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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41991?offset=320</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37610/applied-statistics-for-bioinformatics-using-r</guid>
	<pubDate>Thu, 30 Aug 2018 03:45:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37610/applied-statistics-for-bioinformatics-using-r</link>
	<title><![CDATA[Applied Statistics for Bioinformatics using R]]></title>
	<description><![CDATA[<p>The purpose of this book is to give an introduction into statistics in order to solve some problems of bioinformatics. Statistics provides procedures to explore and visualize data as well as to test biological hypotheses. The book intends to be introductory in explaining and programming elementary statistical concepts, thereby bridging the gap between high school levels and the specialized statistical literature</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37610" length="1368378" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44724/step-by-step-guide-to-detect-pirnas-using-bioinformatics</guid>
	<pubDate>Fri, 13 Dec 2024 11:41:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44724/step-by-step-guide-to-detect-pirnas-using-bioinformatics</link>
	<title><![CDATA[Step-by-Step Guide to Detect piRNAs Using Bioinformatics]]></title>
	<description><![CDATA[<p>Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNAs that play crucial roles in silencing transposable elements and regulating gene expression, particularly in germline cells. Detecting piRNAs involves identifying their unique characteristics, such as size, sequence motifs, and association with Piwi proteins, from high-throughput RNA sequencing data.</p><p>This blog provides a comprehensive step-by-step guide to detect piRNAs using bioinformatics tools and workflows.</p><h4><strong>Step 1: Prepare Your Data</strong></h4><ol>
<li>
<p><strong>Obtain RNA Sequencing Data</strong><br />Acquire raw small RNA-seq data in FASTQ format. Datasets can be sourced from repositories like <strong>NCBI SRA</strong>, <strong>EMBL-EBI</strong>, or specific small RNA sequencing projects.</p>
</li>
<li>
<p><strong>Quality Control (QC)</strong><br />Use <strong>FastQC</strong> to assess the quality of raw reads:</p>
<div>
<div dir="ltr"><code>fastqc reads.fastq </code></div>
</div>
<p>Evaluate the per-base quality, adapter content, and overrepresented sequences.</p>
</li>
<li>
<p><strong>Trimming and Adapter Removal</strong><br />Use tools like <strong>Cutadapt</strong> or <strong>Trim Galore!</strong> to remove adapters and low-quality bases:</p>
<div>
<div dir="ltr"><code>cutadapt -a TGGAATTCTCGGGTGCCAAGG -o trimmed_reads.fastq reads.fastq </code></div>
</div>
<p>Ensure the remaining reads are of high quality for downstream analysis.</p>
</li>
</ol><h4><strong>Step 2: Map Reads to the Genome</strong></h4><p>Mapping reads to the reference genome is crucial for identifying piRNA loci.</p><ol>
<li>
<p><strong>Reference Genome Preparation</strong><br />Download the genome assembly of your organism from databases like <strong>Ensembl</strong>, <strong>UCSC Genome Browser</strong>, or <strong>NCBI</strong>.</p>
</li>
<li>
<p><strong>Align Reads</strong><br />Use <strong>Bowtie</strong> or <strong>STAR</strong> for small RNA alignment:</p>
<div>
<div dir="ltr"><code>bowtie -v 1 -k 1 --best genome_index trimmed_reads.fastq -S aligned_reads.sam </code></div>
</div>
<ul>
<li><code>-v 1</code>: Allows one mismatch.</li>
<li><code>-k 1</code>: Reports the best alignment.</li>
</ul>
</li>
<li>
<p><strong>Convert SAM to BAM</strong><br />Convert and sort alignments using <strong>SAMtools</strong>:</p>
<div>
<div dir="ltr"><code>samtools view -Sb aligned_reads.sam | samtools sort -o sorted_reads.bam </code></div>
</div>
</li>
</ol><h4><strong>Step 3: Identify Small RNAs</strong></h4><p>piRNAs are characterized by their size (24&ndash;32 nt) and strand bias.</p><ol>
<li>
<p><strong>Extract Reads by Size</strong><br />Use tools like <strong>BEDtools</strong> or custom scripts to filter reads between 24 and 32 nt:</p>
<div>
<div dir="ltr"><code>bedtools bamtofastq -i sorted_reads.bam -fq all_reads.fastq seqkit seq -m 24 -M 32 all_reads.fastq &gt; piRNA_size_reads.fastq </code></div>
</div>
</li>
<li>
<p><strong>Check for Sequence Bias</strong><br />piRNAs often have a strong bias for a uridine at the 5&rsquo; end (1U bias). Use tools like <strong>WebLogo</strong> to visualize sequence motifs.</p>
</li>
</ol><h4><strong>Step 4: Detect Ping-Pong Signature</strong></h4><p>The ping-pong amplification loop is a hallmark of piRNA biogenesis, characterized by a 10 nt overlap between piRNAs on opposite strands.</p><ol>
<li>
<p><strong>Generate Overlap Statistics</strong><br />Use the <strong>piPipes</strong> tool or custom scripts to calculate overlap:</p>
<div>
<div dir="ltr"><code>python ping_pong_overlap.py sorted_reads.bam </code></div>
</div>
</li>
<li>
<p><strong>Visualize Overlap Distribution</strong><br />Plot the distribution of overlaps to confirm the presence of the 10 nt ping-pong signature.</p>
