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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42693?offset=30</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29305/miro-mirna-omics</guid>
	<pubDate>Tue, 04 Oct 2016 14:50:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29305/miro-mirna-omics</link>
	<title><![CDATA[MIRO : miRNA omics]]></title>
	<description><![CDATA[<p><span>The MIRO (the miRNA omics) pipeline is a flexible and powerful tool for the analysis of miRNA (or more generall short RNA) expression using short-read deep sequencing data. In its present implementation MIRO is especially adapted for the analysis of reads generated with the Illumina sequencing platform. MIRO allows to preprocess the Solexa-reads, map them flexibly to several reference genomes using one of four different mappers, create differential gene (miRNA) expression profiles and cluster reads using one of several algorithm. MIRO output is furthermore compatible with software such as genome browsers and miRDeep.</span></p><p>Address of the bookmark: <a href="http://seq.crg.es/download/software/Miro/" rel="nofollow">http://seq.crg.es/download/software/Miro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</guid>
	<pubDate>Thu, 16 May 2019 00:20:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</link>
	<title><![CDATA[iRNAD: a computational tool for identifying D modification sites in RNA sequence]]></title>
	<description><![CDATA[<p><span>iRNAD, for identifying D modification sites in RNA sequence. In this predictor, the RNA samples derived from five species were encoded by nucleotide chemical property and nucleotide density. Support vector machine was utilized to perform the classification.&nbsp;</span></p>
<p><span><a href="http://lin-group.cn/server/iRNAD/">http://lin-group.cn/server/iRNAD/</a></span></p><p>Address of the bookmark: <a href="http://lin-group.cn/server/iRNAD/" rel="nofollow">http://lin-group.cn/server/iRNAD/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42033/seastar-systematic-evaluation-of-alternative-start-site-in-rna</guid>
	<pubDate>Thu, 13 Aug 2020 09:54:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42033/seastar-systematic-evaluation-of-alternative-start-site-in-rna</link>
	<title><![CDATA[SEASTAR: Systematic Evaluation of Alternative STArt site in RNA]]></title>
	<description><![CDATA[<p>SEASTAR (Systematic Evaluation of Alternative STArt site in RNA) is a software package for Transcription Start Site (TSS) identification and quantification using only RNA-seq data. It assembles novel TSSs based only on RNA-Seq data and merges them with known TSSs from a public database. This package enables high-quality TSS identification that is comparable to the highly sophisticated CAGE technology. This package is particularly useful for finding novel TSSs that contribute to transcriptome complexity along with identifying differential promoter utilization.</p>
<p>version 1.0.0 - updates several descriptions and tests. To achieve v0.9.4, one can visit&nbsp;<a href="https://github.com/zhyqin/SEASTAR-0.9.4">https://github.com/zhyqin/SEASTAR-0.9.4</a>&nbsp;for download.</p><p>Address of the bookmark: <a href="https://github.com/Xinglab/SEASTAR" rel="nofollow">https://github.com/Xinglab/SEASTAR</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44705/pirna-and-bioinformatics-decoding-the-guardians-of-the-genome</guid>
	<pubDate>Sat, 07 Dec 2024 02:15:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44705/pirna-and-bioinformatics-decoding-the-guardians-of-the-genome</link>
	<title><![CDATA[piRNA and Bioinformatics: Decoding the Guardians of the Genome]]></title>
	<description><![CDATA[<p>In the symphony of small RNAs, PIWI-interacting RNAs (piRNAs) stand out as the protectors of genomic integrity. These small, non-coding RNAs play critical roles in silencing transposable elements, regulating gene expression, and maintaining germline stability. The rise of bioinformatics has revolutionized our understanding of piRNAs, enabling researchers to decipher their biogenesis, functions, and evolutionary significance.</p><h3>What Are piRNAs?</h3><p>piRNAs are the largest class of small non-coding RNAs, typically 24&ndash;32 nucleotides in length. Unlike microRNAs (miRNAs) and small interfering RNAs (siRNAs), piRNAs do not rely on Dicer enzymes for maturation. Instead, they are processed from long single-stranded precursors and associate with PIWI proteins, a subclass of the Argonaute protein family.</p><p>The primary functions of piRNAs include:</p><ol>
<li><strong>Silencing Transposable Elements</strong>: By targeting transposons, piRNAs prevent genomic instability, particularly in germline cells.</li>
<li><strong>Regulating Gene Expression</strong>: piRNAs modulate gene expression at transcriptional and post-transcriptional levels.</li>
<li><strong>Epigenetic Modulation</strong>: They guide epigenetic modifications, such as DNA methylation, to specific genomic loci.</li>
</ol><h3>Challenges in piRNA Research</h3><p>Studying piRNAs is fraught with challenges, including:</p><ul>
<li><strong>Short Length</strong>: Their small size complicates sequencing and alignment.</li>
<li><strong>Lack of Sequence Conservation</strong>: Unlike miRNAs, piRNAs exhibit limited sequence conservation across species.</li>
