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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30102?offset=460</link>
	<atom:link href="https://bioinformaticsonline.com/related/30102?offset=460" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42985/janggu-deep-learning-for-genomics</guid>
	<pubDate>Tue, 23 Mar 2021 05:14:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42985/janggu-deep-learning-for-genomics</link>
	<title><![CDATA[Janggu - Deep learning for Genomics]]></title>
	<description><![CDATA[<p><span>Janggu is a python package that facilitates deep learning in the context of genomics. The package is freely available under a GPL-3.0 license.</span></p>
<p><span>Detail tutorial at&nbsp;https://janggu.readthedocs.io/en/latest/</span></p>
<p><span>USE cases</span></p>
<p><span>https://github.com/wkopp/janggu_usecases</span></p><p>Address of the bookmark: <a href="https://github.com/BIMSBbioinfo/janggu" rel="nofollow">https://github.com/BIMSBbioinfo/janggu</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</guid>
	<pubDate>Mon, 04 Dec 2017 07:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</link>
	<title><![CDATA[MetaSim A Sequencing Simulator for Genomics and Metagenomics.]]></title>
	<description><![CDATA[<p><span>Our software can be used to&nbsp;</span><strong>generate collections of synthetic reads</strong><span>&nbsp;that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to&nbsp;</span><strong>design a metagenome</strong><span>&nbsp;by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a&nbsp;</span><strong>simulation of a number of different sequencing technologies</strong><span>. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ab.inf.uni-tuebingen.de/software/metasim/" rel="nofollow">http://ab.inf.uni-tuebingen.de/software/metasim/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11656/faculty-post-at-zhejiang-university</guid>
  <pubDate>Tue, 10 Jun 2014 03:40:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty post at Zhejiang University]]></title>
  <description><![CDATA[
<p>Zhejiang University (ZJU) is seeking faculty candidates for its newly launched, highly competitive and well funded “Hundred Talents Program”. This search covers all colleges and departments at ZJU. Applicants, expected to be about 35 years old, should hold PhD degree, and postdoctoral experiences are preferred for applicants in most fields. Applicants should have demonstrated commitment to excellence in teaching and research at a level comparable to the academic achievement of assistant professor or associate professor in world-renowned universities. Successful candidates must work full-time and are expected to establish internationally competitive and independent research program in cutting-edge areas of the relevant field at ZJU.</p>

<p>As one of the leading research-intensive universities in China, ZJU is located in the beautiful city of Hangzhou. Successful candidates will be employed as Principal Investigators and are qualified to supervise doctoral students. ZJU will offer an internationally competitive salary and the opportunity to purchase university's apartment at a price much lower than the market price, and will provide office and laboratory spaces as well as internationally competitive research startup packages.</p>

<p>Qualified applicants are strongly encouraged to submit their applications electronically to tr@zju.edu.cn. Applicants should include the following materials in pdf format: a comprehensive CV, a statement of research and teaching plan, and a list of 3 to 5 references with detailed contact information.</p>

<p>Contact：Talents Office, ZJU</p>

<p>Tel：+86-571-88981345, +86-571-88981390</p>

<p>Fax：+86-571-88981976</p>

<p>E-mail:tr@zju.edu.cn</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/36647/bioinformatics-jobs-at-nibmg</guid>
  <pubDate>Wed, 16 May 2018 02:57:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics jobs at NIBMG]]></title>
  <description><![CDATA[
<p>NIBMG are looking for bright and motivated people in our big projects on cutting edge biomedical genomics research</p>

<p>http://www.nibmg.ac.in/academic/SyMeC-ICGC/SyMeC%20&amp;%20ICGC_May%202018.pdf</p>

