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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37409?offset=310</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</guid>
	<pubDate>Sun, 21 May 2023 19:33:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</link>
	<title><![CDATA[Genome Context Viewer (GCV)]]></title>
	<description><![CDATA[<p><span>The Genome Context Viewer (GCV) is a web-app that visualizes genomic context data provided by third party services. Specifically, it uses functional annotations as a unit of search and comparison. By adopting a common set of annotations, data-store operators can deploy federated instances of GCV, allowing users to compare genomes from different providers in a single interface.</span></p><p>Address of the bookmark: <a href="https://github.com/legumeinfo/gcv" rel="nofollow">https://github.com/legumeinfo/gcv</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</guid>
	<pubDate>Thu, 08 Aug 2024 23:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</link>
	<title><![CDATA[Tools to access the quality of your assembled genome !]]></title>
	<description><![CDATA[<ul dir="auto">
<li><a href="https://github.com/linsalrob/fasta_validator">FASTA VALIDATOR</a>&nbsp;+&nbsp;<a href="https://github.com/shenwei356/seqkit">SEQKIT RMDUP</a>: FASTA validation</li>
<li><a href="https://genometools.org/tools/gt_gff3validator.html">GENOMETOOLS GT GFF3VALIDATOR</a>: GFF3 validation</li>
<li><a href="https://github.com/PlantandFoodResearch/assemblathon2-analysis/blob/a93cba25d847434f7eadc04e63b58c567c46a56d/assemblathon_stats.pl">ASSEMBLATHON STATS</a>: Assembly statistics</li>
<li><a href="https://genometools.org/tools/gt_stat.html">GENOMETOOLS GT STAT</a>: Annotation statistics</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS ADAPTOR</a>: Adaptor contamination pass/fail</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS GX</a>: Foreign organism contamination pass/fail</li>
<li><a href="https://gitlab.com/ezlab/busco">BUSCO</a>: Gene-space completeness estimation</li>
<li><a href="https://github.com/tolkit/telomeric-identifier">TIDK</a>: Telomere repeat identification</li>
<li><a href="https://github.com/oushujun/LTR_retriever/blob/master/LAI">LAI</a>: Continuity of repetitive sequences</li>
<li><a href="https://github.com/DerrickWood/kraken2">KRAKEN2</a>: Taxonomy classification</li>
<li><a href="https://github.com/igvteam/juicebox.js">HIC CONTACT MAP</a>: Alignment and visualisation of HiC data</li>
<li><a href="https://github.com/mummer4/mummer">MUMMER</a>&nbsp;&rarr;&nbsp;<a href="http://circos.ca/documentation/">CIRCOS</a>&nbsp;+&nbsp;<a href="https://plotly.com/">DOTPLOT</a>&nbsp;&amp;&nbsp;<a href="https://github.com/lh3/minimap2">MINIMAP2</a>&nbsp;&rarr;&nbsp;<a href="https://github.com/schneebergerlab/plotsr">PLOTSR</a>: Synteny analysis</li>
<li><a href="https://github.com/marbl/merqury">MERQURY</a>: K-mer completeness, consensus quality and phasing assessment</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44754/early-genome-screening-the-new-health-horoscope</guid>
	<pubDate>Thu, 02 Jan 2025 19:44:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44754/early-genome-screening-the-new-health-horoscope</link>
	<title><![CDATA[Early Genome Screening: The New Health Horoscope!]]></title>
	<description><![CDATA[<p>In an era where precision medicine is reshaping healthcare, genome screening is emerging as the modern equivalent of a health horoscope. It offers insights into our biological "stars," unraveling predispositions to various conditions and empowering individuals with knowledge to navigate their health journeys proactively. But how reliable is this "horoscope," and how does it impact our lives?</p><h3>Understanding Genome Screening</h3><p>Genome screening involves analyzing an individual's DNA to identify genetic variations that may influence health and disease susceptibility. This can range from simple single-gene tests to comprehensive whole-genome sequencing. By peering into our genetic blueprint, we can uncover risks for conditions like cancer, diabetes, cardiovascular diseases, and even rare genetic disorders.</p><p>The process is straightforward: a saliva or blood sample is collected, and advanced sequencing technologies decipher the genetic code. The results provide a personalized health map, guiding lifestyle modifications, preventive measures, or medical interventions.</p><h3>A Shift from Reactive to Proactive Healthcare</h3><p>Traditional healthcare often focuses on treating diseases after they manifest. Genome screening flips this model on its head, enabling a shift toward prevention and early intervention. For instance:</p><ul>
<li>
<p><strong>Cancer Risk Management</strong>: Individuals with BRCA1 or BRCA2 gene mutations can opt for enhanced screening programs or preventive surgeries to mitigate their risk of breast and ovarian cancers.</p>
</li>
<li>
<p><strong>Cardiovascular Health</strong>: Genetic predispositions to conditions like familial hypercholesterolemia can prompt early cholesterol monitoring and lifestyle adjustments.</p>
</li>
<li>
<p><strong>Rare Diseases</strong>: Identifying carriers of genetic disorders can aid in family planning and reduce the incidence of inherited conditions.</p>
</li>
</ul><h3>The Ethical and Practical Concerns</h3><p>While genome screening offers incredible promise, it is not without challenges:</p><ol>
<li>
<p><strong>Accuracy and Interpretation</strong>: Genetic predisposition does not guarantee disease. Misinterpretation of results can lead to unnecessary anxiety or unwarranted medical interventions.</p>
