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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44724?offset=240</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</guid>
	<pubDate>Tue, 08 Nov 2022 03:39:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</link>
	<title><![CDATA[Tools for RNA classification]]></title>
	<description><![CDATA[<p><span>barrnap</span>&nbsp;-&nbsp;<a href="https://github.com/tseemann/barrnap" target="_blank">https://github.com/tseemann/barrnap</a></p><p><span>CPAT</span>&nbsp;-&nbsp;<a href="https://github.com/liguowang/cpat" target="_blank">https://github.com/liguowang/cpat</a>,&nbsp;<a href="http://lilab.research.bcm.edu/" target="_blank">http://lilab.research.bcm.edu/</a>&nbsp;(web server)</p><p><span>CPC2</span>&nbsp;-&nbsp;<a href="https://github.com/gao-lab/CPC2_standalone" target="_blank">https://github.com/gao-lab/CPC2_standalone</a>,&nbsp;<a href="http://cpc2.gao-lab.org/" target="_blank">http://cpc2.gao-lab.org/</a>&nbsp;(web server)</p><p><span>Infernal</span>&nbsp;-&nbsp;<a href="http://eddylab.org/infernal/" target="_blank">http://eddylab.org/infernal/</a>,&nbsp;<a href="https://github.com/EddyRivasLab/infernal" target="_blank">https://github.com/EddyRivasLab/infernal</a></p><p><span>NCBI RefSeq</span>&nbsp;-&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">https://www.ncbi.nlm.nih.gov/refseq/</a></p><p><span>Rfam</span>&nbsp;-&nbsp;<a href="http://rfam.xfam.org/" target="_blank">http://rfam.xfam.org/</a>,&nbsp;<a href="https://docs.rfam.org/en/latest/index.html" target="_blank">https://docs.rfam.org/en/latest/index.html</a></p><p><span>SILVA</span>&nbsp;-&nbsp;<a href="https://www.arb-silva.de/" target="_blank">https://www.arb-silva.de/</a></p><p><span>RNAmmer</span>&nbsp;-&nbsp;<a href="http://www.cbs.dtu.dk/services/RNAmmer/" target="_blank">http://www.cbs.dtu.dk/services/RNAmmer/</a>&nbsp;(web server, standalone download link)</p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44716/exploring-rna-sequence-analysis-tools-for-every-bioinformatician</guid>
	<pubDate>Fri, 13 Dec 2024 04:03:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44716/exploring-rna-sequence-analysis-tools-for-every-bioinformatician</link>
	<title><![CDATA[Exploring RNA Sequence Analysis: Tools for Every Bioinformatician]]></title>
	<description><![CDATA[<p>RNA sequence analysis has become an essential part of modern biological research. From RNA-seq pipelines to specialized tools for specific RNA types, here's a comprehensive guide to tools you can use to make sense of RNA data.</p><h4><strong>1. RNA-Seq Analysis Pipelines</strong></h4><p>RNA-seq is one of the most popular techniques for studying RNA. These tools streamline processing raw sequence data:</p><ul>
<li><strong>FASTQC</strong>: For quality control of raw RNA-seq reads.</li>
<li><strong>Trimmomatic</strong>: For trimming and filtering RNA-seq reads.</li>
<li><strong>HISAT2/STAR</strong>: High-performance aligners for RNA-seq reads.</li>
<li><strong>FeatureCounts</strong>: For quantifying gene expression.</li>
<li><strong>DESeq2/EdgeR</strong>: For differential expression analysis.</li>
</ul><h4><strong>2. Transcriptome Assembly and Annotation</strong></h4><p>For analyzing transcriptomes from non-model organisms or assembling novel transcripts:</p><ul>
<li><strong>Trinity</strong>: For de novo transcriptome assembly.</li>
<li><strong>StringTie</strong>: For transcript assembly and quantification from RNA-seq alignments.</li>
<li><strong>TransDecoder</strong>: To predict coding regions within assembled transcripts.</li>
<li><strong>TAU</strong>: Tools for annotating non-coding and coding RNAs.</li>
</ul><h4><strong>3. Exploring Non-Coding RNA (ncRNA)</strong></h4><p>Non-coding RNAs play critical regulatory roles. Dedicated tools for studying them include:</p><ul>
<li><strong>Infernal</strong>: For identifying ncRNA sequences based on covariance models.</li>
<li><strong>Rfam</strong>: Database and tools for ncRNA families.</li>
<li><strong>miRDeep</strong>: For identifying microRNAs in RNA-seq datasets.</li>
</ul><h4><strong>4. RNA Structure and Motif Analysis</strong></h4><p>Structural biology of RNA helps in understanding its function:</p><ul>