<p>http://www.nibmg.ac.in/academic/plp/15_05_2018/AdvertisementMay2018.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/11592/xampp-starting-apache-fail-ubuntu</guid>
	<pubDate>Sat, 07 Jun 2014 05:52:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/11592/xampp-starting-apache-fail-ubuntu</link>
	<title><![CDATA[XAMPP: Starting Apache fail Ubuntu]]></title>
	<description><![CDATA[<p>Once you install XAMMP on linux, the most common problem you face is Apache failure. To fix the issues please use following command to first stop and then again start it.</p><p>sudo /etc/init.d/apache2 stop</p><p>sudo /etc/init.d/mysql stop</p><p>sudo /etc/init.d/proftpd stop</p><p>sudo /opt/lampp/lampp start</p><p>&nbsp;</p><p><strong>PhpMyAdmin &ldquo;Wrong permissions on configuration file, should not be world writable!&rdquo;</strong></p><p>Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:</p><p>Just chmod 0755 the file</p><pre>sudo chmod 0755 config.inc.php</pre>]]></description>
	<dc:creator>Ram Yash Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42324/comparative-genomics-data-set-including-240-mammals-released</guid>
	<pubDate>Thu, 19 Nov 2020 06:45:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42324/comparative-genomics-data-set-including-240-mammals-released</link>
	<title><![CDATA[Comparative Genomics Data Set Including 240 Mammals Released !]]></title>
	<description><![CDATA[<p>The genome of 130 mammals was sequenced by a large international consortium and the data was analyzed together with 110 existing genomes to allow scientists to identify the important positions in the DNA. This report, published in Nature today will help advance research on human disease mutations and inform how best to protect endangered species.</p><p>In addition to the knowledge of the human genome, all these genomes, widely sampled across mammals, can be used to research how particular organisms respond to different conditions. Some otters, for example, have a thick, water-resistant shell, and some rodents, but not all, have adapted to hibernation. These animal traits will help us to understand human traits, such as metabolic diseases.</p><p><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-020-2876-6/MediaObjects/41586_2020_2876_Fig1_HTML.png?as=webp" alt="image" style="border: 0px; border: 0px;"></p><p>With climate change and more animal ecosystems being threatened by human activity, the protection of endangered species is becoming increasingly important. Scientists have historically researched several people in various populations of a species to understand the genetic variation that occurs in that species. This is important for understanding how particular species can be protected. In this study, animals on the Red List of Endangered Species of the International Union for Conservation of Nature had fewer differences in their genomes, which is consistent with their endangered status.</p><p>Ref @&nbsp;A comparative genomics multitool for scientific discovery and conservation&nbsp;https://www.nature.com/articles/s41586-020-2876-6</p><p>&nbsp;Data at&nbsp;http://zoonomiaproject.org/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12594/faculty-positions-at-central-university-of-punjab</guid>
  <pubDate>Mon, 07 Jul 2014 23:33:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty Positions at Central University of Punjab]]></title>
  <description><![CDATA[
<p>Faculty Positions: Rolling/Open Advertisement Advt.No: T-10 (2013)</p>

<p>Pay Scale: Pay Band Rs.15600-39100 with AGP of Rs.6,000/-</p>

<p>Essential Qualifications for Professors, Associate Professors, and Assistant Professors: As per “UGC REGULATIONS ON MINIMUM QUALIFICATIONS FOR APPOINTMENT OF TEACHERS AND OTHER ACADEMIC STAFF IN UNIVERSITIES AND COLLEGES AND MEASURES FOR THE MAINTENANCE OF STANDARDS IN HIGHER EDUCATION 2010“ and the 2nd Amendments to the regulation issued in June 2013.</p>

<p>For details: http://www.ugc.ac.in/oldpdf/regulations/revised_finalugcregulationfinal10.pdf http://www.ugc.ac.in/pdfnews/8539300_English.pdf and University rules.</p>

<p>Procedure to apply:</p>

<p>Application forms along with API form complete in all respect along with necessary documents and application fee of Rs. 500/-. (Rs. 250/- for Scheduled Caste/Scheduled Tribe/Person with disabilities) should be sent to:</p>

<p>Registrar, Central University of Punjab, City Campus, Mansa Road, Bathinda-151001</p>

<p>For more info visit: http://www.centralunipunjab.com/Teaching/Final%20Details-t10-2013.pdf, http://www.centralunipunjab.com/Teaching/Advertisement-t10-2013.jpg</p>

<p>Last Apply Date: 31 Dec 2014</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42903/katherine-belov-lab</guid>
  <pubDate>Sun, 21 Feb 2021 22:59:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Katherine Belov Lab]]></title>
  <description><![CDATA[
<p>Evolution of the adaptive immune system Marsupial and monotreme immune genes MHC Diversity and Conservation Marsupial and monotreme genomics Comparative Genomics Genetics of Tasmanian Devil facial tumour disease</p>

<p>More at https://www.sydney.edu.au/science/about/our-people/academic-staff/kathy-belov.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44412/scientist-positions-csir-institute-of-genomics-integrative-biology-igib</guid>
  <pubDate>Sat, 02 Dec 2023 00:51:08 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist positions @ CSIR-Institute of Genomics &amp; Integrative Biology (IGIB)]]></title>
  <description><![CDATA[
<p>CSIR-Institute of Genomics &amp; Integrative Biology (IGIB) is a premier Institute of Council of Scientific<br />and Industrial Research (CSIR), engaged in research of national importance in the areas of genomics,<br />molecular medicine, bioinformatics and proteomics. For more details, kindly refer to website<br />https://igib.res.in.<br />The Institute is looking for dynamic and creative Indian researchers having excellent academic record<br />and interested in Product Development / Technology Innovation / Applied Technology / Translational<br />Research in the above broad areas. The eligible candidates may apply for the following positions<br />through the CSIR-IGIB website.</p>