</li>
<li>
<p><strong>Privacy and Data Security</strong>: Genetic data is highly sensitive. Ensuring robust data protection measures is crucial to prevent misuse.</p>
</li>
<li>
<p><strong>Accessibility and Equity</strong>: High costs and limited availability may restrict access to genome screening, exacerbating health disparities.</p>
</li>
</ol><h3>Balancing Science and Pseudoscience</h3><p>The comparison of genome screening to horoscopes isn&rsquo;t entirely unfounded. Both offer predictive insights, but the scientific foundation of genome screening distinguishes it from astrology. Unlike the alignment of celestial bodies, genetic predictions are based on rigorous data and evidence. However, the probabilistic nature of genetic predispositions underscores the importance of interpreting results in conjunction with clinical and lifestyle factors.</p><h3>The Road Ahead</h3><p>As genome screening becomes more affordable and integrated into routine healthcare, its potential to transform lives is immense. Policymakers, healthcare providers, and genetic counselors must collaborate to ensure ethical implementation, public awareness, and equitable access.</p><p>Imagine a future where your genetic "horoscope" is a trusted guide, not just a prediction. Early genome screening could help chart a healthier path for generations, making it a cornerstone of personalized medicine. After all, our genes might just hold the key to unlocking a future of better health and well-being.</p><p>&nbsp;</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34400/ioniser-tools-for-the-quality-assessment-of-data-produced-by-oxford-nanopore%E2%80%99s-minion-sequencer</guid>
	<pubDate>Thu, 23 Nov 2017 10:24:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34400/ioniser-tools-for-the-quality-assessment-of-data-produced-by-oxford-nanopore%E2%80%99s-minion-sequencer</link>
	<title><![CDATA[IONiseR:  tools for the quality assessment of data produced by Oxford Nanopore’s MinION sequencer]]></title>
	<description><![CDATA[<p>This package is intended to provide tools for the quality assessment of data produced by Oxford Nanopore&rsquo;s MinION sequencer. It includes a functions to generate a number plots for examining the statistics that we think will be useful for this task.</p>
<p>However, nanopore sequencing is an emerging and rapidly developing technology. It is not clear what will be most informative. We hope that&nbsp;<code>IONiseR</code>&nbsp;will provide a framework for visualisation of metrics that we haven&rsquo;t thought of, and welcome feedback at&nbsp;<a href="mailto:mike.smith@embl.de" target="_blank">mike.smith@embl.de</a>.</p>
<p>If you&rsquo;re not interested in the quality assement of the raw or event level data, and want to jump straight to the getting FASTQ format files from fast5 files you can go straight to the final section of this document.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/IONiseR/inst/doc/IONiseR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/IONiseR/inst/doc/IONiseR.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40972/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</guid>
	<pubDate>Mon, 10 Feb 2020 02:45:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40972/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</link>
	<title><![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Deepbinner is a tool for demultiplexing barcoded <a href="https://nanoporetech.com/">Oxford Nanopore</a> sequencing reads. It does this with a deep <a href="https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks/">convolutional neural network</a> classifier, using many of the <a href="https://towardsdatascience.com/neural-network-architectures-156e5bad51ba">architectural advances</a> that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and <a href="https://github.com/rrwick/Porechop">Porechop</a>), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Deepbinner" rel="nofollow">https://github.com/rrwick/Deepbinner</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34704/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization</guid>
	<pubDate>Mon, 18 Dec 2017 04:16:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34704/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization</link>
	<title><![CDATA[NanoSim: nanopore sequence read simulator based on statistical characterization.]]></title>
	<description><![CDATA[<p><span>NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data and allows for adjustments upon improvement of nanopore sequencing technology. The first step of NanoSim is read characterization, which provides a comprehensive alignment-based analysis and generates a set of read profiles serving as the input to the next step, the simulation stage. The simulation stage uses the model built in the previous step to produce in silico reads for a given reference genome. NanoSim is written in Python and R. The source files and manual are available at the Genome Sciences Centre website: http://www.bcgsc.ca/platform/bioinfo/software/nanosim</span></p>
<p><span>https://github.com/bcgsc/NanoSim</span></p><p>Address of the bookmark: <a href="http://www.bcgsc.ca/platform/bioinfo/software/nanosim" rel="nofollow">http://www.bcgsc.ca/platform/bioinfo/software/nanosim</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</guid>
	<pubDate>Fri, 10 Aug 2018 13:29:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</link>
	<title><![CDATA[FMLRC: a long-read error correction tool using the multi-string Burrows Wheeler Transform]]></title>
