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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34912?offset=120</link>
	<atom:link href="https://bioinformaticsonline.com/related/34912?offset=120" rel="self" type="application/rss+xml" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8480/paper-test-for-cancer</guid>
	<pubDate>Wed, 26 Feb 2014 00:20:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8480/paper-test-for-cancer</link>
	<title><![CDATA[Paper test for cancer !!!]]></title>
	<description><![CDATA[<p>The American Cancer Society projects the numbers of new cancer cases and deaths expected each year in order to estimate the contemporary cancer burden, because cancer incidence and mortality data lag three to four years behind the current year. In addition, the regularly updated Facts &amp; Figures publications present the most current trends in cancer occurrence and survival, as well as information on symptoms, prevention, early detection, and treatment. Cancer rates in developing nations have climbed sharply in recent years, and now account for 70 percent of cancer mortality worldwide. Early detection has been proven to improve outcomes, but screening approaches such as mammograms and colonoscopy, used in the developed world, are too costly to be implemented in settings with little medical infrastructure.</p><p>The US born Sangeeta Bhatia at Massachusetts Institute of Technology (MIT) has developed a cheap, simple, paper test that can detect cancer. These diagnostic, which works much like a pregnancy test, could reveal within minutes, based on a urine sample, whether a person have cancer or not. The MIT media announce the major and amazing breakthrough in cancer diagonistics. These newly developed technology will allow non-communicable diseases to be detect at early stage, which will be cheap and easily accessible to the masses. For the developing world it would be exciting to adapt it instead to a paper test that could be performed on unprocessed samples in a rural setting, without the need for any specialized equipment. The simple readout could even be transmitted to a remote caregiver by a picture on a mobile phone.</p><p>The MIT professor and Howard Hughes Medical Institute investigator Sangeeta Bhatia, who is also the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, invented a new class of synthetic biomarker, which is highly specialized instrument to do these kind of analysis. These paper test essentially relies on nanoparticles that interact with tumor proteins called proteases, each of which can trigger release of hundreds of biomarkers that are then easily detectable in a patient's urine. The MIT nanoparticles are coated with peptides (short protein fragments) targeted by different MMPs. These particles congregate at tumor sites, where MMPs cleave hundreds of peptides, which accumulate in the kidneys and are excreted in the urine.</p><p><img src="http://www.jasongrowclients.com/bhatia/source/image/100601e_bhatia_8122.jpg" width="400" height="600" alt="image" style="border: 0px;"><br /><br />To create the test strips, the researchers first coated nitrocellulose paper with antibodies that can capture the peptides. Once the peptides are captured, they flow along the strip and are exposed to several invisible test lines made of other antibodies specific to different tags attached to the peptides. If one of these lines becomes visible, it means the target peptide is present in the sample. The technology can also easily be modified to detect multiple types of peptides released by different types or stages of disease.<br /><br />In tests in mice, the researchers were able to accurately identify colon tumors, as well as blood clots. Bhatia says these tests represent the first step toward a diagnostic device that could someday be useful in human patients. "This is a new idea &mdash; to create an excreted biomarker instead of relying on what the body gives you," she says. "To prove this approach is really going to be a useful diagnostic, the next step is to test it in patient populations."</p><p>&nbsp;</p><p>Reference:</p><p>Image: jasongrowclients</p><p>Homepage: http://lmrt.mit.edu/about.html</p><p>http://web.mit.edu/newsoffice/2014/a-paper-diagnostic-for-cancer-0224.html</p><p>http://timesofindia.indiatimes.com/home/science/PIO-develops-cheap-paper-test-to-detect-cancer/articleshow/30963615.cms</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28926/scientist-at-advanced-centre-for-treatment-research-and-education-in-cancer-navi-mumbai-maharashtra</guid>
  <pubDate>Tue, 30 Aug 2016 04:16:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Scientist at Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra]]></title>
  <description><![CDATA[
<p>Scientist <br />Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra<br />Scientist (One position) <br />Project: Bioinformatics centre DBT- Sub-DIC at ACTREC <br />Funding agency: DBT Grant No.232 </p>

<p>Duration of the Project: Six Months from the date of appointment can be extended further for six months <br />Essential Qualification and Experience: 1st Class Masters Degree in Bioinformatics or Life Sciences equivalent degree from a recognized University with 4 years R&amp;D experience in Bioinformatics or relevant subjects from recognized institutes. <br />OR <br />Ph.D. degree in Bioinformatics or Life Sciences from recognized University. <br />M.Sc. degree obtained after a one year course will not be considered. <br />Experience: Research/teaching experience in Bioinformatics or relevant subjects form recognized Institute(s). </p>