<li><strong>RNAfold (ViennaRNA)</strong>: Predicts secondary structures from RNA sequences.</li>
<li><strong>RNAstructure</strong>: Tools for RNA secondary structure prediction and analysis.</li>
<li><strong>MEME Suite</strong>: For identifying motifs in RNA sequences.</li>
<li><strong>IntaRNA</strong>: For RNA-RNA interaction prediction.</li>
</ul><h4><strong>5. RNA Editing and Modifications</strong></h4><p>Epitranscriptomics is a growing field focusing on RNA modifications:</p><ul>
<li><strong>REDItools</strong>: For RNA editing analysis.</li>
<li><strong>m6Aboost</strong>: For identifying m6A modifications in RNA.</li>
</ul><h4><strong>6. Long-Read RNA Sequencing Analysis</strong></h4><p>Long-read technologies like Nanopore and PacBio are transforming RNA research:</p><ul>
<li><strong>FLAIR</strong>: For isoform-level analysis of long-read RNA-seq data.</li>
<li><strong>NanoMod</strong>: For detecting modifications in RNA from Nanopore sequencing.</li>
</ul><h4><strong>7. RNA-Protein Interactions</strong></h4><p>To study RNA-protein interactions and complexes:</p><ul>
<li><strong>RBPmap</strong>: For identifying RNA-binding protein motifs.</li>
<li><strong>PARalyzer</strong>: For analyzing PAR-CLIP data.</li>
</ul><h4><strong>8. Functional Enrichment Analysis</strong></h4><p>Understanding biological functions and pathways from RNA-seq data:</p><ul>
<li><strong>getENRICH</strong>: A tool designed for pathway enrichment analysis of non-model organisms (hypergeometric P-value calculation with FDR correction).</li>
<li><strong>ClusterProfiler</strong>: For GO and KEGG pathway enrichment analysis.</li>
</ul><h4><strong>9. Visualization and Data Sharing</strong></h4><p>Presenting and sharing RNA sequence analysis results effectively:</p><ul>
<li><strong>IGV</strong>: Genome browser for visualizing RNA-seq alignments.</li>
<li><strong>Circos</strong>: Circular visualization of RNA-seq data.</li>
<li><strong>DashBio</strong>: A Python library for creating bioinformatics visualizations.</li>
</ul><h4><strong>Conclusion</strong></h4><p>The bioinformatics landscape for RNA sequence analysis is vast, with tools catering to specific needs. Whether you&rsquo;re studying coding RNAs, non-coding RNAs, or exploring RNA-protein interactions, the right tools can transform your data into biological insights.</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/27321/slurm-basics</guid>
	<pubDate>Fri, 13 May 2016 04:42:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/27321/slurm-basics</link>
	<title><![CDATA[SLURM basics !]]></title>
	<description><![CDATA[<p><a href="http://bioinformaticsonline.com/bookmarks/view/27238/slurm" target="_blank">SLURM</a> is a queue management system and stands for Simple Linux Utility for Resource Management. SLURM was developed at the Lawrence Livermore National Lab and currently runs some of the largest compute clusters in the world.</p><p>SLURM is similar in many ways to most other queue systems. You write a batch script then submit it to the queue manager. The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.</p><p>SLURM has a number of valuable features compared to other job management systems:</p><ul>
<li><em>Kill and Requeue</em> SLURM&rsquo;s ability to kill and requeue is superior to that of other systems. It waits for jobs to be cleared before scheduling the high priority job. It also does kill and requeue on memory rather than just on core count.</li>
<li><em>Memory</em> Memory requests are sacrosanct in SLURM. Thus the amount of memory you request at run time is guaranteed to be there. No one can infringe on that memory space and you cannot exceed the amount of memory that you request.</li>
<li><em>Accounting Tools</em> SLURM has a back end database which stores historical information about the cluster. This information can be queried by the users who are curious about how much resources they have used.</li>
</ul><p><strong>Summary of SLURM commands</strong></p><p>The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.</p><table>
<tbody>
<tr><th>&nbsp;</th><th>SLURM</th><th>SLURM Example</th></tr>
<tr>
<td>Submit a batch serial job</td>
<td><a href="http://slurm.schedmd.com/sbatch.html">sbatch</a></td>