<li><strong>Complex Biogenesis</strong>: The intricate pathways of piRNA generation require sophisticated computational tools to unravel.</li>
</ul><h3>Bioinformatics: Illuminating the World of piRNAs</h3><p>Bioinformatics has emerged as an indispensable tool for studying piRNAs, facilitating their discovery, annotation, and functional analysis. Here's how bioinformatics is transforming piRNA research:</p><h4>1. <strong>Identification and Annotation</strong></h4><p>The discovery of piRNAs relies on next-generation sequencing (NGS) data. Bioinformatics tools such as <em>piRNApredictor</em> and <em>Piano</em> identify piRNA clusters and predict potential targets. Databases like piRBase and piRNAdb curate information about known piRNAs, their sequences, and associated proteins.</p><h4>2. <strong>Mapping and Alignment</strong></h4><p>piRNAs often originate from repetitive regions, making their alignment challenging. Tools like Bowtie and STAR handle the unique mapping requirements of piRNAs, enabling accurate identification of piRNA clusters in genomes.</p><h4>3. <strong>Functional Analysis</strong></h4><p>Bioinformatics approaches predict piRNA functions by analyzing their interactions with transposons, genes, and epigenetic marks. Algorithms such as TargetFinder and RIblast explore piRNA-mRNA interactions, shedding light on regulatory networks.</p><h4>4. <strong>Evolutionary Studies</strong></h4><p>piRNAs are evolutionarily diverse, reflecting their roles in species-specific genomic defense. Comparative genomics tools help trace the evolution of piRNA clusters and their associated PIWI proteins across species.</p><h4>5. <strong>Epigenomic Insights</strong></h4><p>piRNAs are key players in epigenetic regulation. Bioinformatics pipelines integrate piRNA data with chromatin immunoprecipitation sequencing (ChIP-seq) and DNA methylation data to uncover their role in shaping the epigenome.</p><h3>Case Study: piRNAs in Germline Integrity</h3><p>One of the hallmark functions of piRNAs is the suppression of transposable elements in the germline. For example, in <em>Drosophila melanogaster</em>, piRNAs target retrotransposons like <em>gypsy</em> and <em>copia</em>. Bioinformatics analyses revealed that these piRNAs guide PIWI proteins to transposon-derived RNA, ensuring genome stability during gametogenesis.</p><h3>Clinical Relevance of piRNAs</h3><p>Recent studies suggest that piRNAs may serve as biomarkers for diseases such as cancer, infertility, and neurodegenerative disorders. For instance:</p><ul>
<li><strong>Cancer</strong>: Dysregulated piRNA expression has been linked to tumorigenesis, making them potential targets for cancer therapies.</li>
<li><strong>Infertility</strong>: Aberrant piRNA pathways are implicated in male infertility due to their role in spermatogenesis.</li>
<li><strong>Neurodegeneration</strong>: piRNAs may regulate neuronal gene expression, highlighting their potential in neurological research.</li>
</ul><h3>Future Directions</h3><p>The integration of bioinformatics with emerging technologies offers exciting opportunities for piRNA research:</p><ul>
<li><strong>Single-Cell Sequencing</strong>: Unveiling cell-specific piRNA expression and function.</li>
<li><strong>Machine Learning</strong>: Predicting piRNA functions and targets with greater accuracy.</li>
<li><strong>CRISPR-Based Tools</strong>: Editing piRNA clusters to explore their roles in vivo.</li>
</ul><h3>Conclusion</h3><p>piRNAs are the unsung guardians of the genome, safeguarding genetic material from transposable elements and contributing to gene regulation and epigenetic programming. Bioinformatics has opened the floodgates of discovery, unraveling the complexities of piRNAs and their myriad roles in biology and disease.</p><p>As we continue to decode the piRNA landscape, these small RNAs promise to unveil big secrets about genome stability, evolution, and human health, cementing their place as a fascinating frontier in molecular biology.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38053/swgis-v20-a-seqword-genomic-island-sniffer</guid>
	<pubDate>Thu, 01 Nov 2018 12:35:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38053/swgis-v20-a-seqword-genomic-island-sniffer</link>
	<title><![CDATA[swgis v2.0 : a seqword genomic island sniffer]]></title>
	<description><![CDATA[<p><strong>swgis v2.0</strong>&nbsp;is the modified version of the seqword genomic island sniffer. this version is specifically optimized for predicting genomic islands in eukaryotic genomes. swgis v2.0 was tested on several eukaryotic species of different lineages. all identified genomic islands were deposited in the&nbsp;<a href="http://eugi.bi.up.ac.za/" title="Go to EuGI database">eugi database</a>.</p>
<p><a href="http://eugi.bi.up.ac.za/download_swgis/swgisv2.0.zip" title="Download SWGIS v2.0">download swgis v2.0</a></p><p>Address of the bookmark: <a href="http://eugi.bi.up.ac.za/eugi_download_swgis.php" rel="nofollow">http://eugi.bi.up.ac.za/eugi_download_swgis.php</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/989/bioinformatics-approach-to-boar-taint</guid>
	<pubDate>Wed, 17 Jul 2013 15:50:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/989/bioinformatics-approach-to-boar-taint</link>
	<title><![CDATA[Bioinformatics approach to Boar Taint]]></title>
