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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31351?offset=630</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35635/ete-3-reconstruction-analysis-and-visualization-of-phylogenomic-data</guid>
	<pubDate>Mon, 19 Feb 2018 06:46:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35635/ete-3-reconstruction-analysis-and-visualization-of-phylogenomic-data</link>
	<title><![CDATA[ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data]]></title>
	<description><![CDATA[<p><span>ETE v3, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics. </span></p>
<p><span>The new features include </span></p>
<p><span>(i) building gene-based and supermatrix-based phylogenies using a single command, </span></p>
<p><span>(ii) testing and visualizing evolutionary models, </span></p>
<p><span>(iii) calculating distances between trees of different size or including duplications, and </span></p>
<p><span>(iv) providing seamless integration with the NCBI taxonomy database. </span></p>
<p><span>ETE is freely available at&nbsp;</span><a href="http://etetoolkit.org/" target="">http://etetoolkit.org</a></p><p>Address of the bookmark: <a href="http://etetoolkit.org" rel="nofollow">http://etetoolkit.org</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28547/jrf-bioinformatics-at-iit-delhi</guid>
  <pubDate>Mon, 25 Jul 2016 03:26:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at IIT, Delhi]]></title>
  <description><![CDATA[
<p>No. IITD/IRD/RP03017/4254/Advertisement No.: IITD/IRD/093/2016<br />JRF Bioinformatics  job vacancies in Indian Institute of Technology Delhi (IIT Delhi)<br />Title : Elucidation of Pathologically Relevant miRNAs Responsible for Disease Progression and Resistance to Chemotherapy in Chronic Lymphocytic Leukemia (CLL) (RP03017)<br />Qualification : Candidates having first class B. Tech. / M.Sc. Degree or equivalent in Bioinformatics or Biotechnology with NET qualification. Desirable: Candidates having computer programming skills (C++, Python, Java, Web designing using Materialize frameworks, database management, offline software GUI development) with knowledge of Linux server environment and / or experience in next generation sequencing (NGS) data analysis, MD simulations will be preferred.<br />No. of Post : 01<br />Pay Scale : Rs.25,000/-<br />How to apply<br />Walk-in test / interview will be held on 04/08/2016, 03.00 p.m. at Committee Room No. 230, Block-I, Department of Biochemical Engineering &amp; Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi-110016.</p>

<p>More at http://ird.iitd.ac.in/sites/default/files/jobs/project/IITD-IRD-093-2016.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28577/research-associate-computer-sciences-recruitment-in-national-bureau-of-plant-genetic-resources</guid>
  <pubDate>Thu, 28 Jul 2016 04:39:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate (Computer Sciences) recruitment in National Bureau of Plant Genetic Resources]]></title>
  <description><![CDATA[
<p>Research Associate (Computer Sciences) recruitment in National Bureau of Plant Genetic Resources</p>

<p>Project: Indo-UK Centre for improvement of Nitrogen use efficiency in wheat Dr. Soma S. Marla, Pr. Scientist (Bioinformatics), Division of Genomic Resources, ICAR, NBPGR, ND.</p>

<p>Qualification: Ph.D. Degree in Computer Sciences/Bioinformatics OR 1. First class Master’s degree in any discipline of Plant Sciences with specialization in Computer Sciences/ Bioinformatics having 1st division or 60% marks or equivalent overall grade point average with at least two years of research experience as evidenced from Fellowship/ Associate ship. 2. NET qualification is essential for the candidates with 3+2 years B.Sc.+ M.Sc. Desirable: Demonstrated experience &amp; skills in database design, management, UNIX OS, in NGS data analysis. Experience substantiated by publications of high quality will be preferred.</p>

<p>No.of Post: 1</p>

<p>Pay Scale: Rs. 40,000 (Ph.D)/ Rs + 30 % HRA; Rs.38,000 ( Masters Degree 0 + 30 % HRA).</p>

<p>Age Limit : below 40 years for RA position<br />How to apply<br />Applicants for RA post should send their complete CV (Advance copy of the application may be sent by email to :soma.marla@icar.gov.in or ssmarl@yahoo.com, should enclose the copy of the research publications; one page summary of their achievement relevant to the post applied for; and should enclose two reference letters (one must be from the person with whom worked latest). Shortlisted candidate will be intimated for interview by email.</p>