<p>More at http://www.actrec.gov.in/data%20files/Vacancies/2016/AV-scin-stud-trainee-6-Sept-16.docx</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/38838/computer-scientistbioinformatician-at-ieo-in-milan-italy</guid>
  <pubDate>Thu, 31 Jan 2019 09:10:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[Computer scientist/bioinformatician at IEO in Milan, Italy]]></title>
  <description><![CDATA[
<p>We are looking for a computer scientist or a bioinformatician with a strong computation background to join the bioinformatics unit of the IEO in Milan. Web development, scripting, experience with spring boot, hpc, docker are appreciated. The candidate will evolve in a research environment (next generation sequencing among others). The selected candidate will consolidate our team for the development and maintenance of the bioinformatics resources, and will have the opportunity to support the research groups in setting new tools and pipelines.</p>

<p>Place of employment and work</p>

<p>The candidate will be located at the Department of Experimental Oncology of the European Institute of Oncology in Milan (Italy), one of Europe’s leading research institutes in biomedical research, where he/she will also interact with one of the largest computational biology communities in Italy</p>

<p>Requirements:</p>

<p>The candidate should have a good knowledge of the UNIX system and good programming skills (bash, R, python, java). Background in bioinformatics would be appreciated but is not mandatory. Additional experience with containers (docker, singularity),  grid computing, web frameworks, continuous integrations will be appreciated.</p>

<p>For further info or to arrange an informal interview, please write to arnaud.ceol@ieo.it</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4550/gupta-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:31:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Gupta Lab]]></title>
  <description><![CDATA[
<p>Gupta laboratory of Natural Information Processing at DA-IICT. Research in our lab currently focuses on two aspects of information processing viz. deciphering the information processing principles in life (systems biology) and making a computer out of bio-molecules. The key expertise of the lab is in error-correcting codes. We also work in classical and quantum information processing principles with expertise in coding theory and its wide variety of applications in Information and Communication Technology (ICT). </p>

<p>More @ http://www.guptalab.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/13415/genomics-and-sequencing-approach-for-identification-of-biomarkers-to-assess-the-efficacy-of-tgf-%CE%B2ri-inhibitors-of-liver-cancer-in-vivo</guid>
	<pubDate>Tue, 05 Aug 2014 13:55:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/13415/genomics-and-sequencing-approach-for-identification-of-biomarkers-to-assess-the-efficacy-of-tgf-%CE%B2ri-inhibitors-of-liver-cancer-in-vivo</link>
	<title><![CDATA[Genomics and sequencing approach for identification of biomarkers to assess the efficacy of TGF-βRI inhibitors (of liver cancer) in vivo]]></title>
	<description><![CDATA[<p>Liver cancer is third leading cause of deaths and fourth most frequent occuring cancer worldwide. There are multiple signaling pathways responsible for causing cancer amongst which TGFb is most important cytokine whose signaling pathway promote cancer. However, main problem is to cure this cancer at late stage where we still have no treatment strategy to tackle this deadly cancer. &nbsp;Hence we need to find out new therapeutic target. One way is to look the relationships between mRNA, methylation and miRNA data of patients with different pathological conditions (cancer vs control either with inhibitor/not). MiRNA is small RNA molecules known to inhibit mRNA expression of particular gene by binding improperly to 3'UTR region of a gene and hence block binding of TF /translation of gene. CpG regions is known to located at promoter region of gene (5' UTR) and usually hypomethylated which allow to gene to transcribe and translate however sometime this region become hyper-methylated thats prevent expression of host gene. Thus , integration of these three data reveal new targets and pathways important for causing or preventing cancer and also reveal biomarker thats check the effects of inhibitor on signaling pathway underlying liver cancer.</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/13415" length="26423" type="image/jpeg" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40497/artificial-intelligence-is-more-accurate-than-doctors-in-diagnosing-breast-cancer</guid>
	<pubDate>Wed, 01 Jan 2020 22:12:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40497/artificial-intelligence-is-more-accurate-than-doctors-in-diagnosing-breast-cancer</link>
	<title><![CDATA[Artificial intelligence is more accurate than doctors in diagnosing breast cancer]]></title>
	<description><![CDATA[<p>Artificial intelligence is more accurate than doctors in diagnosing breast cancer from mammograms, a study in the journal Nature suggests.</p><p>An international team, including researchers from&nbsp;<a href="https://health.google/" target="_blank">Google Health</a>&nbsp;and&nbsp;<a href="https://www.imperial.ac.uk/news/183293/research-collaboration-aims-improve-breast-cancer/" target="_blank">Imperial College London</a>, designed and trained a computer model on X-ray images from nearly 29,000 women.</p><p>The algorithm&nbsp;<a href="https://nature.com/articles/s41586-019-1799-6" target="_blank">outperformed six radiologists</a>&nbsp;in reading mammograms.</p><p>AI was still as good as two doctors working together.</p><p>Unlike humans, AI is tireless. Experts say it could improve detection. Read More:&nbsp;<a href="https://www.bbc.com/news/health-50857759" target="_blank">https://www.bbc.com/news/health-50857759</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43055/infogenomer-integrative-reconstruction-of-cancer-genome-karyotypes</guid>
	<pubDate>Wed, 05 May 2021 01:02:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43055/infogenomer-integrative-reconstruction-of-cancer-genome-karyotypes</link>
	<title><![CDATA[InfoGenomeR: Integrative reconstruction of cancer genome karyotypes]]></title>
	<description><![CDATA[<p>InfoGenomeR is the Integrative Framework for Genome Reconstruction that uses a breakpoint graph to model the connectivity among genomic segments at the genome-wide scale. InfoGenomeR integrates cancer purity and ploidy, total CNAs, allele-specific CNAs, and haplotype information to identify the optimal breakpoint graph representing cancer genomes.</p>
<p><img src="https://github.com/YeonghunL/InfoGenomeR/raw/master/doc/overview.png" alt="image" style="border: 0px; border: 0px;"></p>
<p>More at&nbsp;https://www.nature.com/articles/s41467-021-22671-6</p><p>Address of the bookmark: <a href="https://github.com/dmcblab/InfoGenomeR" rel="nofollow">https://github.com/dmcblab/InfoGenomeR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/869/bioinformatics-phd-studentship-available-in-new-zealand</guid>
  <pubDate>Sun, 14 Jul 2013 13:36:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics PhD studentship available in New Zealand]]></title>
  <description><![CDATA[
<p>Bioinformatics PhD studentship available in New Zealand</p>