	<description><![CDATA[<p><span>Meat products obtained from intact male pigs often produce offensive smell or odour which is recognized as a complex genetic trait called boar taint.Androstenone and Skatole&nbsp;in the fat primarily cause boar taint. Metabolism of androstenone and sex steroids share a common pathway which makes removal of boar taint a very challenging task. Castration is a traditional solution to remove boar taint but it also results in bad quality of meat due to low level of steroids which is objectionable to many consumers. Detected functional variant(s) underlying boar taint compounds can be used as genetic markers in selection of male pigs with reduced boar taint levels. Resequencing of a total of 47 samples belong to Norwegian Landrace (NL) and Duroc (D) pigs with varied boar taint levels were done in Illumina HiSeq2000 to &gt;10X average coverage. Short reads generated from these samples mapped to&nbsp;<em>Sus Scrofa</em>&nbsp;version 10.2 reference assembly using Bowtie2. Alignment file then used for calling SNPs and InDels inside previousy identified QTL regions on SSC5,13, and 7 with the aid of FreeBayes , a variant caller tool. A final list of SNPs was prepared after filtering SNPs on the basis of SNP quality, coverage of SNP allele, functional and structural annotation, and repeats, etc. Selected SNPs will be genotyped in sample population for validation and then used for constructing SNPs haplotypes in close linkage disequilibrium with QTLs and fine mapping of QTLs through association mapping of genotyped SNPs.</span><span>&nbsp;</span></p><p><span>&nbsp;</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/989" length="19688" type="image/jpeg" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4297/how-genes-are-regulated-transcription-factors</guid>
	<pubDate>Thu, 05 Sep 2013 16:54:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4297/how-genes-are-regulated-transcription-factors</link>
	<title><![CDATA[How Genes are Regulated: Transcription Factors]]></title>
	<description><![CDATA[<iframe src="http://player.vimeo.com/video/30034882?byline=0" width="" height="" frameborder="0" webkitAllowFullScreen allowFullScreen></iframe>Each cell in our body inherits the same master copy of DNA, but different cell types use it differently. Transcription Factors help influence which genes are used in which cell. Understanding how these dynamic proteins physically interact with DNA allows us to better understand and model their binding to DNA and their regulation of gene expression.  Scientific Direction by the Wasserman Lab at the University of British Columbia: http://www.cmmt.ubc.ca/research/investigators/wasserman/lab  Animation and editing by Blair Lyons of Stroma Studios: http://www.stromastudios.com]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4943/molecular-genetics-lecture</guid>
	<pubDate>Fri, 27 Sep 2013 04:24:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4943/molecular-genetics-lecture</link>
	<title><![CDATA[Molecular Genetics Lecture]]></title>
	<description><![CDATA[<p><span>"Robert Sapolsky makes interdisciplinary connections between behavioral biology and molecular genetic influences. He relates protein synthesis and point mutations to microevolutionary change, and discusses conflicting theories of gradualism and punctuated equilibrium and the influence of epigenetics on development theories."&nbsp;</span></p>
<p><span>"<span><strong>Robert Sapolsky</strong> is an American neuroendocrinologist, professor of biology, neuroscience, and neurosurgery at Stanford University, researcher and author" ----Wikipedia</span></span></p><p>Address of the bookmark: <a href="http://www.youtube.com/watch?v=_dRXA1_e30o" rel="nofollow">http://www.youtube.com/watch?v=_dRXA1_e30o</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8639/edit-dna</guid>
	<pubDate>Wed, 05 Mar 2014 02:27:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8639/edit-dna</link>
	<title><![CDATA[Edit DNA !!!]]></title>
	<description><![CDATA[<p>A genome-engineering tool known as Crispr may allow scientists to alter the DNA of humans, animals and plants, a research breakthrough that promises to make a significant impact on science and fighting diseases, according to a <a href="http://www.nytimes.com/2014/03/04/health/a-powerful-new-way-to-edit-dna.html">March 3 story in the <em>New York Times</em></a>. Scientists hope Crispr might also be used for genomic surgery, as it were, to correct errant genes that cause disease.</p><p>A rescently publication paper ( http://jb.asm.org/content/169/12/5429.long )shows significance of an unusual repeated DNA sequences next to a gene in a common bacterium, and their scientific significance. The sequences, it turns out, are part of a sophisticated immune system that bacteria use to fight viruses. And that system, whose very existence was unknown until about seven years ago, may provide scientists with unprecedented power to rewrite the code of life. This means a genome can be edited, much as a writer might change words or fix spelling errors. It allows &ldquo;customizing the genome of any cell or any species at will,&rdquo;.</p><p>Reference:</p><p>http://www.prweb.com/releases/2014/03/prweb11636031.htm</p><p>http://www.nytimes.com/2014/03/04/health/a-powerful-new-way-to-edit-dna.html?hpw&amp;rref=health</p><p>http://jb.asm.org/content/169/12/5429.long</p>]]></description>
	<dc:creator>Jit</dc:creator>
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