</li>
</ol><h4><strong>Step 5: Annotate piRNA Clusters</strong></h4><p>piRNAs are often generated from genomic clusters.</p><ol>
<li>
<p><strong>Cluster Identification</strong><br />Use tools like <strong>proTRAC</strong> or <strong>PIRANHA</strong> to identify piRNA-producing clusters:</p>
<div>
<div dir="ltr"><code>proTRAC.pl -s sorted_reads.bam -g genome.fa -o clusters </code></div>
</div>
</li>
<li>
<p><strong>Annotate Genomic Regions</strong><br />Annotate the identified clusters using gene annotation files (GTF/GFF). Tools like <strong>BEDtools intersect</strong> can help associate piRNA clusters with genes or transposable elements:</p>
<div>
<div dir="ltr"><code>bedtools intersect -a clusters.bed -b genome_annotation.gtf &gt; annotated_clusters.bed </code></div>
</div>
</li>
</ol><h4><strong>Step 6: Functional Analysis</strong></h4><p>Functional analysis of piRNAs can uncover their targets and regulatory roles.</p><ol>
<li>
<p><strong>Predict piRNA Targets</strong><br />Use tools like <strong>IntaRNA</strong> or <strong>RNAhybrid</strong> to predict interactions between piRNAs and potential target mRNAs:</p>
<div>
<div dir="ltr"><code>RNAhybrid -t target_transcripts.fa -q piRNAs.fa &gt; piRNA_targets.txt </code></div>
</div>
</li>
<li>
<p><strong>Enrichment Analysis</strong><br />Perform GO or KEGG enrichment analysis of target genes using tools like <strong>g:Profiler</strong> or <strong>DAVID</strong>.</p>
</li>
</ol><h4><strong>Step 7: Validation and Visualization</strong></h4><ol>
<li>
<p><strong>Validate piRNA Candidates</strong><br />Cross-check the identified piRNAs against known piRNA databases, such as <strong>piRBase</strong> or <strong>piRNAdb</strong>.</p>
</li>
<li>
<p><strong>Visualize Results</strong></p>
<ul>
<li>Use <strong>IGV</strong> (Integrative Genomics Viewer) to visualize piRNA alignment and clusters on the genome.</li>
<li>Generate heatmaps or circos plots to present piRNA distributions.</li>
</ul>
</li>
</ol><h4><strong>Step 8: Share and Publish Findings</strong></h4><ol>
<li>
<p><strong>Archive Data</strong><br />Submit sequencing data to public repositories like <strong>SRA</strong> or <strong>GEO</strong> with metadata specifying piRNA-related experiments.</p>
</li>
<li>
<p><strong>Publish Results</strong><br />Share findings in journals or conferences, emphasizing novel piRNA candidates, target genes, or regulatory mechanisms.</p>
</li>
</ol><h4><strong>Conclusion</strong></h4><p>Detecting piRNAs involves a combination of computational and analytical methods to identify these unique small RNAs and their roles in gene regulation and transposable element suppression. By following this step-by-step guide, you can confidently navigate the complexities of piRNA detection and contribute to the growing understanding of their biological significance.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38487/betsy-a-new-backward-chaining-expert-system-for-automated-development-of-pipelines-in-bioinformatics</guid>
	<pubDate>Mon, 17 Dec 2018 18:46:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38487/betsy-a-new-backward-chaining-expert-system-for-automated-development-of-pipelines-in-bioinformatics</link>
	<title><![CDATA[BETSY: A new backward-chaining expert system for automated development of pipelines in Bioinformatics]]></title>
	<description><![CDATA[<p>The BETSY provides a command-line interface and available at&nbsp;<a href="https://github.com/jefftc/changlab">https://github.com/jefftc/changlab</a>. A user first searches in the knowledge base for desired output and then BETSY develops an initial workflow to produce that data which is later examined by the user. The user can optimize the parameters, the algorithm to preprocess the data, and normalize it depending on the task.</p>
<p>Currently, BETSY consists of modules required for the microarray and next-generation sequencing data [4] such as expression analysis, classification, peak calling, and visualization.</p><p>Address of the bookmark: <a href="https://github.com/jefftc/changlab" rel="nofollow">https://github.com/jefftc/changlab</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/39603/tenure-track-position-in-bioinformatics-at-institute-of-neurobiology-unam-queretaro-mexico</guid>
  <pubDate>Mon, 10 Jun 2019 00:48:54 -0500</pubDate>
  <link></link>
  <title><![CDATA[Tenure Track position in Bioinformatics at Institute of Neurobiology, UNAM, Querétaro, México]]></title>
  <description><![CDATA[
<p>The Institute of Neurobiology UNAM (www.inb.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to develop an original research program in Bioinformatics with applications to neuroscience and to establish multidisciplinary collaboration with other members of the Institute. Applicants are expected to have a doctorate degree, postdoctoral experience related to bioinformatics or genome biology, and a strong track record of peer-reviewed publications. No previous experience in neuroscience is required.</p>

