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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/13226?offset=1360</link>
	<atom:link href="https://bioinformaticsonline.com/related/13226?offset=1360" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4653/human-genome-meeting-2014-geneva-switzerland</guid>
  <pubDate>Fri, 20 Sep 2013 12:36:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Human Genome Meeting 2014, Geneva, Switzerland]]></title>
  <description><![CDATA[
<p>The spectacular advances of the last few years resulted in the rapid analysis of the genome sequence of each individual. The biomedical world is now faced with the enormous challenges of assigning pathogenicity to each genomic variant, the functional analysis of the genome of each individual, and the accurate and detailed phenotypic characterization. Advances in these challenges are likely to fundamentally change the medical practice in a global scale.</p>

<p>This 2014 HUGO Meeting in Geneva will be a Forum for discussions on innovative approaches, and proposals to tackle the anticipated challenges.</p>

<p>Time : 27 April 2014 - 30 April 2014 </p>

<p>For enquiries, please email hugo2014@mci-group.com or visit www.hugo-international.org</p>

<p>More at http://www.hgm2014-geneva.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43084/frequently-used-bioinformatics-tools-for-viral-genome-analysis</guid>
	<pubDate>Wed, 23 Jun 2021 07:40:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43084/frequently-used-bioinformatics-tools-for-viral-genome-analysis</link>
	<title><![CDATA[Frequently used bioinformatics tools for viral genome analysis !]]></title>
	<description><![CDATA[<p><strong>IVA: accurate de novo assembly of RNA virus genomes.</strong><br /> Hunt M, Gall A, Ong SH, Brener J, Ferns B, Goulder P, Nastouli E, Keane JA, Kellam P, Otto TD.<br /> Bioinformatics. 2015 Jul 15;31(14):2374-6. doi: <a href="http://bioinformatics.oxfordjournals.org/content/31/14/2374.long">10.1093/bioinformatics/btv120</a>. Epub 2015 Feb 28.</p><p><a href="http://www.nature.com/nmeth/journal/v9/n1/full/nmeth.1814.html"><strong>Adapter sequences</strong></a>:<br /> <strong>Optimal enzymes for amplifying sequencing libraries.</strong><br /> Quail, M. a et al. Nat. Methods 9, 10-1 (2012).</p><p><a href="http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111"><strong>GAGE</strong></a>:<br /> <strong>GAGE: A critical evaluation of genome assemblies and assembly algorithms.</strong><br /> Salzberg, S. L. et al. Genome Res. 22, 557-67 (2012).</p><p><a href="http://www.biomedcentral.com/1471-2105/14/160"><strong>KMC</strong></a>:<br /> <strong>Disk-based k-mer counting on a PC.</strong><br /> Deorowicz, S., Debudaj-Grabysz, A. &amp; Grabowski, S. BMC Bioinformatics 14, 160 (2013).</p><p><a href="http://genomebiology.com/2014/15/3/R46"><strong>Kraken</strong></a>:<br /> <strong>Kraken: ultrafast metagenomic sequence classification using exact alignments.</strong><br /> Wood, D. E. &amp; Salzberg, S. L. Genome Biol. 15, R46 (2014).</p><p><a href="http://genomebiology.com/2004/5/2/r12"><strong>MUMmer</strong></a>:<br /> <strong>Versatile and open software for comparing large genomes.</strong><br /> Kurtz, S. et al. Genome Biol. 5, R12 (2004).</p><p><strong>R</strong>:<br /> <strong>R: A language and environment for statistical computing.</strong><br /> R Core Team (2013). R Foundation for Statistical Computing, Vienna, Austria. URL <a href="http://www.R-project.org/">http://www.R-project.org/</a>.</p><p><a href="http://nar.oxfordjournals.org/content/39/9/e57"><strong>RATT</strong></a>:<br /> <strong>RATT: Rapid Annotation Transfer Tool.</strong><br /> Otto, T. D., Dillon, G. P., Degrave, W. S. &amp; Berriman, M. Nucleic Acids Res. 39, e57 (2011).</p><p><a href="http://bioinformatics.oxfordjournals.org/content/25/16/2078.abstract"><strong>SAMtools</strong></a>:<br /> <strong>The Sequence Alignment/Map format and SAMtools.</strong><br /> Li, H. et al. Bioinformatics 25, 2078-9 (2009).</p><p><a href="http://bioinformatics.oxfordjournals.org/content/early/2014/04/12/bioinformatics.btu170"><strong>Trimmomatic</strong></a>:<br /> <strong>Trimmomatic: A flexible trimmer for Illumina Sequence Data.</strong><br /> Bolger, A. M., Lohse, M. &amp; Usadel, B. Bioinformatics 1-7 (2014).</p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43329/postdoc-position-at-kiel-university-germany</guid>
  <pubDate>Sat, 28 Aug 2021 01:16:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Kiel University, Germany]]></title>
  <description><![CDATA[
<p>In the Genomic Microbiology Group of Prof. Tal Dagan at the Institute<br />of Microbiology at Kiel University, Germany, a</p>

<p>Postdoc position (m/w/d)</p>

<p>in the field of computational evolutionary microbiology is available<br />for an initially limited period of 36 months at the earliest possible<br />date. The weekly working time corresponds to 100% of full employment<br />(If the legal requirements under collective bargaining law are met, the<br />tariff grouping is carried out up to pay scale 13 TV-L. The obligation<br />to teach amounts to 4 hours.</p>