<td><code>sbatch runscript.sh</code></td>
</tr>
<tr>
<td>Run a script interatively</td>
<td><a href="http://slurm.schedmd.com/srun.html">srun</a></td>
<td><code>srun --pty -p interact -t 10 --mem 1000 /bin/bash /bin/hostname</code></td>
</tr>
<tr>
<td>Kill a job</td>
<td><a href="http://slurm.schedmd.com/scancel.html">scancel</a></td>
<td><code>scancel 999999</code></td>
</tr>
<tr>
<td>View status of queues</td>
<td><a href="http://slurm.schedmd.com/squeue.html">squeue</a></td>
<td><code>squeue -u akitzmiller</code></td>
</tr>
<tr>
<td>Check current job by id</td>
<td><a href="http://slurm.schedmd.com/squeue.html">sacct</a></td>
<td><code>sacct -j 999999</code></td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44720/a-beginners-guide-to-using-kraken-for-taxonomic-classification</guid>
	<pubDate>Fri, 13 Dec 2024 11:29:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44720/a-beginners-guide-to-using-kraken-for-taxonomic-classification</link>
	<title><![CDATA[A Beginner&#039;s Guide to Using Kraken for Taxonomic Classification]]></title>
	<description><![CDATA[<div>Kraken is a popular bioinformatics tool designed for fast and accurate taxonomic classification of metagenomic sequences. Its efficiency and precision make it a go-to resource for analyzing microbial communities, including bacteria, viruses, archaea, and fungi. Whether you're new to bioinformatics or experienced in the field, Kraken is an indispensable tool for taxonomic analysis.</div><div><div><div><div dir="auto"><div><div><p>In this blog, we&rsquo;ll walk through the basics of Kraken, from installation to running an analysis, and highlight its key features and applications.</p><h4><strong>What is Kraken?</strong></h4><p>Kraken is a sequence classification tool that assigns taxonomic labels to DNA sequences using exact k-mer matching. It uses a reference database of genomes, dividing sequences into k-mers and identifying matches in a computationally efficient way.</p><h4><strong>Key Features of Kraken</strong></h4><ul>
<li><strong>Speed</strong>: Kraken processes data much faster than alignment-based methods.</li>
<li><strong>Accuracy</strong>: It uses a precise k-mer matching algorithm for high-resolution taxonomic assignments.</li>
<li><strong>Scalability</strong>: It can handle large metagenomic datasets.</li>
<li><strong>Custom Databases</strong>: You can build and use custom databases tailored to your research needs.</li>
</ul><h4><strong>Installing Kraken</strong></h4><ol>
<li>
<p><strong>System Requirements</strong></p>
<ul>
<li>A Unix-based operating system (Linux/macOS).</li>
<li>Sufficient computational resources for database building (RAM and disk space).</li>
</ul>
</li>
<li>
<p><strong>Installation Steps</strong></p>
<ul>
<li>Clone the Kraken repository from GitHub:
<div>
<div>&nbsp;</div>
<div dir="ltr"><code>git <span style="font-size: 12.8px; font-weight: normal;">clone</span> https://github.com/DerrickWood/kraken.git <span style="font-size: 12.8px; font-weight: normal;">cd</span> kraken </code></div>
</div>
</li>
<li>Compile the Kraken binaries:
<div>
<div>&nbsp;</div>
<div dir="ltr"><code>make </code></div>
</div>
</li>
<li>Add Kraken to your PATH for easy access:
<div>
<div>&nbsp;</div>
<div dir="ltr"><code><span style="font-size: 12.8px; font-weight: normal;">export</span> PATH=<span style="font-size: 12.8px; font-weight: normal;">$PATH</span>:/path/to/kraken </code></div>
</div>
</li>
</ul>
</li>
</ol><h4><strong>Preparing a Database</strong></h4><p>Kraken requires a database of reference genomes. You can use a pre-built database or create a custom one.</p><ol>
<li>
<p><strong>Downloading a Pre-built Database</strong><br />Kraken offers pre-built databases, such as the <em>MiniKraken</em> database, which is lightweight and suitable for smaller datasets. Download it using:</p>
<div>
<div dir="ltr"><code>kraken-build --download-library minikraken </code></div>
</div>
</li>
<li>
<p><strong>Building a Custom Database</strong><br />To include specific genomes, download FASTA files and build the database:</p>
<div>
<div dir="ltr"><code>kraken-build --download-library bacteria --threads 4 --db my_database kraken-build --build --db my_database </code></div>
