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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36592?offset=520</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</guid>
	<pubDate>Wed, 15 May 2024 14:24:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</link>
	<title><![CDATA[The ATCC Genome Portal]]></title>
	<description><![CDATA[<p><span>The ATCC Genome Portal (AGP,&nbsp;</span><a href="https://genomes.atcc.org/">https://genomes.atcc.org/</a><span>) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC&rsquo;s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.</span></p><p>Address of the bookmark: <a href="https://genomes.atcc.org/" rel="nofollow">https://genomes.atcc.org/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</guid>
	<pubDate>Tue, 02 Apr 2024 01:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</link>
	<title><![CDATA[Entire Human Genome Sequencing !]]></title>
	<description><![CDATA[<p>Cost-effective whole human genome sequencing has revolutionized the landscape of genetic research and personalized medicine by making comprehensive genetic analysis accessible to a wider population. Through advancements in sequencing technologies, such as next-generation sequencing (NGS), costs have significantly decreased, enabling researchers and healthcare providers to analyze an individual's complete genetic makeup with greater efficiency and affordability. This has profound implications for disease diagnosis, prognosis, and treatment, as it allows for the identification of genetic predispositions and the customization of healthcare interventions based on an individual's unique genetic profile. Moreover, as the cost continues to decline, the potential for population-scale genomic studies and large-scale screening programs becomes increasingly feasible, promising to further enhance our understanding of human genetics and improve healthcare outcomes on a global scale.</p><p>Here are few companies:</p><p>https://mynucleus.com/</p><p>https://myome.com/</p><p>https://nebula.org/whole-genome-sequencing-dna-test/</p>]]></description>
	<dc:creator>LEGE</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/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</guid>
	<pubDate>Tue, 04 Mar 2025 12:26:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</link>
	<title><![CDATA[Genomic architecture surrounding the fusion site of human chromosome 2]]></title>
	<description><![CDATA[<p>The article <strong>"Genomic Structure and Evolution of the Ancestral Chromosome Fusion Site in 2q13&ndash;2q14.1 and Paralogous Regions on Other Human Chromosomes (https://pmc.ncbi.nlm.nih.gov/articles/PMC187548/)"</strong> explores the genomic architecture surrounding the fusion site of human chromosome 2. This fusion event is a key evolutionary marker distinguishing humans from other great apes, as humans have 46 chromosomes while chimpanzees, gorillas, and orangutans possess 48. The fusion occurred through an end-to-end joining of two ancestral chromosomes, which remain separate in nonhuman primates.</p><h3><strong>Key Findings:</strong></h3><ol>
<li>
<p><strong>Chromosomal Fusion and Its Molecular Signature:</strong></p>
<ul>
<li>The fusion site is located at <strong>2q13&ndash;2q14.1</strong> and is characterized by <strong>degenerate telomeric sequences</strong> appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.</li>
<li>Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.</li>
</ul>
</li>
<li>
<p><strong>Extensive Duplications in the Surrounding Genomic Region:</strong></p>
<ul>
<li>The study identifies <strong>large-scale segmental duplications</strong> flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.</li>
<li>These duplications are predominantly located in <strong>subtelomeric and pericentromeric regions</strong>, suggesting their role in genomic instability and chromosomal evolution.</li>
</ul>
</li>
<li>
<p><strong>Paralogous Regions and Their Evolutionary Relationships:</strong></p>
<ul>
<li>A <strong>168-kilobase (kb) segment</strong> near the fusion site has <strong>98%&ndash;99% sequence identity</strong> with three regions on <strong>chromosome 9 (9pter, 9p11.2, and 9q13)</strong>.</li>
<li>Another <strong>67-kb region distal to the fusion site</strong> shows a high degree of homology to sequences in <strong>chromosome 22qter</strong>.</li>
<li>Additionally, a <strong>100-kb segment</strong> exhibits <strong>96% sequence identity</strong> with a region in <strong>chromosome 2q11.2</strong>.</li>
</ul>
</li>
<li>
<p><strong>Comparative Genomics and Evolutionary Implications:</strong></p>
<ul>
<li>By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.</li>
<li>The presence of specific repetitive elements within these duplicated segments serves as <strong>evolutionary markers</strong> that help infer their historical rearrangements.</li>
<li>Some of these <strong>duplicated regions are associated with chromosomal inversion breakpoints</strong>, potentially contributing to evolutionary changes in primates.</li>
<li>Recurrent <strong>structural rearrangements</strong> in these regions have been linked to human chromosomal disorders.</li>
</ul>
</li>
</ol><h3><strong>Conclusions and Implications:</strong></h3><ul>
<li>The findings provide valuable insights into <strong>the structural evolution of human chromosome 2</strong>, which played a crucial role in human speciation.</li>