<p>The candidates who wish to attend the walk-in interview are requested to bring with them five copies of the CV (one copy with photograph) as per the format given below. Also, the candidates should bring the original documents such as degree certificates, marks sheets, publications, thesis, experience certificate etc. for verification. </p>

<p>Date of Interview: 17.8.2016.</p>

<p>More at http://www.nbpgr.ernet.in/Downloadfile.aspx?EntryId=7133</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39875/lrsday-long-read-sequencing-data-analysis-for-yeasts</guid>
	<pubDate>Mon, 26 Aug 2019 18:07:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39875/lrsday-long-read-sequencing-data-analysis-for-yeasts</link>
	<title><![CDATA[LRSDAY: Long-read Sequencing Data Analysis for Yeasts]]></title>
	<description><![CDATA[<p><span>Long-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast,&nbsp;</span><em>Saccharomyces cerevisiae</em><span>, has many isolates currently being sequenced with long reads.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/yjx1217/LRSDAY" rel="nofollow">https://github.com/yjx1217/LRSDAY</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28618/jrf-bioinformatics-at-dpu-india</guid>
  <pubDate>Fri, 05 Aug 2016 03:06:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at DPU, India]]></title>
  <description><![CDATA[
<p>Advertisement for position of “JRF (Junior Research Fellow)” on DST research project “Molecular modeling and docking studies on Deguelin and its derivatives with cell cycle arrest, apoptosis and anti-angiogenesis pathway proteins in cancer cell signaling pathway”</p>

<p>Applications are invited on plain paper from eligible candidates along with biodata and copies of certificates in support of age, qualification and experience for the following position:</p>

<p>Particulars Description</p>

<p>1. Position &amp; No. JRF (Junior Research Fellow) 01</p>

<p>2. Title of the Project Molecular modeling and docking studies on Deguelin and its derivatives with cell cycle arrest, apoptosis and anti-angiogenesis pathway proteins in cancer cell signaling pathway</p>

<p>3. Tenure 3 years</p>

<p>4. Investigator Dr. K. V.Swamy</p>

<p>5. Institute Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Tathawade, Pune 411033.</p>

<p>5. Qualifications/Eligibility</p>

<p>Essential: NET (National Eligibility Test) qualified M. Sc Bioinformatics/ M. Tech Bioinformatics/M. Sc Biotechnology/M. Tech Biotechnology or Graduate degree in Professional course with NET qualification or Post graduation degree in professional course</p>

<p>The following examinations conducted by various Central Government Departments/Agencies are considered as National Eligibility Test (NET).</p>

<p>1. CSIR-UGC-LS <br />2. GATE (Graduate Aptitude Test in Engineering) <br />3. JAM (Joint Admission Test) <br />4. GPAT (Graduate Pharmacy Aptitude Test) <br />5. BET(Biotechnology Eligibility Test) <br />6. BINC(Bioinformatics National Consortium) <br />7. JEST( Joint Entrance Screening Test) <br />8. JGEEBILS(Joint Graduate Entrance Examination for Biology &amp; Interdisciplinary Life Sciences) <br />9. NBHM Ph.D scholarship Screening Test <br />10. ICMR- JRF Entrance Examination <br />11. AICE (ICAR-All India competitive Examination ) <br />(For all above examinations valid score considered at the time of interview)</p>

<p>Desirable: Knowledge and skills in Bioinformatics tools/ softwares</p>

<p>6. Monthly Emoluments Rs.25,000/ (As per DST-SERB rules)</p>

<p>7. Last date for submission of prescribed application 20/08/2016</p>

<p>Kindly send your applications to “Dr. K. V. Swamy, Asst.Professor, Dr. D. Y. Patil Biotechnology &amp; Bioinformatics Institute, Survey No. 87/88, Mumbai-Pune Express Way, Tathawade, Pune - 411033, Maharashtra, India”. Highlight the envelope with “Application for post of JRF (Junior Research Fellow)”.</p>