<p>More at https://www.igib.res.in/bdmg/ScientistRecruitmentAdvt2023.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44713/understanding-rna-seq-normalization-methods-tpm-vs-fpkm-vs-cpm</guid>
	<pubDate>Wed, 11 Dec 2024 00:59:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44713/understanding-rna-seq-normalization-methods-tpm-vs-fpkm-vs-cpm</link>
	<title><![CDATA[Understanding RNA-Seq Normalization Methods: TPM vs. FPKM vs. CPM]]></title>
	<description><![CDATA[<p>RNA sequencing (RNA-Seq) is a powerful technology used to study transcriptomes, providing insights into gene expression levels. However, raw RNA-Seq data requires normalization to account for sequencing depth and gene length, enabling accurate comparisons between genes and samples. Among the most widely used normalization methods are TPM (Transcripts Per Million), FPKM (Fragments Per Kilobase Million), and CPM (Counts Per Million). Each method has its unique principles and applications, which we&rsquo;ll explore in this blog.</p><h2>Why Normalize RNA-Seq Data?</h2><p>Normalization is a crucial step in RNA-Seq analysis for the following reasons:</p><ul>
<li>
<p><strong>Sequencing depth:</strong> Different RNA-Seq experiments produce varying numbers of reads, making direct comparisons between samples misleading.</p>
</li>
<li>
<p><strong>Gene length:</strong> Longer genes inherently generate more reads, irrespective of their actual expression level.</p>
</li>
<li>
<p><strong>Bias reduction:</strong> Normalization mitigates technical biases, enabling meaningful biological interpretation.</p>
</li>
</ul><h2>TPM (Transcripts Per Million)</h2><p>TPM measures the proportion of reads mapped to a transcript, normalized by transcript length and sequencing depth. It is calculated as:</p><h3>Key Features:</h3><ol>
<li>
<p><strong>Proportionality:</strong> TPM values sum to 1,000,000 across all transcripts in a sample, making it easier to compare between samples.</p>
</li>
<li>
<p><strong>Intuitive interpretation:</strong> TPM values directly represent the abundance of transcripts in a sample.</p>
</li>
<li>
<p><strong>Preferred for comparisons:</strong> TPM facilitates between-sample comparisons better than FPKM.</p>
</li>
</ol><h2>FPKM (Fragments Per Kilobase Million)</h2><p>FPKM normalizes read counts by transcript length and sequencing depth, but without enforcing proportionality like TPM. It is defined as:</p><h3>Key Features:</h3><ol>
<li>
<p><strong>Historical significance:</strong> FPKM was one of the first normalization methods used for RNA-Seq.</p>
</li>
<li>
<p><strong>Single-end vs. paired-end:</strong> In paired-end sequencing, FPKM becomes RPKM (Reads Per Kilobase Million).</p>
</li>
<li>
<p><strong>Limited utility:</strong> FPKM values are not as robust as TPM for cross-sample comparisons due to lack of proportionality.</p>
</li>
</ol><h2>CPM (Counts Per Million)</h2><p>CPM normalizes raw read counts by sequencing depth, without considering gene length. It is expressed as:</p><h3>Key Features:</h3><ol>
<li>
<p><strong>Simplicity:</strong> CPM is straightforward and computationally less intensive.</p>
</li>
<li>
<p><strong>Application:</strong> Suitable for non-length-dependent analyses, such as comparing total expression levels or differential expression analysis.</p>
</li>
<li>
<p><strong>Gene length agnostic:</strong> CPM does not correct for gene length, making it less ideal for measuring expression levels.</p>
</li>
</ol><h2>When to Use Each Method</h2><ul>
<li>
<p><strong>TPM:</strong> Best for comparing expression levels between samples, especially when transcript length and sequencing depth vary.</p>
</li>
<li>
<p><strong>FPKM:</strong> Useful for historical consistency but generally replaced by TPM.</p>
</li>
<li>
<p><strong>CPM:</strong> Ideal for differential expression analysis when gene length normalization is unnecessary.</p>
</li>
</ul><h2>Conclusion</h2><p>Choosing the right normalization method depends on the specific objectives of your RNA-Seq analysis. TPM&rsquo;s proportionality and robustness make it the preferred choice for most applications, while CPM serves well for differential expression studies. Although FPKM paved the way for RNA-Seq normalization, it has largely been supplanted by TPM in modern workflows. Understanding these methods and their nuances ensures accurate and meaningful interpretations of RNA-Seq data.</p><h3>References:</h3><ol>
<li>
<p>Li, B., &amp; Dewey, C. N. (2011). RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. <em>BMC Bioinformatics.</em></p>
</li>
<li>
<p>Trapnell, C., et al. (2010). Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. <em>Nature Biotechnology.</em></p>
</li>
<li>
<p>Law, C. W., et al. (2014). voom: precision weights unlock linear model analysis tools for RNA-seq read counts. <em>Genome Biology.</em></p>
</li>
</ol>]]></description>
	<dc:creator>Neel</dc:creator>
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