<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23892?offset=560</link>
	<atom:link href="https://bioinformaticsonline.com/related/23892?offset=560" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40865/dminda2-an-integrated-web-server-for-dna-motif-identification-and-analyses</guid>
	<pubDate>Sun, 02 Feb 2020 14:26:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40865/dminda2-an-integrated-web-server-for-dna-motif-identification-and-analyses</link>
	<title><![CDATA[DMINDA2: an integrated web server for DNA motif identification and analyses]]></title>
	<description><![CDATA[<p><span>DMINDA (</span><strong>D</strong><span>NA&nbsp;</span><strong>m</strong><span>otif&nbsp;</span><strong>i</strong><span>dentification a</span><strong>nd a</strong><span>nalyses) is an integrated web server for DNA motif identification and analyses</span></p>
<p><span>More at&nbsp;http://bmbl.sdstate.edu/DMINDA2/</span></p>
<p><span><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086085/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086085/</a></span></p><p>Address of the bookmark: <a href="http://bmbl.sdstate.edu/DMINDA2/" rel="nofollow">http://bmbl.sdstate.edu/DMINDA2/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014</guid>
	<pubDate>Tue, 24 Jun 2014 07:58:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014</link>
	<title><![CDATA[Genomic Medicine - Bruce Korf (2014)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/FYldIrsXHKw" frameborder="0" allowfullscreen></iframe>May 21, 2014 - Current Topics in Genome Analysis 2014
A lecture series covering contemporary areas in genomics and bioinformatics. More: http://www.genome.gov/COURSE2014]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</guid>
	<pubDate>Fri, 12 Jun 2020 07:26:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</link>
	<title><![CDATA[PPAI: a web server for predicting protein-aptamer interactions]]></title>
	<description><![CDATA[<p><span>PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at&nbsp;</span><a href="http://39.96.85.9/PPAI">http://39.96.85.9/PPAI</a></p><p>Address of the bookmark: <a href="http://39.96.85.9/PPAI/" rel="nofollow">http://39.96.85.9/PPAI/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44900/pegas-a-comprehensive-bioinformatic-solution-for-pathogenic-bacterial-genomic-analysis</guid>
	<pubDate>Mon, 01 Sep 2025 01:18:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44900/pegas-a-comprehensive-bioinformatic-solution-for-pathogenic-bacterial-genomic-analysis</link>
	<title><![CDATA[PeGAS: A Comprehensive Bioinformatic Solution for Pathogenic Bacterial Genomic Analysis]]></title>
	<description><![CDATA[<p><span>This is PeGAS, a powerful bioinformatic tool designed for the seamless quality control, assembly, and annotation of Illumina paired-end reads specific to pathogenic bacteria. This tool integrates state-of-the-art open-source software to provide a streamlined and efficient workflow, ensuring accurate insights into the genomic makeup of pathogenic microbial strains.</span></p>
<p><span><img src="https://github.com/liviurotiul/PeGAS/raw/main/Features.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/liviurotiul/PeGAS" rel="nofollow">https://github.com/liviurotiul/PeGAS</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</guid>
	<pubDate>Sat, 06 Feb 2021 13:31:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</link>
	<title><![CDATA[Bioinformatics in Africa: Part 4 - Morocco]]></title>
	<description><![CDATA[<p>Bioinformatics, in the UFR in Artificial Intelligence and Bioinformatics, deals with the management, the analysis, the modelling and the visualization of biological databases. Since the size of the databases is often exponential, the traditional algorithms are not very effective when seeking for a good computational solution.</p><p>To take care of this issue, many ways are opened to the researchers&nbsp;to&nbsp;improve&nbsp;the&nbsp;quality&nbsp;of&nbsp;the&nbsp;algorithms:</p><p>1. Usage of new information processing methods like artificial neuronal networks, genetic algorithms,&nbsp;etc. 2. Usage&nbsp;of&nbsp;Data&nbsp;mining&nbsp;&nbsp;to&nbsp;explore&nbsp;biochemical&nbsp;databases,<br />3. Usage of Machine learning on the biological examples to solve, for example, the problem of classification&nbsp;in&nbsp;Bioinformatics.</p><p>UFR&nbsp;offers&nbsp;in&nbsp;addition&nbsp;a&nbsp;doctoral&nbsp;training&nbsp;in&nbsp;Computer&nbsp;Science&nbsp;and&nbsp;Bioinformatics.</p><p>Doctoral&nbsp;module&nbsp;which&nbsp;includes:&nbsp;a&nbsp;Dipl&ocirc;me&nbsp;des&nbsp;Etudes&nbsp;Sup&eacute;rieures&nbsp;Approfondies&nbsp;(DESA)&nbsp; of&nbsp;two&nbsp;years;&nbsp;and&nbsp;a&nbsp;doctorate&nbsp;studies&nbsp;program&nbsp;with&nbsp;a&nbsp;national&nbsp;Ph.D.&nbsp;certification. Three&nbsp;specializations&nbsp;constitute&nbsp;the&nbsp;teaching&nbsp;trunk&nbsp;of&nbsp;the&nbsp;ENSAT:&nbsp;Computer&nbsp;engineering,&nbsp;Telecom&nbsp; engineering,&nbsp;and&nbsp;electronic&nbsp;systems&nbsp;engineering.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities:</p><p>The&nbsp;following&nbsp;are&nbsp;the&nbsp;present&nbsp;areas&nbsp;of&nbsp;research&nbsp;interest:</p><p>1. Machine&nbsp;Learning&nbsp;and&nbsp;Profile&nbsp;Gene&nbsp;Expression&nbsp;of&nbsp;Cancer<br />2. Predicting&nbsp;Protein&nbsp;structure <br />3. Hidden&nbsp;Markov&nbsp;Models&nbsp;(HMMs)&nbsp;and&nbsp;multiple&nbsp;alignments <br />4. Transformational&nbsp;Grammar&nbsp;for&nbsp;sequence&nbsp;modelling <br />5. Physical&nbsp;Mapping:&nbsp;STSs <br />6. Evolutionary&nbsp;Computation&nbsp;applied&nbsp;to&nbsp;Genomic&nbsp;and&nbsp;Proteomic <br />7. Predicate&nbsp;Logic&nbsp;and&nbsp;Protein&nbsp;Structure</p><p>Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ensat.ac.ma/udiab http://www.pasteur.fr/pasteur/international/annonce_coursBioinfoannonce06_casa.pdf</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</guid>