<p>Note: No TA/DA will be paid for attending the interview.</p>

<p>Advertisement: http://careers.dpu.edu.in/Biotech.aspx</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42419/biojupies-automatically-generates-rna-seq-data-analysis-notebooks</guid>
	<pubDate>Sun, 20 Dec 2020 11:43:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42419/biojupies-automatically-generates-rna-seq-data-analysis-notebooks</link>
	<title><![CDATA[BioJupies: Automatically Generates RNA-seq Data Analysis Notebooks]]></title>
	<description><![CDATA[<p>With BioJupies you can produce in seconds a customized, reusable, and interactive report from your own raw or processed RNA-seq data through a simple user interface</p>
<p>BioJupies now supports user accounts! Sign in from the top right corner of the page for access to unlimited private notebooks, RNA-seq datasets and alignment jobs.</p><p>Address of the bookmark: <a href="https://amp.pharm.mssm.edu/biojupies/" rel="nofollow">https://amp.pharm.mssm.edu/biojupies/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28802/research-associate-bioinformatics-recruitment-in-icgeb-new-delhi</guid>
  <pubDate>Tue, 16 Aug 2016 03:38:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics recruitment in ICGEB, New Delhi]]></title>
  <description><![CDATA[
<p>Research Associate Bioinformatics recruitment in ICGEB, New Delhi </p>

<p>Project :“Genetic Transformation and Development of Elite Transgenic Maize (Zea mays L.) for Biotic and Abiotic Stresses Tolerance”.</p>

<p>Qualification: Ph.D. degree in:Biotechnology/Bioinformatics/Biochemistry/Plant Molecular Biology/Plant Physiology/Botany or any related area with evidence of prior experience in maize transformation.</p>

<p>Additional experience in plant transformation of any cereal crop would be preferable.</p>

<p>The appointment would initially be for one year.</p>

<p>How to apply<br />Interested applicants should send their detailed CV including brief synopsis regarding the previous research experience (along withcontact email address by email) to: Dr. Tanushri Kaul (tanushri@icgeb.res.in). Group Leader, Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi-110 067.</p>

<p>Closing date for applications: 22 August 2016.</p>

<p>More at http://www.icgeb.org/vacancies.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44470/phyloherb-phylogenomic-analysis-pipeline-for-herbarium-specimens</guid>
	<pubDate>Wed, 21 Feb 2024 06:15:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44470/phyloherb-phylogenomic-analysis-pipeline-for-herbarium-specimens</link>
	<title><![CDATA[PhyloHerb: Phylogenomic Analysis Pipeline for Herbarium Specimens]]></title>
	<description><![CDATA[<p><span>What is PhyloHerb</span><span>: PhyloHerb is a wrapper program to process&nbsp;</span><span>genome skimming</span><span>&nbsp;data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include&nbsp;</span><span>low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming</span><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/lmcai/PhyloHerb/" rel="nofollow">https://github.com/lmcai/PhyloHerb/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28889/project-scientist-at-national-agri-food-biotechnology-institute-nabi</guid>
  <pubDate>Thu, 25 Aug 2016 05:49:36 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Scientist at National Agri-Food Biotechnology Institute (NABI)]]></title>
  <description><![CDATA[
<p>Advt. No. NABI/8(18)/2012-PME-3<br />Project Scientist recruitment in National Agri-Food Biotechnology Institute (NABI)<br />Project Title : “Transfer and Evaluation of Indian Banana with Pro-Vitamin A (PVA) Constructs”<br />Essential qualifications:  Ph.D. thesis submitted/awarded in any branch of life/plant sciences. Desirable qualification: a) Excellent academic record with research experience in area relevant to plant metabolic engineering, molecular biology and bioinformatics supported with high quality publications. b) Knowledge and experience of Chromatography and Mass Spectrometry based technological analysis of samples. c) Knowledge and experience of in-silico analysis such as trascriptomics, proteomics and genomics. c) Relevant research publications in reputed international journals with high impact factors.<br />No. of Post : 01<br />Age: 35 years<br />Emoluments:  Rs.40,000/- per month.<br />How to apply<br />Walk-In-Interview on 29/08/2016 at National Agri-Food Biotechnology Institute, C-127, Industrial Area, Phase VIII, S.A.S. Nagar, Mohali-160 071 Email: siddharth@nabi.res.in</p>

<p>More at http://www.nabi.res.in/Vacancies/NABI/ResearchFellowships/JRFSRFRA/2016/NABI8(18)2012-PME-3/Advt.pdf</p>
]]></description>
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	<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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