	<description><![CDATA[<p><span>FMLRC, or FM-index Long Read Corrector, is a tool for performing hybrid correction of long read sequencing using the BWT and FM-index of short-read sequencing data. Given a BWT of the short-read sequencing data, FMLRC will build an FM-index and use that as an implicit de Bruijn graph. Each long read is then corrected independently by identifying low frequency k-mers in the long read and replacing them with the closest matching high frequency k-mers in the implicit de Bruijn graph. In contrast to other de Bruijn graph based implementations, FMLRC is not restricted to a particular k-mer size and instead uses a two pass method with both a short "k-mer" and a longer "K-mer". This allows FMLRC to correct through low complexity regions that are computational difficult for short k-mers.</span></p><p>Address of the bookmark: <a href="https://github.com/holtjma/fmlrc" rel="nofollow">https://github.com/holtjma/fmlrc</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/915/researcher-in-computer-sciencebiology</guid>
  <pubDate>Mon, 15 Jul 2013 18:38:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Researcher in computer science/biology]]></title>
  <description><![CDATA[
<p>Researcher in Computer Science at the Computational Biology Unit - temporary employment</p>

<p>The Department of Informatics is a vacant position as a researcher in computer science, related to Computational Biology Unit (CBU), for 3 years.<br /> <br />The position is part of CBU Service Group and will focus on bioinformatic analysis project and especially the analysis of high-throughput data, including NGS (sequencing), and proteomics data.<br /> <br />The successful candidate will be part of the Norwegian bioinformatics platform's national helpdesk within the project ELIXIR.NO<br /> <br />Applicants must hold a PhD in a relevant subject such as computer science, mathematics, molecular biology and also possess expertise and experience in bioinformatics statistics and analysis of data from high-throughput molecular experiment.<br /> <br />Basic programming or scripting skills are required. Experience in Python, R, Perl, Linux-based operating systems and moreover knowledge of databases and web programming will be a strength for applicants.<br /> <br />We expect enthusiasm and independence and moreover the ability to work in an interdisciplinary team environment.<br /> <br />Good knowledge of English is required.<br /> <br />Salaries start at level 57 (code 1109/LR 24.1) by appointment. Further promotion occurs after<br />service seniority in the position (at grade 57-65). Of particularly highly qualified applicants may be considered a higher salary.<br /> <br />Further information about the position is available from the chair of the CBU, <br />Professor Inge Jonassen, e-mail: Inge.Jonassen @ ii.uib.no<br /> <br />The successful applicant must comply with the guidelines that apply at any given time the position.<br /> <br />State employment shall as far as possible reflect the diversity of the population. It is therefore an objective to achieve a balanced age and sex composition and the recruitment of persons with immigrant backgrounds. Persons with immigrant background are requested to apply for the position.<br /> <br />Women are particularly encouraged to apply. If the experts find that several applicants have approximately equivalent qualifications, the rules on equal in the Personnel Regulations for Academic Positions will be applied.<br /> <br />University of Bergen applies the principles of public openness when recruiting staff to scientific positions.<br /> <br />Information about the applicant may be made public even though the applicant has requested not to be named in the list of applicants. If the request does not host admitted to the result, the applicant shall be notified of this.<br /> <br />Send application, CV, certificates, diplomas, undergraduate work and a list of publications (list of publications) online by clicking on https://www.jobbnorge.no/jobbsoknet/login.aspx?returnurl=/jobbsoknet/jobapplication.aspx?jobid=95196<br /> <br />You need to upload certified translations into English or a Scandinavian language of appendices, such as diplomas and transcripts.<br /> <br />Applications sent by email to individuals at the institute will not be considered.<br /> <br />Deadline: 9 August 2013</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2336/3rd-annual-next-generation-sequencing-asia-congress-2013-at-singapore-singapore</guid>
  <pubDate>Wed, 14 Aug 2013 09:55:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[3rd Annual Next Generation Sequencing Asia Congress 2013 at Singapore, Singapore]]></title>
  <description><![CDATA[
<p>The 3rd Annual Next Generation Sequencing Asia Congress is to be held on the 22nd and 23rd of October 2013 in Singapore. Over the 2 days, the conference will provide an overview of the current options of next-generation sequencing platforms, technologies, applications and the newest computational tools for the analysis of next-generation sequencing data and analytical genomics as well as overcoming data management problems. The event will attract over 200 senior-level decision makers working in areas such as next generation sequencing, analytical genomics, computational biology, oncology, RNA profiling, molecular genomics, biomarkers, bioinformatics &amp; data management and clinical &amp; diagnostics development.</p>

<p>Dated : 22 Nov 2013 -23 Nov 2013</p>

<p>http://www.ngsasia-congress.com/</p>
]]></description>
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