	<pubDate>Wed, 25 Mar 2020 17:11:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</link>
	<title><![CDATA[Coronavirus Resources !]]></title>
	<description><![CDATA[<p><span>2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.</span></p>
<p><span>Annotation</span></p>
<p><span><a href="https://bigd.big.ac.cn/ncov/variation/annotation">https://bigd.big.ac.cn/ncov/variation/annotation</a></span></p>
<p><span>Genome wharehouse&nbsp;</span></p>
<p><span><a href="https://bigd.big.ac.cn/gwh/browse/index">https://bigd.big.ac.cn/gwh/browse/index</a></span></p>
<p>Released Genome</p>
<p><a href="https://bigd.big.ac.cn/ncov/release_genome">https://bigd.big.ac.cn/ncov/release_genome</a></p>
<p>Download data&nbsp;</p>
<p><a href="ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/">ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/</a></p>
<p>Raw data</p>
<p><a href="https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae">https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae</a></p><p>Address of the bookmark: <a href="https://bigd.big.ac.cn/ncov/about" rel="nofollow">https://bigd.big.ac.cn/ncov/about</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43308/rna-seq-differential-expression-work-flow-using-deseq2</guid>
	<pubDate>Mon, 23 Aug 2021 10:57:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43308/rna-seq-differential-expression-work-flow-using-deseq2</link>
	<title><![CDATA[RNA-Seq differential expression work flow using DESeq2]]></title>
	<description><![CDATA[<p><span>One of the aim of RNAseq data analysis is the detection of differentially expressed genes. The package&nbsp;</span><a href="http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html">DESeq2</a><span>&nbsp;provides methods to test for differential expression analysis.</span></p><p>Address of the bookmark: <a href="http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2" rel="nofollow">http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</guid>
	<pubDate>Wed, 13 Aug 2014 18:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</link>
	<title><![CDATA[Dynamic chromosome breakpoints !!!]]></title>
	<description><![CDATA[<p>Cell division involves the distribution of identical genetic material, DNA, to two daughters&rsquo; cells. During this process, duplicated deoxyribonucleic acid (DNA) goes through a condensation and decondensation process. This is followed by nuclear envelope dissolution, mitotic spindle assembly, migration of the sister chromatid pairs to the metaphase plate, division and segregation of identical sets of chromosomes into daughter nuclei and nuclear envelope reformation.</p><p>The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo <strong>recombination </strong>which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.</p><p><img src="http://www.sciencelearn.org.nz/var/sciencelearn/storage/images/contexts/uniquely-me/sci-media/images/chromosomes-crossing-over/464438-1-eng-NZ/Chromosomes-crossing-over.jpg" alt="image" width="504" height="342" style="border: 0px; border: 0px;"></p><p>During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The &ldquo;<strong>chromosomal breakpoints</strong>&rdquo; refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this &ldquo;break and sealing/ break and reattach&rdquo; process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities &nbsp;where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.</p><p>&nbsp;</p><p>&nbsp;</p><p><img src="http://upload.wikimedia.org/wikipedia/commons/4/4a/Chromosomal_translocations.svg" alt="image" width="424" height="331" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>Apart from certain chromosome abnormalities, these &ldquo;crossing over&rdquo; of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.</p><p>I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/&nbsp; in my next blog.</p><p><strong>Software for recombination detection:</strong></p><p><strong>RAT</strong> http://cbr.jic.ac.uk/dicks/software/RAT/</p><p><strong>Breakpointer</strong> https://github.com/ruping/Breakpointer</p><p><strong>DRP</strong> http://web.cbio.uct.ac.za/~darren/rdp.html</p><p><strong>RB-finder</strong> http://www.ncbi.nlm.nih.gov/pubmed/18707535</p><p><strong>LDhat2.0</strong> http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml</p><p><strong>Reference:</strong></p><p>http://www.nature.com/scitable/topicpage/genetic-recombination-514#</p><p>Image: Wikipedia , sciencelearn.org.nz</p><p><strong>Recommended Articles:</strong></p><p>http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/</p><p>http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf</p><p>http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/</p><p>http://learn.genetics.utah.edu/content/disorders/chromosomal/</p><p>http://www.ncert.nic.in/html/learning_basket/biology/cc&amp;cd.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</guid>
	<pubDate>Mon, 06 Oct 2014 12:51:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</link>
	<title><![CDATA[Orange-Bioinformatics 2.5.34]]></title>
	<description><![CDATA[<p>Orange Bioinformatics extends <a href="http://orange.biolab.si/">Orange</a>, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.</p>
<p>Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.</p><p>Address of the bookmark: <a href="https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34" rel="nofollow">https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18380/jrfsrf-at-university-of-hyderabad</guid>
  <pubDate>Fri, 17 Oct 2014 01:55:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at University of Hyderabad]]></title>
  <description><![CDATA[
<p>Applications are invited for the following post of Junior Research Fellow (temporary position coterminous with the project) under DBT funded research project on ““Understanding the functions of α1β1γ1/α2β1γ1 selective AMPK Modulators in dissecting the pharmacological role of these isozymes in metabolic diseases”</p>

