included.&nbsp; This distribution includes [http://samtools.sourceforge.net/ SAMtools], [http://www.cbcb.umd.edu/software/jellyfish/ Jellyfish 2.0], [https://github.com/pbjd/pbutgcns PBUTGCNS], [https://github.com/PacificBiosciences/pbdagcon PBDAGCON], [https://github.com/PacificBiosciences/BLASR BLASR], and parts of the [https://github.com/PacificBiosciences/FALCON/tree/v0.1.3 Falcon assembler].<br><br>Full documentation can be found online at http://wgs-assembler.sourceforge.net/.</p>
<p>Interesting scripts within it</p>
<p>urbe@urbo214b[bin] ls&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; []<br>-rwxrwxr-x 1 urbe urbe&nbsp; 11K Apr 10 11:41 addCNSToStore<br>-rwxrwxr-x 1 urbe urbe 575K Apr 10 11:41 addReadsToUnitigs<br>-rwxrwxr-x 1 urbe urbe 128K Apr 10 11:41 analyzeBest<br>-rwxrwxr-x 1 urbe urbe 257K Apr 10 11:41 analyzePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 analyzeScaffolds<br>-rwxrwxr-x 1 urbe urbe 224K Apr 10 11:41 asmOutputFasta<br>-rwxrwxr-x 1 urbe urbe 448K Apr 10 11:41 asmOutputStatistics<br>-rwxrwxr-x 1 urbe urbe 2,4K Apr 10 11:41 asmToAGP.pl<br>-rwxrwxr-x 1 urbe urbe 7,6M Apr 10 11:41 blasr<br>-rwxrwxr-x 1 urbe urbe 1,6M Apr 10 11:41 bogart<br>-rwxrwxr-x 1 urbe urbe 183K Apr 10 11:41 bogus<br>-rwxrwxr-x 1 urbe urbe 272K Apr 10 11:41 bogusness<br>-rwxrwxr-x 1 urbe urbe 247K Apr 10 11:41 buildPosMap<br>-rwxrwxr-x 1 urbe urbe 213K Apr 10 11:41 buildRefContigs<br>-rwxrwxr-x 1 urbe urbe 990K Apr 10 11:41 buildUnitigs<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:41 ca2ace.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 12K Apr 10 11:41 caqc_help.ini<br>-rwxrwxr-x 1 urbe urbe&nbsp; 61K Apr 10 11:41 caqc.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 23K Apr 10 11:41 cat-corrects<br>-rwxrwxr-x 1 urbe urbe&nbsp; 24K Apr 10 11:41 cat-erates<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 cgw<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 cgwDump<br>-rwxrwxr-x 1 urbe urbe 204K Apr 10 11:41 chimChe<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 chimera<br>-rwxrwxr-x 1 urbe urbe 220K Apr 10 11:41 classifyMates<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:41 classifyMatesApply<br>-rwxrwxr-x 1 urbe urbe 215K Apr 10 11:41 classifyMatesPairwise<br>-rwxrwxr-x 1 urbe urbe 366K Apr 10 11:41 computeCoverageStat<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 convert-fasta-to-v2.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 convertOverlap<br>-rwxrwxr-x 1 urbe urbe 119K Apr 10 11:41 convertSamToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 20K Apr 10 11:41 convertToPBCNS<br>-rwxrwxr-x 1 urbe urbe 197K Apr 10 11:41 correct-frags<br>-rwxrwxr-x 1 urbe urbe 259K Apr 10 11:41 correct-olaps<br>-rwxrwxr-x 1 urbe urbe 520K Apr 10 11:41 correctPacBio<br>-rwxrwxr-x 1 urbe urbe 540K Apr 10 11:41 ctgcns<br>-rwxrwxr-x 1 urbe urbe 162K Apr 10 11:40 deduplicate<br>-rwxrwxr-x 1 urbe urbe&nbsp; 37K Apr 10 11:41 demotePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 dumpCloneMiddles<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:41 dumpPBRLayoutStore<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 dumpSingletons<br>-rwxrwxr-x 1 urbe urbe 171K Apr 10 11:41 erate-estimate<br>-rwxrwxr-x 1 urbe urbe 221K Apr 10 11:40 estimate-mer-threshold<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 extendClearRanges<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 extendClearRangesPartition<br>-rwxrwxr-x 1 urbe urbe 205K Apr 10 11:40 extractmessages<br>-rwxrwxr-x 1 urbe urbe 7,2M Apr 10 11:41 falcon_sense<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 fastaToCA<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:40 fastqAnalyze<br>-rwxrwxr-x 1 urbe urbe 137K Apr 10 11:40 fastqSample<br>-rwxrwxr-x 1 urbe urbe&nbsp; 62K Apr 10 11:40 fastqSimulate<br>-rwxrwxr-x 1 urbe urbe 121K Apr 10 11:40 fastqSimulate-sort<br>-rwxrwxr-x 1 urbe urbe 246K Apr 10 11:40 fastqToCA<br>-rwxrwxr-x 1 urbe urbe 140K Apr 10 11:41 filterOverlap<br>-rwxrwxr-x 1 urbe urbe 341K Apr 10 11:40 finalTrim<br>-rwxrwxr-x 1 urbe urbe 228K Apr 10 11:41 fixUnitigs<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 fragmentDepth<br>-rwxrwxr-x 1 urbe urbe&nbsp; 29K Apr 10 11:41 fragsInVars<br>-rwxrwxr-x 1 urbe urbe 545K Apr 10 11:41 frgs2clones<br>-rwxrwxr-x 1 urbe urbe 398K Apr 10 11:40 