<p>The importance of transcriptional control has been explored in a burgeoning line of research over several decades; nevertheless, we are still far from having a complete picture of the regulatory mechanisms of genes and non-coding RNAs, and their influences on different phenotypes and disease states of a cell. Recent shifts towards large-scale analyses of transcriptional regulation on a sequence and epigenetic level are at the forefront of research, mainly due to sequencing technology advancements and a deeper understanding of the fundamental regulatory processes involved.</p>

<p>Arriving at a better understanding of the influence of specific parts of the overall regulatory machinery on disease states is a high priority of the group’s research agenda.</p>

<p>We are seeking an enthusiastic student to join the group as a PhD student. Applicants must have a BSc(Hons) or MSc degree in a relevant discipline and a willingness to learn and apply new techniques and work in a team. Both local and international students are encouraged to apply.</p>

<p>The studentship covers all university fees and an annual tax-exempt stipend of NZ$22,000 for three years.</p>

<p>Sebastian Schmeier recently joined Massey University and started his own research group in Auckland, New Zealand, a city regularly ranked one of the most livable in the world. This is your chance to experience the amazing Auckland lifestyle and the excitement of joining a young new science team, while staying connected to world class scientific networks.</p>

<p>To apply for the post, please send a cover letter stating your interest in the position and why you think you would be a good candidate, a Curriculum Vitae, a copy of your academic transcript, a sample of your written scientific work, and the names of three referees. Applications will be accepted until the position is filled.</p>