</div>
<p>This process may take considerable time and resources, depending on the size of the database.</p>
</li>
</ol><h4><strong>Running Kraken</strong></h4><p>Once the database is ready, you can classify sequences.</p><ol>
<li>
<p><strong>Basic Usage</strong><br />Use the following command to classify sequences:</p>
<div>
<div dir="ltr"><code>kraken --db my_database --threads 4 --fastq-input input_sequences.fastq --output kraken_output.txt </code></div>
</div>
<p>Key options:</p>
<ul>
<li><code>--db</code>: Specifies the database.</li>
<li><code>--threads</code>: Number of threads for parallel processing.</li>
<li><code>--fastq-input</code>: Indicates input file format (FASTQ/FASTA).</li>
</ul>
</li>
<li>
<p><strong>Interpreting Results</strong><br />Kraken generates an output file with columns for sequence IDs, taxonomic classifications, and the confidence score.</p>
</li>
</ol><h4><strong>Visualizing Kraken Results</strong></h4><p>Kraken results can be visualized using tools like <strong>Krona</strong> or converted to human-readable reports using <code>kraken-report</code>.</p><ol>
<li>
<p><strong>Generate a Report</strong></p>
<div>
<div dir="ltr"><code>kraken-report --db my_database kraken_output.txt &gt; kraken_report.txt </code></div>
</div>
</li>
<li>
<p><strong>Krona Visualization</strong><br />Install Krona and convert Kraken output for visualization:</p>
<div>
<div dir="ltr"><code>cut -f2,3 kraken_output.txt | ktImportTaxonomy -o krona_output.html </code></div>
</div>
<p>Open the HTML file in your browser to interactively explore the taxonomic classifications.</p>
</li>
</ol><h4><strong>Advanced Usage</strong></h4><ol>
<li>
<p><strong>Confidence Thresholds</strong><br />Adjust the confidence threshold for classification using the <code>--confidence</code> option. Higher values reduce false positives but may miss some true positives:</p>
<div>
<div dir="ltr"><code>kraken --db my_database --confidence 0.1 --fastq-input input.fastq </code></div>
</div>
</li>
<li>
<p><strong>Paired-End Reads</strong><br />For paired-end sequencing data, use:</p>
<div>
<div dir="ltr"><code>kraken --db my_database --paired reads_1.fastq reads_2.fastq </code></div>
</div>
</li>
<li>
<p><strong>Customizing K-mers</strong><br />Kraken allows you to set custom k-mer lengths during database building for specific applications.</p>
</li>
</ol><h4><strong>Applications of Kraken</strong></h4><ul>
<li><strong>Microbial Ecology</strong>: Characterizing microbial communities in soil, water, and the human microbiome.</li>
<li><strong>Pathogen Detection</strong>: Identifying pathogens in clinical samples.</li>
<li><strong>Fungal Research</strong>: Analyzing fungal diversity in metagenomic datasets.</li>
<li><strong>Environmental Monitoring</strong>: Tracking microbial populations in diverse habitats.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Kraken is a versatile and efficient tool for taxonomic classification in metagenomics. Its speed, accuracy, and flexibility make it a favorite among bioinformaticians. By following this guide, you can set up and use Kraken to unlock insights into microbial and fungal communities, paving the way for discoveries in ecology, medicine, and biotechnology.</p></div></div></div></div></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</guid>
	<pubDate>Thu, 09 Mar 2023 02:48:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</link>
	<title><![CDATA[Common steps for reads mapping !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis. Here are some general steps to follow for mapping reads to a genome:</p><ol>
<li>
<p>Choose a read mapper: There are many read mappers available, such as BWA, Bowtie, and HISAT2. Choose a mapper that is appropriate for your type of data and research question.</p>
</li>
<li>
<p>Index the reference genome: Before mapping reads, the reference genome needs to be indexed. This involves creating an index of the genome sequence that allows the mapper to quickly find matches to the reads. Most mappers have their own indexing tools.</p>
</li>
<li>
<p>Prepare the read data: The reads should be in a format that is compatible with the mapper. Most mappers accept FASTQ or BAM files. Depending on the quality of the data, it may need to be filtered or trimmed before mapping.</p>
