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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44934?offset=60</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38678/upho-scripts-for-homology-and-orthology-assessment-from-genomic-sequences</guid>
	<pubDate>Mon, 14 Jan 2019 10:36:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38678/upho-scripts-for-homology-and-orthology-assessment-from-genomic-sequences</link>
	<title><![CDATA[UPhO: Scripts for homology and orthology assessment from genomic sequences.]]></title>
	<description><![CDATA[<p>UPhO finds orthologs with and without inparalogs from input gene family trees. Refer to the Documentation.pdf for more detailed explanations on its usage, installation and dependencies. Type UPhO.py -h for help.</p>
<p>The only input requierement for UPhO is a tree (or trees) in Newick format in which the leaves are named with a species idenfifier, a field separator, and sequence identifier. By default, the field separator is the character "|" but custom delimiters can be defined. Examples of trees to test UPhO are provided in the TestData folder.</p><p>Address of the bookmark: <a href="https://github.com/ballesterus/UPhO" rel="nofollow">https://github.com/ballesterus/UPhO</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</guid>
	<pubDate>Sat, 01 Feb 2020 13:38:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</link>
	<title><![CDATA[AccessSyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies]]></title>
	<description><![CDATA[<p><span>Access</span><span>SyRI: finding genomic rearrangements and</span><span>local sequence differences from whole-</span><span>genome assemblies</span><span><br></span></p>
<p><span><span>SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.</span></span></p>
<p><span><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0</a></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements</guid>
	<pubDate>Thu, 14 Dec 2023 12:33:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements</link>
	<title><![CDATA[ReConPlot: an R package for the visualization and interpretation of genomic rearrangements]]></title>
	<description><![CDATA[<p>ReConPlot (REarrangement and COpy Number PLOT), an R package that provides functionalities for the joint visualization of SCNAs and SVs across one or multiple chromosomes. ReConPlot is based on the popular ggplot2 package, thus allowing customization of plots and the generation of publication-quality figures with minimal effort.</p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false" rel="nofollow">https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</guid>
	<pubDate>Wed, 13 Aug 2025 19:56:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</link>
	<title><![CDATA[dna2bit: an ultra-fast and accurate genomic distance estimation software]]></title>
	<description><![CDATA[<p dir="auto">dna2bit: an ultra-fast and accurate genomic distance estimation software</p>
<div dir="auto"><a href="https://github.com/lijuzeng/dna2bit#compilation"></a></div>
<p dir="auto">dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/lijuzeng/dna2bit" rel="nofollow">https://github.com/lijuzeng/dna2bit</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/870/6-phd-students-tu-dresden</guid>
  <pubDate>Sun, 14 Jul 2013 13:42:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[6 PhD Students @ TU Dresden]]></title>
  <description><![CDATA[
<p>At TU Dresden, Faculty of Computer Science, the DFG Research Training Group GRK 1907 “Role-based Software Infrastructures for continuous-context-sensitive Systems” offers the positions of 6 PhD Students (E 13 TV-L)</p>

<p>for applicants interested in performing high-quality research on the connection between software engineering, database systems, and theoretical computer science as well as their applications in bioinformatics and business informatics. The research programme will start on October 1, 2013 until 30.09.2016. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG).</p>

<p>This research programme is a joint activity of Professors Lehner, Assmann, Baader, Baier, Schill, Schlegel, Schroeder, and Strahringer at TU Dresden. Alongside their research, an individual mentoring and qualification approach are arranged with specialized courses that prepare them optimally for their research, a research seminar where they can meet internationally renowned researchers in the field, and soft skills and language courses.</p>

<p>Requirements: Applicants should have an excellent academic record, and hold a MSc (or an equivalent university degree) in computer science or related disciplines (such as mathematics, bioinformatics or business informatics). Fluency in spoken and written English is required. Applicants with a good knowledge of software engineering or one of the application areas mentioned above are preferred. TU Dresden is committed to increase the proportion of women in research.</p>

<p>Applications from women are particularly welcome. The same applies to disabled people.</p>

<p>Please send enquiries to: wolfgang.lehner@tu-dresden.de</p>

<p>Applications consist of a CV, the names of two referees, transcipts of documents summarizing their academic performance, and a statement of interest. Application by email in pdf format is preferred, and should be submitted to wolfgang.lehner@tu-dresden.de in an electronically signed and encrypted form by July 30, 2013 (stamped arrival date of the university central mail service applies). Alternatively, applications can be sent to: TU Dresden, Fakultät Informatik, Institut für Systemarchitektur, Prof.  Dr.-Ing.  Wolfgang Lehner, 01062 Dresden, Germany.</p>