<p>Interested applicants must submit CV and addresses of three references to ataulfo@unam.mx.</p>

<p>Tenure Track position in Genomic Sciences  </p>

<p>Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM Juriquilla, Querétaro, México </p>

<p>The International Laboratory for Human Genome Research, LIIGH-UNAM (www.liigh.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to perform research, teaching and formation of human resources in the area of: “Genomics of Mendelian Diseases” </p>

<p>Applicants are expected to have a doctorate degree, postdoctoral experience related to the above mentioned area and a strong track record of peer-reviewed publications. Interested applicants must submit CV, email addresses of three references, and a three-page project to Dr. Rafael Palacios, Coordinator of LIIGH-UNAM (palacios@liigh.unam.mx) before June 21, 2019 ………………………………………………………………</p>

<p>Tenure Track position in Genomic Sciences </p>

<p>Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM Juriquilla, Querétaro, México </p>

<p>The International Laboratory for Human Genome Research, LIIGH-UNAM (www.liigh.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to perform research, teaching and formation of human resources in the area of: “Statistic Population Genomics and its Impact in Complex Diseases” </p>

<p>Applicants are expected to have a doctorate degree, postdoctoral experience related to the above mentioned area and a strong track record of peer-reviewed publications. Interested applicants must submit CV, email addresses of three references, and a three-page statement of research interests to Dr. Rafael Palacios, Coordinator of LIIGH-UNAM (palacios@liigh.unam.mx) before June 21, 2019</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</guid>
	<pubDate>Wed, 13 Nov 2019 05:00:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</link>
	<title><![CDATA[Industrial Training in Computer Aided Drug Designing (CADD)]]></title>
	<description><![CDATA[<p>Learn More about&nbsp; Computer Aided Drug Designing (CADD)!!!</p><p>#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,</p><h2 style="text-align: center;"><strong>Batch Starts From 18<sup>th</sup> November 2019</strong></h2><p>#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will&nbsp; learn from industry leaders&nbsp;how to apply these skills in life science &amp; have a command over software developing process &nbsp;by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41041/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-mfd</guid>
  <pubDate>Sat, 15 Feb 2020 06:13:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post Doc Computational Biology, Bioinformatics - Network Biology &amp; Data Science, NGS (m/f/d)]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df</p>

<p>Requirements<br />Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus<br />Ability to numerically process complex and large data sets<br />Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)<br />Experience in analyzing next-generation sequencing data sets using network biology<br />Scientific publication record in applied bioinformatics<br />Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35920/mesquite-a-modular-system-for-evolutionary-analysis</guid>
	<pubDate>Tue, 13 Mar 2018 06:54:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35920/mesquite-a-modular-system-for-evolutionary-analysis</link>
	<title><![CDATA[Mesquite: A modular system for evolutionary analysis]]></title>
	<description><![CDATA[<p><span>Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.</span></p>
<p><span>https://github.com/MesquiteProject/MesquiteCore</span></p><p>Address of the bookmark: <a href="http://mesquiteproject.org/" rel="nofollow">http://mesquiteproject.org/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41924/senior-scientist-bioinformatics-it-at-regional-centre-for-biotechnology</guid>
  <pubDate>Tue, 30 Jun 2020 22:04:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Scientist (Bioinformatics/ IT) at Regional Centre for Biotechnology]]></title>
  <description><![CDATA[
<p>Regional Centre for Biotechnology</p>