</li>
<li>
<p>Run the mapper: The mapper is run with the command-line interface or using a graphical user interface. The specific command depends on the mapper being used, but typically involves specifying the input data, reference genome, and output file format.</p>
</li>
<li>
<p>Evaluate the mapping results: After the mapping is complete, the results should be evaluated. This includes assessing the quality of the mapping, such as the mapping rate, the number of mapped reads, and the mapping quality score.</p>
</li>
<li>
<p>Post-processing: Depending on the analysis being performed, post-processing of the mapped reads may be necessary. This can include filtering reads based on quality, removing duplicate reads, and calling variants.</p>
</li>
</ol><p>Overall, mapping reads to a reference genome is a complex process that requires careful consideration of the type of data, the research question, and the specific mapper being used.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43954/elgg-installation-steps</guid>
	<pubDate>Wed, 07 Sep 2022 00:43:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43954/elgg-installation-steps</link>
	<title><![CDATA[Elgg Installation steps !]]></title>
	<description><![CDATA[<p>Elgg is an open source social networking engine that allows the creation of social environments such as campus social networks and internal collaborative platforms for organizations. Elgg offers a number of social networking features including microblogging, messaging, file-sharing and groups. This tutorial will guide you through the process of installing Elgg on a Ubuntu 18.04 VPS.</p><h2 id="Prerequisites">Prerequisites</h2><ul>
<li>A fresh Vultr Cloud Compute instance with Ubuntu 18.04 and root access.</li>
</ul><h2 id="Step_1__Install_Apache__MySQL__and_PHP">Step 1: Install Apache, MySQL, and PHP</h2><p>Elgg requires MySQL, PHP, and a web server. Before you can install Elgg, you will need to install the Apache web server, MySQL, and PHP.</p><p>Update the repository list.</p><pre><code>apt-get update
</code></pre><p>Install the Apache web server.</p><pre><code>apt-get install apache2 -y
</code></pre><p>Install MySQL.</p><pre><code>apt-get install mysql-server -y
</code></pre><p>Complete the MySQL installation by executing the following command.</p><pre><code>/usr/bin/mysql_secure_installation
</code></pre><p>During the installation, you will be asked to enter a root password. Enter a secure password. This will be the MySQL root password.</p><pre><code>Would you like to setup VALIDATE PASSWORD plugin? [Y/N] N
New password: password
Re-enter new password: password
Remove anonymous users? [Y/N] Y
Disallow root login remotely? [Y/N] Y
Remove test database and access to it? [Y/N] Y
Reload privilege tables now? [Y/N] Y
</code></pre><p>Install PHP 7.2, as well as the PHP modules required by Elgg.</p><pre><code>apt-get install php7.2 libapache2-mod-php7.2 php7.2-common php7.2-sqlite3 php7.2-curl php7.2-intl php7.2-mbstring php7.2-xmlrpc php7.2-mysql php7.2-gd php7.2-xml php7.2-cli php7.2-zip -y
</code></pre><h2 id="Step_2__Create_a_MySQL_database_for_Elgg">Step 2: Create a MySQL database for Elgg</h2><p>Elgg will require a MySQL database. Log into the MySQL console.</p><pre><code>mysql -u root -p
</code></pre><p>When prompted for a password, enter the MySQL root password you set in step 1. Once you are logged in to the MySQL console, create a new database.</p><pre><code>CREATE DATABASE elgg;
</code></pre><p>Create a new MySQL user and grant it privileges to the newly created database. You can replace&nbsp;<code>username</code>&nbsp;and&nbsp;<code>password</code>&nbsp;with the username and password of your choice.</p><pre><code>GRANT ALL PRIVILEGES on elgg.* to 'username'@'localhost' identified by 'password';
FLUSH PRIVILEGES;
</code></pre><p>Exit the MySQL console.</p><pre><code>exit
</code></pre><h2 id="Step_3__Download_and_Install_Elgg">Step 3: Download and Install Elgg</h2><p>Download the latest version of Elgg.</p><pre><code>cd /var/www/html
rm -r index.html
wget https://elgg.org/download/elgg-2.3.7.zip