<p>Shortlisted candidates will be invited to Dresden in the middle of August to give a presentation on their Master’s thesis and discuss their research interest with the participating professors. Candidates that have not yet finished their degree when they send in their application should send preliminary transcripts of their academic records as well as a letter by the thesis adviser that comments on their progress so far and on the expected date of completion of their MSc or equivalent degree.</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9039/postdoc-position-in-computational-biology</guid>
  <pubDate>Fri, 14 Mar 2014 01:38:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc Position in Computational Biology]]></title>
  <description><![CDATA[
<p>The Computational Biology Group of Interdisciplinary Center for<br />Clinical Research (IZKF) Aachen, RWTH Aachen University Hospital,<br />Aachen, invites applicants for PhD candidate or postdoctoral position<br />in computational biology in one of the following topics:</p>

<p>1) Statistical machine learning methods for the analysis of medical<br />epigenomics data.</p>

<p>2) Sequence analysis algorithms for detection of RNA-DNA interactions.</p>

<p>Applicants should hold a M.Sc . or PhD in Computer Science or related<br />areas. Experience in the analysis of biological sequences, gene<br />expression and gene regulation is desirable. The candidate should have<br />solid programming skills (C, Python and/or R) and acquaintance with<br />Linux. Experience with high performance computing is a plus. The<br />working language of the group is English.</p>

<p>The position is based on the German TV-L 13 salary scale, including<br />all German social benefits (health insurance and pension scheme). The<br />expected starting date is September 2014. Interested candidates should<br />send a CV, statement of research interests and the names of three<br />references to jobs@costalab.org.</p>

<p>More at http://costalab.org/wp/phd-and-postdoc-position-in-computational-biology/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42958/claus-peter-stelzer-lab</guid>
  <pubDate>Mon, 15 Mar 2021 15:24:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Claus-Peter Stelzer Lab]]></title>
  <description><![CDATA[
<p>Interested in various topics at the intersection of ecology and evolution. In my research I use rotifers as model organisms for experimental studies at the individual and population level. Rotifers are ideally suited for this, because populations of thousands can be kept in small containers in the lab, while single individuals can still be handled conveniently. </p>

<p>More at https://www.uibk.ac.at/limno/personnel/stelzer/index.html.en#research</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5380/04-informatics-approach-to-cancer-interview-with-dr-joel-saltz</guid>
	<pubDate>Mon, 07 Oct 2013 14:35:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5380/04-informatics-approach-to-cancer-interview-with-dr-joel-saltz</link>
	<title><![CDATA[04- Informatics Approach to Cancer - Interview with Dr. Joel Saltz]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/8Kf5EP4LY7k" frameborder="0" allowfullscreen></iframe>For additional information visit http://www.cancerquest.org/joel-saltz-interview.

Dr. Joel Saltz is a Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at
Emory University. Dr. Saltz's research on bioinformatics spans several disciplines.  One project involves applying computer analysis to medical imaging to yield better results for patients.  As an example, a computer program may able to help doctors detect small cancers in a CT scan or mammogram. 

In this interview segment, Dr. Saltz  discusses the informatics approach to cancer.

To learn more about cancer and watch additional interviews, please visit the CancerQuest website at http://www.cancerquest.org.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</guid>
	<pubDate>Fri, 27 Dec 2013 19:58:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</link>
	<title><![CDATA[Oldest Hominin DNA Sequenced]]></title>
	<description><![CDATA[<p>Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.<br /><br />From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.<br /><br /></p><p>Reference</p><p>http://www.sciencedaily.com/releases/2013/12/131204132018.htm</p>]]></description>
	<dc:creator>Surajeet</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12868/landry-lab</guid>
  <pubDate>Thu, 17 Jul 2014 14:33:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Landry Lab]]></title>
  <description><![CDATA[
<p>EVOLUTIONARY AND INTEGRATIVE CELL BIOLOGY</p>

<p>Our research is at the crossroad between cell biology, ecological genomics, systems biology, molecular evolution and population genetics. We study the architecture and evolution of protein and signalling networks.</p>

<p>More at http://landrylab.ibis.ulaval.ca/</p>
]]></description>
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