<p>Qualified and interested candidates can send their curriculum vitae by e-mail to hr@drils.org on or before 27th October 2014 mention in the subject line of the mail the following code: AMPK-Biology.</p>

<p>Selected candidates will be called for a personal interview to Dr. Reddy’s Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad. The selected candidate is expected to report within two weeks from the date of selection to start work on the project.</p>

<p>Junior Research Fellowship (Molecular Modeling/Biology) for two years and Senior Research fellowship for one year</p>

<p>Junior Research Fellowship: Rs. 15,600/- (consolidated) per month for first two years.<br />Senior Research Fellowship: Rs. 18,200/-(consolidated) per month for the 3rd year.</p>

<p>Duration: The duration of the fellowship is for three years. However, the performance of the candidate will be reviewed after the completion of every year and the fellowship will be renewed only upon satisfactory performance.</p>

<p>Responsibilities:</p>

<p>1) Literature search.<br />2) Design, plan and execute experiments under the supervision of the scientist.<br />3) Provide scientific support to the scientist in his/her research activities.<br />4) Book keeping and maintenance of stocks and consumables.</p>

<p>Essential Qualifications:</p>

<p>Required: M.Sc. in Microbiology/Biotechnology/Bioinformatics or any other related branch of basic Sciences from a recognized university/institute with a consistent academic record of minimum 60% aggregate in all qualifying examinations. The candidate should be NET qualified for lectureship. The candidate should be motivated to work with dedication.</p>

<p>Desirable: expertise/experience in both Molecular Modeling and Molecular Biology.</p>

<p>Experience: 0-2 years in the areas of Molecular Modeling and/or Molecular Biology and cell biology and Biochemistry.</p>

<p>Preferable: Relevant research experience as evident from thesis/dissertation/project work.</p>

<p>Advertisement: http://www.ilsresearch.org/userfiles/Junior%20REsearch%20Fellowship%20-%20AMPK(Biology).pdf</p>
]]></description>
</item>

</channel>
</rss>