gatekeeper<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:40 gatekeeperbench<br>-rwxrwxr-x 1 urbe urbe 167K Apr 10 11:40 gkpStoreCreate<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 gkpStoreDumpFASTQ<br>-rwxrwxr-x 1 urbe urbe 184K Apr 10 11:41 greedyFragmentTiling<br>-rwxrwxr-x 1 urbe urbe 1,6K Apr 10 11:41 greedy_layout_to_IUM<br>-rwxrwxr-x 1 urbe urbe 142K Apr 10 11:40 initialTrim<br>-rwxrwxr-x 1 urbe urbe 967K Apr 10 11:41 jellyfish<br>-rwxrwxr-x 1 urbe urbe 219K Apr 10 11:41 markRepeatUnique<br>-rwxrwxr-x 1 urbe urbe 273K Apr 10 11:40 markUniqueUnique<br>-rwxrwxr-x 1 urbe urbe 114K Apr 10 11:40 mercy<br>-rwxrwxr-x 1 urbe urbe 3,8K Apr 10 11:41 mergeqc.pl<br>-rwxrwxr-x 1 urbe urbe 422K Apr 10 11:40 merTrim<br>-rwxrwxr-x 1 urbe urbe 125K Apr 10 11:40 merTrimApply<br>-rwxrwxr-x 1 urbe urbe 376K Apr 10 11:40 meryl<br>-rwxrwxr-x 1 urbe urbe 176K Apr 10 11:41 metagenomics_ovl_analyses<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:41 olap-from-seeds<br>-rwxrwxr-x 1 urbe urbe 275K Apr 10 11:41 outputLayout<br>-rwxrwxr-x 1 urbe urbe 229K Apr 10 11:41 overlapInCore<br>-rwxrwxr-x 1 urbe urbe 144K Apr 10 11:40 overlap_partition<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStats<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStore<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:41 overlapStoreBucketizer<br>-rwxrwxr-x 1 urbe urbe 175K Apr 10 11:41 overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe&nbsp; 33K Apr 10 11:41 overlapStoreIndexer<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 overlapStoreSorter<br>-rwxrwxr-x 1 urbe urbe 604K Apr 10 11:40 overmerry<br>lrwxrwxrwx 1 urbe urbe&nbsp;&nbsp;&nbsp; 4 Apr 10 11:41 pacBioToCA -&gt; PBcR<br>-rwxrwxr-x 1 urbe urbe 131K Apr 10 11:41 PBcR<br>-rwxrwxr-x 1 urbe urbe 2,9M Apr 10 11:41 pbdagcon<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 pbutgcns<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 remove_fragment<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:40 removeMateOverlap<br>-rwxrwxr-x 1 urbe urbe 2,5K Apr 10 11:41 replaceUIDwithName-fastq<br>-rwxrwxr-x 1 urbe urbe 1,2K Apr 10 11:41 replaceUIDwithName-posmap<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 resolveSurrogates<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:41 rewriteCache<br>-rwxrwxr-x 1 urbe urbe 232K Apr 10 11:41 runCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 88K Apr 10 11:41 runCA-dedupe<br>-rwxrwxr-x 1 urbe urbe&nbsp; 14K Apr 10 11:41 runCA-overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe 3,6K Apr 10 11:41 run_greedy.csh<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:40 sffToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 13K Apr 10 11:40 show-corrects<br>-rwxrwxr-x 1 urbe urbe 557K Apr 10 11:41 splitUnitigs<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 terminator<br>drwxrwxr-x 2 urbe urbe 4,0K Apr 10 11:41 TIGR<br>-rwxrwxr-x 1 urbe urbe 526K Apr 10 11:41 tigStore<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracearchiveToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracedb-to-frg.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 44K Apr 10 11:41 trimFastqByQVWindow<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:40 uidclient<br>-rwxrwxr-x 1 urbe urbe 589K Apr 10 11:41 unitigger<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v8-to-v9<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v9-to-v10<br>-rwxrwxr-x 1 urbe urbe&nbsp; 854 Apr 10 11:41 utg2fasta<br>-rwxrwxr-x 1 urbe urbe 731K Apr 10 11:41 utgcns<br>-rwxrwxr-x 1 urbe urbe 561K Apr 10 11:41 utgcnsfix<br><br><br></p><p>Address of the bookmark: <a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page" rel="nofollow">http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator</guid>
	<pubDate>Wed, 24 May 2017 08:41:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator</link>
	<title><![CDATA[Grinder / Biogrinder - A versatile omics shotgun and amplicon sequencing read simulator]]></title>
	<description><![CDATA[<p><span>Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file. </span></p>
<p><span>Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/biogrinder/files/biogrinder/" rel="nofollow">https://sourceforge.net/projects/biogrinder/files/biogrinder/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</guid>