<p>Enquiries and applications to Sebastian Schmeier (s.schmeier@massey.ac.nz).</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/923/phylogenetic-for-bioinformatics</guid>
	<pubDate>Tue, 16 Jul 2013 03:50:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/923/phylogenetic-for-bioinformatics</link>
	<title><![CDATA[Phylogenetic for Bioinformatics]]></title>
	<description><![CDATA[<p>Biologists estimate that there are about 5 to 100 million species of organisms living on Earth today. Evidence from morphological, biochemical, and gene sequence data suggests that all organisms on Earth are genetically related, and the genealogical relationships of living things can be represented by a vast evolutionary tree, the Tree of Life. The Tree of Life then represents the phylogeny of organisms, i. e., the history of organismal lineages as they change through time.<br />Every living organism contains DNA, RNA, and proteins. Closely related organisms generally have a high degree of agreement in the molecular structure of these substances, while the molecules of organisms distantly related usually show a pattern of dissimilarity. Molecular phylogeny uses such data to build a "relationship tree" that shows the probable evolution of various organisms. Not until recent decades, however, has it been possible to isolate and identify these molecular structures.&nbsp;<br />phylogenetics is the study of evolutionary relatedness among various groups of organisms (for example, species or populations), which is discovered through molecular sequencing data and morphological data matrices. In other word, Phylogenetics, the science of phylogeny, is one part of the larger field of systematics, which also includes taxonomy. Taxonomy is the science of naming and classifying the diversity of organisms Molecular phylogeny is the use of the structure of molecules to gain information on an organism's evolutionary relationships. The result of a molecular phylogenetic analysis is expressed in a so-called phylogenetic tree.</p><p>The evolutionary connections between organisms are represented graphically through phylogenetic trees. Due to the fact that evolution takes place over long periods of time that cannot be observed directly, biologists must reconstruct phylogenies by inferring the evolutionary relationships among present-day organisms.&nbsp;<br />Application of the techniques that make this possible can be seen in the very limited field of human genetics, such as the ever more popular use of genetic testing to determine a child's paternity, as well as the emergence of a new branch of criminal forensics focused on genetic evidence.<br />The effect on traditional scientific classification schemes in the biological sciences has been dramatic as well. Work that was once immensely labor- and materials-intensive can now be done quickly and easily, leading to yet another source of information becoming available for systematic and taxonomic appraisal. This particular kind of data has become so popular that taxonomical schemes based solely on molecular data may be encountered. Proponents even claim that taxonomy was previously based on morphology alone, which of course is utter fable.<br /><br /><strong>For additional information on phylogenetics, see list of Phylogenetics Resources on the Internet.</strong></p><p>Phylogeny and Reconstructing Phylogenetic Trees:&nbsp;<a href="http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html"></a><a href="http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html">http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html</a><br />the CBRG and Department of Statistics Phylogeny tutorial:&nbsp;<a href="http://www.compbio.ox.ac.uk/tutorials/phylogeny/"></a><a href="http://www.compbio.ox.ac.uk/tutorials/phylogeny/">http://www.compbio.ox.ac.uk/tutorials/phylogeny/</a><br />TUTORIAL: PHYLOGENETIC ANALYSIS USING PARSIMONY:<a href="http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html"></a><a href="http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html">http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html</a></p><p>PHYLIP:&nbsp;<a href="http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html"></a><a href="http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html">http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html</a><br />An Introduction to Molecular Phylogeny:&nbsp;<a href="http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf"></a><a href="http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf">http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf</a></p><p>How to make a phylogenetic tree:&nbsp;<a href="http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree"></a><a href="http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree">http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree</a>tutorial.html<br />Phylogenetic Trees:&nbsp;<a href="http://cnx.org/content/m11052/latest/"></a><a href="http://cnx.org/content/m11052/latest/">http://cnx.org/content/m11052/latest/</a><br />Phylogeny by Ron Shamir:&nbsp;<a href="http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf"></a><a href="http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf">http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf</a><br />Introduction to Phylogeny:&nbsp;<a href="http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm"></a><a href="http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm">http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm</a><br />Lecturer notes on Phylogeny:&nbsp;<a href="http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf"></a><a