<p>An Institution of National Importance established by Dept. of<br />Biotechnology, Govt. of India Under the auspices of UNESCO</p>

<p>Advertisement No. RCB/IBDC/01/2020/Recruitment/HR</p>

<p>Recruitment For Contractual Positions Under The Project<br />Indian Biological Data Centre (IBDC) Phase-1</p>

<p>Regional Centre for Biotechnology (RCB) invites online applications from suitably qualified, dynamic, result-oriented and dedicated candidates for the following positions under the project Indian Biological Data Centre (BIDC) Phase-1 on contract basis:</p>

<p>Industry: Biotechnology</p>

<p>Location: Faridabad (Haryana, India)</p>

<p>Project Head - 1</p>

<p>Senior Scientist (Bioinformatics/ IT) - 1</p>

<p>For other details, visit: www.rcb.res.in. Last date for receipt of online application is 18th July 2020.</p>

<p>Registrar</p>

<p>Regional Centre for Biotechnology<br />Faridabad-Gurgaon Expressway,<br />Faridabad - 121001</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</guid>
	<pubDate>Thu, 30 May 2019 04:06:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</link>
	<title><![CDATA[snakepipes: A toolkit based on snakemake and python for analysis of NGS data]]></title>
	<description><![CDATA[<p><span><span>snakePipes are flexible and powerful workflows built using&nbsp;</span><a href="https://github.com/maxplanck-ie/snakepipes/blob/master/snakemake.readthedocs.io">snakemake</a><span>&nbsp;that simplify the analysis of NGS data.</span></span></p>
<ul>
<li>DNA-mapping*</li>
<li>ChIP-seq*</li>
<li>RNA-seq*</li>
<li>ATAC-seq*</li>
<li>scRNA-seq</li>
<li>Hi-C</li>
<li>Whole Genome Bisulfite Seq/WGBS</li>
</ul>
<p><span>(*Also available in "allele-specific" mode)</span></p>
<p><span>snakePipes can be installed via conda : </span></p>
<p><span>'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'. </span></p>
<p><span>Source code (</span><a href="https://github.com/maxplanck-ie/snakepipes" target="">https://github.com/maxplanck-ie/snakepipes</a><span>) and documentation (</span><a href="https://snakepipes.readthedocs.io/en/latest/" target="">https://snakepipes.readthedocs.io/en/latest/</a><span>) are available online.</span></p><p>Address of the bookmark: <a href="https://github.com/maxplanck-ie/snakepipes" rel="nofollow">https://github.com/maxplanck-ie/snakepipes</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42172/sr-scientist-bioinformatics-vacancies-at-indian-institute-of-toxicology-research-india</guid>
  <pubDate>Tue, 01 Sep 2020 07:21:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sr. Scientist Bioinformatics Vacancies at Indian Institute of Toxicology Research, India]]></title>
  <description><![CDATA[
<p>Start date of online Registration: Wednesday August 19, 2020 11:00 Hrs IST<br />Last date for Registration: Monday September 21, 2020 17:30 Hrs IST<br />Last date for submission of online application: Monday September 21, 2020 17:30 Hrs IST<br />Last date of Receipt of physical copy of application at CSIR-IITR: Tuesday October 05, 2020 17:30 Hrs IST</p>

<p>Pay Matrix Level-12<br />No. of Post-01<br />(UR)<br />Post – Sr. Scientist<br />Area Bioinformatics<br />Age limit : 37 years<br />PhD in Computational Biology/Bioinformatics with 2 years experience in desired area<br />Or<br />ME/M.Tech in Bioinformatics or Genome Informatics or Genetic Engineering with 3 years experience in desired area<br />Experience of understanding fundamental science behind Artificial Intelligence, machine learning, novel Artificial Intelligence algorithms and architectures, software engineering principles for Artificial Intelligence, natural language processing with proficiency in programming as evident by publications in SCI journals with high impact factor. To be part a group of scientists working in the area of genomics, running the central<br />bioinformatics facility, developing independent projects and providing bioinformatics support to the user scientists of the Institute.</p>

<p>More at </p>

<p>http://14.139.62.50/CSIR-IITR%20Scientist%20Recruitment%20Adv%202020.pdf</p>
]]></description>
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