</code></pre><p>Unzip the downloaded archive and move the files to the root of the Apache web server.</p><pre><code>apt install unzip
unzip elgg-2.3.7.zip
mv ./elgg-2.3.7/* . &amp;&amp; rm elgg-2.3.7.zip &amp;&amp; rm -r elgg-2.3.7
</code></pre><p>Create a data directory for Elgg.</p><pre><code>sudo mkdir -p /var/www/html/data
</code></pre><p>Set the appropriate file permissions.</p><pre><code>sudo chown -R www-data:www-data /var/www/html/
sudo chmod -R 755 /var/www/html/
</code></pre><h2 id="Step_4__Configure_Apache_for_Elgg">Step 4: Configure Apache for Elgg</h2><p>Elgg requires the Apache rewrite module. Enable the Apache rewrite module.</p><pre><code>sudo a2enmod rewrite
</code></pre><p>Create an Apache configuration file for the Elgg installation.</p><pre><code>sudo nano /etc/apache2/sites-available/elgg.conf
</code></pre><p>Paste the following snippet to the file, replacing&nbsp;<code>example.com</code>&nbsp;with your own domain name.</p><pre><code>&lt;VirtualHost *:80&gt;
     DocumentRoot /var/www/html/
     ServerName example.com
     &lt;Directory /var/www/html/&gt;
          Options FollowSymlinks
          AllowOverride All
          Require all granted
     &lt;/Directory&gt;
     ErrorLog ${APACHE_LOG_DIR}/error.log
     CustomLog ${APACHE_LOG_DIR}/access.log combined
&lt;/VirtualHost&gt;
</code></pre><p>Enable the configuration and restart the Apache server.</p><pre><code> sudo a2ensite elgg.conf
 sudo systemctl restart apache2.service</code></pre>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</guid>
	<pubDate>Thu, 22 May 2014 07:18:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</link>
	<title><![CDATA[GenXPro GmbH]]></title>
	<description><![CDATA[<p><strong>GenXPro</strong>&nbsp;GMbH is service provider for entire spectrum of nucleotide-based information&nbsp;of any biological sample. By combining intelligent data reduction techniques and&nbsp;latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for&nbsp;transcriptomic-, genomic- or epigenomic research.</p><p><span><span><strong><span>GENXPRO GMBH</span>,&nbsp;</strong></span></span><span>ALTENH&Ouml;FERALLEE 3,&nbsp;</span><span>60438 FRANKFURT MAIN,&nbsp;</span><span>GERMANY</span></p><p><span><span><strong>Website</strong></span>:&nbsp;<a href="http://www.genxpro.info/products_and_services/"></a><a href="http://www.genxpro.info/products_and_services/">http://www.genxpro.info/products_and_services/</a></span></p><p><span><strong>PHONE</strong>: +49 (0)69- 95 73 97 10,&nbsp;FAX: +49 (0)69- 95 73 97 06</span></p><p><span>EMAIL: info@genxpro.de</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41394/ngsymposium-in-computational-biology</guid>
  <pubDate>Mon, 09 Mar 2020 06:00:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[NGSymposium in Computational Biology]]></title>
  <description><![CDATA[
<p>We have a great pleasure to invite you to the NGSymposium in Computational Biology to celebrate the 5th anniversary of the NGSchool Summer Schools. This international conference will make way for exchanging knowledge and experiences between experienced and early-stage researchers as well as bioinformaticians. The meeting will be held on 31.07 - 1.08.2020 in Warsaw. It will be a satellite event to the #NGSchool2020: Statistical Learning in Genomics. It will cover a wide range of topics from basic and applied biomedical sciences: bioinformatics, genomics, transcriptomics, computational biology, Machine Learning.</p>

<p>Registration of active participants will be open from February, 27 12 PM CET to April 17, 23:59 CET. In registration forms you will be asked for providing us with some basic information about yourself. You will also be able to submit your abstract. You can save your registration form after filling it partially and come back later to supply more data e.g. upload an abstract. Your registration will be completed only with the payment of the registration fee reaching our accounts - please make sure to transfer the money in advance!</p>

<p>Registration of passive participants will be open after closing of registration of active participants.</p>

<p>Details an registration: https://ngschool.eu/conference/</p>
]]></description>
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