	<pubDate>Thu, 29 Apr 2021 23:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</link>
	<title><![CDATA[CoverM: Read coverage calculator for metagenomics]]></title>
	<description><![CDATA[<p>CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.</p>
<p>CoverM calculates coverage of genomes/MAGs&nbsp;<code>coverm genome</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-genome.html">help</a>) or individual contigs&nbsp;<code>coverm contig</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-contig.html">help</a>). Calculating coverage by read mapping, its input can either be BAM files sorted by reference, or raw reads and reference genomes in various formats.</p><p>Address of the bookmark: <a href="https://github.com/wwood/CoverM" rel="nofollow">https://github.com/wwood/CoverM</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37574/simlord-a-read-simulator-for-third-generation-sequencing-reads</guid>
	<pubDate>Wed, 22 Aug 2018 10:40:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37574/simlord-a-read-simulator-for-third-generation-sequencing-reads</link>
	<title><![CDATA[SimLoRD: A read simulator for third generation sequencing reads]]></title>
	<description><![CDATA[<p>SimLoRD is a read simulator for third generation sequencing reads and is currently focused on the Pacific Biosciences SMRT error model.</p>
<p>Reads are simulated from both strands of a provided or randomly generated reference sequence.</p>
<div id="rst-header-features">
<ul>
<li>The reference can be read from a FASTA file or randomly generated with a given GC content. It can consist of several chromosomes, whose structure is respected when drawing reads. (Simulation of genome rearrangements may be incorporated at a later stage.)</li>
<li>The read lengths can be determined in four ways: drawing from a log-normal distribution (typical for genomic DNA), sampling from an existing FASTQ file (typical for RNA), sampling from a a text file with integers (RNA), or using a fixed length</li>
<li>Quality values and number of passes depend on fragment length.</li>
<li>Provided subread error probabilities are modified according to number of passes</li>
<li>Outputs reads in FASTQ format and alignments in SAM format</li>
</ul>
</div><p>Address of the bookmark: <a href="https://bitbucket.org/genomeinformatics/simlord/" rel="nofollow">https://bitbucket.org/genomeinformatics/simlord/</a></p>]]></description>
	<dc:creator>Aaryan Lokwani</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44527/alvis-a-tool-for-contig-and-read-alignment-visualisation-and-chimera-detection</guid>
	<pubDate>Wed, 08 May 2024 07:02:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44527/alvis-a-tool-for-contig-and-read-alignment-visualisation-and-chimera-detection</link>
	<title><![CDATA[Alvis: a tool for contig and read ALignment VISualisation and chimera detection]]></title>
	<description><![CDATA[<p><span>Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in a variety of alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies.</span></p>
<p>More at&nbsp;https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04056-0</p><p>Address of the bookmark: <a href="https://github.com/SR-Martin/alvis" rel="nofollow">https://github.com/SR-Martin/alvis</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2335/embo-practical-course-bioinformatics-large-scale-data-at-shenzhen-china</guid>
  <pubDate>Wed, 14 Aug 2013 09:50:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[EMBO Practical Course, Bioinformatics, large-scale data, at Shenzhen, China]]></title>
  <description><![CDATA[
<p>This international advanced course will provide training on bioinformatics and statistics methods for genomic research. It will give insight into how biological knowledge can be generated from high-throughput sequencing (DNA-Seq, RNA-seq, ChIP-seq) experiments and will illustrate how to analyze such data. The course covers both the underlying statistical and algorithmic concepts, and the practice of how to automate and code such analyses using the scripting language R.</p>

<p>17 Nov 2013 -22 Nov 2013</p>

<p>More at http://events.embo.org/13-large-scale-data/</p>

<p>Online Registration: https://www.conference-service.com/pc13-47/welcome.cgi</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>

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