<li>Understanding these <strong>segmental duplications</strong> and their evolutionary trajectories sheds light on <strong>genomic instability</strong>, which may contribute to <strong>human genetic diseases</strong>.</li>
<li>The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the <strong>evolutionary divergence of humans</strong> from other primates.</li>
</ul><p>This research advances our understanding of <strong>human genome evolution</strong> and offers a foundation for studying the effects of <strong>structural variants in genetic disorders</strong>.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41328/deephic-a-generative-adversarial-network-for-enhancing-hi-c-data-resolution</guid>
	<pubDate>Tue, 03 Mar 2020 01:12:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41328/deephic-a-generative-adversarial-network-for-enhancing-hi-c-data-resolution</link>
	<title><![CDATA[DeepHiC: A Generative Adversarial Network for Enhancing Hi-C Data Resolution]]></title>
	<description><![CDATA[<p><strong>DeepHiC</strong> is a GAN-based model for enhancing Hi-C data resolution. We developed this server for helping researchers to enhance their own low-resolution data by a few steps of clicks. <em>Ab initio</em> training could be performed according to our published <a href="https://github.com/omegahh/DeepHiC">code</a>. We provided trained models for various depth of low-coverage sequencing Hi-C data. The depth of input data is estimated by its distribution comparing with those of the downsampled Hi-C data we used in training</p><p>Address of the bookmark: <a href="http://sysomics.com/deephic" rel="nofollow">http://sysomics.com/deephic</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny</guid>
	<pubDate>Mon, 17 Feb 2020 05:38:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny</link>
	<title><![CDATA[Chromonomer: a tool set for repairing and enhancing assembled genomes through integration of genetic maps and conserved synteny]]></title>
	<description><![CDATA[<p>Chromonomer is a program designed to integrate a genome assembly with a genetic map. Chromonomer tries very hard to identify and remove markers that are out of order in the genetic map, when considered against their local assembly order; and to identify scaffolds that have been incorrectly assembled according to the genetic map, and split those scaffolds.</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/chromonomer/" rel="nofollow">http://catchenlab.life.illinois.edu/chromonomer/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41405/sequence-tube-maps-displays-multiple-genomic-sequences-in-the-form-of-a-tube-map</guid>
	<pubDate>Wed, 11 Mar 2020 01:12:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41405/sequence-tube-maps-displays-multiple-genomic-sequences-in-the-form-of-a-tube-map</link>
	<title><![CDATA[Sequence Tube Maps: displays multiple genomic sequences in the form of a tube map]]></title>
	<description><![CDATA[<p>A JavaScript module for the visualization of genomic sequence graphs. It automatically generates a "tube map"-like visualization of sequence graphs which have been created with <a href="https://github.com/vgteam/vg">vg</a>. (<a href="https://github.com/vgteam/vg">https://github.com/vgteam/vg</a>)</p>
<h3>Link to working demo: <a href="https://vgteam.github.io/sequenceTubeMap/">https://vgteam.github.io/sequenceTubeMap/</a></h3>
<p><img src="https://raw.githubusercontent.com/vgteam/sequenceTubeMap/master/images/header.png" alt="image" style="border: 0px; border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/vgteam/sequenceTubeMap" rel="nofollow">https://github.com/vgteam/sequenceTubeMap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:34:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</link>
	<title><![CDATA[Statistics and probability]]></title>
	<description><![CDATA[<h3><span>Topics</span></h3>
<div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/displaying-describing-data">Displaying and describing data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/modeling-distributions-of-data">Modeling distributions of data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/describing-relationships-quantitative-data">Describing relationships in quantitative data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/designing-studies">Designing studies</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/probability-library">Probability</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library">Random variables</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library">Sampling distributions</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/confidence-intervals-one-sample">Confidence intervals (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-one-sample">Significance tests (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-confidence-intervals-two-samples">Significance tests and confidence intervals (two samples)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/inference-categorical-data-chi-square-tests">Inference for categorical data (chi-square tests)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/advanced-regression-inference-transforming">Advanced regression (inference and tran</a></div>
</div><p>Address of the bookmark: <a href="https://www.khanacademy.org/math/statistics-probability" rel="nofollow">https://www.khanacademy.org/math/statistics-probability</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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