href="http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf">http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf</a><br />Principles and Practice of Phylogenetic Systematics:<a href="http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm"></a><a href="http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm">http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm</a></p><p>Inferring phylogenetic trees:&nbsp;<a href="http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf"></a><a href="http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf">http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf</a></p><p><strong>Lecture Notes</strong></p><p>Chapter 1 - The Diversity, Classification, and Evolution of Vertebrates:<a href="http://academic.emporia.edu/mooredwi/nathist/chap1.htm"></a><a href="http://academic.emporia.edu/mooredwi/nathist/chap1.htm">http://academic.emporia.edu/mooredwi/nathist/chap1.htm</a></p><p>Algorithms for Phylogenetic Reconstructions:<a href="http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf"></a><a href="http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf">http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf</a></p><p>Phylogeny.fr is a free, simple to use web service dedicated to reconstructing and analysing phylogenetic relationships between molecular sequences. Phylogeny.fr runs and connects various bioinformatics programs to reconstruct a robust phylogenetic tree from a set of sequences. For more detail :&nbsp;<a href="http://www.phylogeny.fr/version2_cgi/index.cgi"></a><a href="http://www.phylogeny.fr/version2_cgi/index.cgi">http://www.phylogeny.fr/version2_cgi/index.cgi</a></p><p>A Brief Tutorial on Phylogenetics<br /><a href="http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf"></a><a href="http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf">http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf</a></p><p>A Brief Tutorial on Phylogenetics Human Rabbit Chicken<br /><a href="http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf"></a><a href="http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf">http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf</a></p><p>Phylogenetic Tree Computation Tutorial Overview<br /><a href="http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf"></a><a href="http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf">http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf</a></p><p>MrBayes: A program for the Bayesian inference of phylogeny<br /><a href="http://golab.unl.edu/teaching/SBseminar/manual.pdf"></a><a href="http://golab.unl.edu/teaching/SBseminar/manual.pdf">http://golab.unl.edu/teaching/SBseminar/manual.pdf</a></p><p><strong>Web sites providing software for the construction of phylogenetic trees</strong></p><ul>
<li><a href="http://www.mbio.ncsu.edu/BioEdit/bioedit.html">BioEdit</a></li>
</ul><ul>
<li><a href="http://www.dinofish.com/">Coelocanth-Fish Out of Time</a></li>
</ul><ul>
<li><a href="http://cbrg.inf.ethz.ch/">Computational Biochemistry Research Group</a></li>
</ul><ul>
<li><a href="http://www.geocities.com/RainForest/Vines/8695/software.html">Digital Taxonomy</a></li>
</ul><ul>
<li><a href="http://www.cladistics.org/education/hennig86.html">Hennig 86</a></li>
</ul><ul>
<li><a href="http://www.bioinformaticssolutions.com/">Hyperclean</a>&nbsp;from Bioinformatics Solutions, Inc.</li>
</ul><ul>
<li><a href="http://www.mun.ca/biology/scarr/Directory.html">Memorial University of Newfoundland</a></li>
</ul><ul>
<li><a href="http://morphbank.ebc.uu.se/mrbayes/">Mr. Bayes</a></li>
</ul><ul>
<li><a href="http://www.cladistics.com/about_nona.htm">NONA</a></li>
</ul><ul>
<li><a href="http://evolve.zoo.ox.ac.uk/">Oxford University Evolutionary Biology Group</a></li>
</ul><ul>
<li><a href="http://flatpebble.nceas.ucsb.edu/public/">Paleobiology Database</a></li>
</ul><ul>
<li><a href="http://paup.csit.fsu.edu/index.html">PAUP</a></li>
</ul><ul>
<li><a href="http://evolution.genetics.washington.edu/phylip.html">Phylip Homepage</a></li>
</ul><ul>
<li><a href="http://research.amnh.org/scicomp/projects/poy.php">Poy</a></li>
</ul><ul>
<li><a href="http://www.sinauer.com/">Sinauer Associates</a></li>
</ul><ul>
<li><a href="http://www.cladistics.org/downloads/webtnt.html">TNT</a>-Tree Analysis Using New Technology</li>
</ul><ul>
<li><a href="http://www.treebase.org/treebase/index.html">Tree Base</a></li>
</ul><ul>
<li><a href="http://www.treefinder.de/">Treefinder</a></li>
</ul><ul>
<li><a href="http://www.tree-puzzle.de/">Tree-Puzzle</a></li>
</ul><ul>
<li><a href="http://taxonomy.zoology.gla.ac.uk/rod/treeview.html">Tree View</a>-Taxonomy and Systematics Group at Glasgow</li>
</ul><ul>
<li><a href="http://evolution.genetics.washington.edu/phylip/software.html">Washington University</a>-List of Phylogeny Software</li>
</ul>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1469/prime-minister%E2%80%99s-100k-genome-project</guid>
	<pubDate>Thu, 08 Aug 2013 09:40:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1469/prime-minister%E2%80%99s-100k-genome-project</link>
	<title><![CDATA[Prime Minister’s 100k Genome Project]]></title>
	<description><![CDATA[<p>Genomics Ebgland is destined to sequence 100,000 patients over the next five year in England.&nbsp; A landmark project by british government.</p><p>Genomics England will play a key role in building on the UK&rsquo;s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system &ndash; leading the global race for better tests, better drugs and above all better, more personalised care.</p><p>http://www.genomicsengland.co.uk/100k-genome-project/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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