<p>The Genomic Microbiology Group research interests are focused on<br />microbial genome evolution with an emphasis on the study of lateral gene<br />transfer. In our research we use both computational and experimental<br />approaches (see www.uni-kiel.de/genomik). The position offers the<br />opportunity to develop an independent research profile within the group<br />research focus. The successful applicant is expected to be involved<br />in teaching of bioinformatics and molecular evolution, including the<br />development of teaching materials (lectures/exercises/short videos).</p>

<p>Your profile:<br />· Doctoral or PhD degree in Molecular Evolution, Bioinformatics or<br />related fields.<br />· Knowledge and experience in programming (e.g., Python) and<br />biostatistical analysis (e.g., with R or MatLab).<br />· Any of the following expertise is an advantage: the analysis of<br />genomic or transcriptomic data, phylogenetic reconstruction,<br />comparative genomics.<br />· Good oral and written communication skills in English.<br />· Ability to teach in German is an advantage (alternatively, an<br />indication to do so from the 2nd year on).<br />· Skills and motivation to communicate and interact with other<br />scientists.<br /> <br />The Christian-Albrechts-University sees itself as a modern and<br />cosmopolitan employer. We welcome your application regardless of your age,<br />gender, cultural and social background, religion, ideology, disability<br />or sexual identity. We promote equality of the sexes.</p>

<p>The Christian-Albrechts-University is committed to the employment of<br />people with disabilities. Preference will be given to applications from<br />severely handicapped persons and persons of equal standing, provided<br />they are suitable.</p>

<p>We expressly welcome applications from people with a migration background.</p>

<p>For enquiries regarding the position, teaching obligations and research<br />topic please contact Prof. Tal Dagan: tdagan@ifam.uni-kiel.de.</p>

<p>Applications should be submitted by email to Mrs. Haacks<br />(dhaacks@ifam.uni-kiel.de) as a single PDF and include: (1) a letter of<br />motivation (max 1 page, Arial 11, line spacing 1.15), (2) CV, (3) PhD<br />certificate. Please use 'GMG postdoc application - [your name]'<br />as a subject.</p>

<p>Please, refrain from sending us application photos.</p>

<p>Application deadline:  August 31 2021 or until the position is<br />filled. Interviews will take place during September/October 2021. The<br />planned starting date for the position is flexible (but in 2021).</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</guid>
	<pubDate>Wed, 24 Apr 2024 04:33:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</link>
	<title><![CDATA[16sRNA Database Download]]></title>
	<description><![CDATA[<p>Downloading 16S rRNA databases can be crucial for various bioinformatics analyses, especially in microbiome research. However, it's important to note that databases can vary based on your specific needs, such as the taxonomic coverage you require or the type of analysis you're performing. Here's a general guideline on how you can obtain 16S rRNA databases:</p><ol>
<li>
<p><span>NCBI (National Center for Biotechnology Information)</span>:</p>
<ul>
<li>NCBI provides various databases related to genetic information, including 16S rRNA sequences.</li>
<li>You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (<a href="https://www.ncbi.nlm.nih.gov/nucleotide/" target="_new">https://www.ncbi.nlm.nih.gov/nucleotide/</a>).</li>
<li>Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.</li>
<li>You can download sequences individually or in batches using the provided tools.</li>
</ul>
</li>
<li>
<p><span>GreenGenes</span>:</p>
<ul>
<li>GreenGenes is a widely used 16S rRNA gene sequence database.</li>
<li>You can access it at <a target="_new">http://greengenes.secondgenome.com/</a>.</li>
<li>GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.</li>
</ul>
</li>
<li>
<p><span>SILVA</span>:</p>
<ul>
<li>SILVA (<a href="https://www.arb-silva.de/" target="_new">https://www.arb-silva.de/</a>) is another comprehensive database for ribosomal RNA (rRNA) sequences.</li>
<li>It covers not only 16S rRNA but also other ribosomal RNA sequences.</li>
<li>SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.</li>
</ul>
</li>
<li>
<p><span>Ribosomal Database Project (RDP)</span>:</p>
<ul>
<li>RDP (<a target="_new">http://rdp.cme.msu.edu/</a>) is a curated database that offers 16S rRNA sequences.</li>
<li>It provides tools for sequence analysis and classification.</li>
<li>You can download sequences and taxonomy information from their website.</li>
</ul>
</li>
<li>
<p><span>QIIME (Quantitative Insights Into Microbial Ecology)</span>:</p>
<ul>
<li>QIIME (<a href="https://qiime2.org/" target="_new">https://qiime2.org/</a>) is a widely used bioinformatics platform for microbiome analysis.</li>
<li>It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.</li>
<li>QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.</li>
</ul>
</li>
</ol><p>Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.</p><p>&nbsp;</p><p>NCBI 16s RNA database location&nbsp;ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<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>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2422/bioinformatics-codes-search</guid>
	<pubDate>Thu, 15 Aug 2013 11:08:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2422/bioinformatics-codes-search</link>
	<title><![CDATA[Bioinformatics Codes Search]]></title>
	<description><![CDATA[<p>I bet, this website will be your best friend in near future. This helps us to explore the existing open source codes and learn from it.</p>
<p>You can find some useful open source bioinformatics codes for your analysis work. You can use the left bar options to filtere out or narrow down your search result. This webpage can be an useful resource for a beginners bioinformatician as it contain several bioinformatics basics script that are commonly used by biological programmers and biologist.</p>
<p>Stand on the slumped, dandruff-covered shoulders of millions of computer nerds. _/\_</p>
<p>Enjoy the code and research work.</p>
<p>http://code.ohloh.net/search?s=bioinformatics</p><p>Address of the bookmark: <a href="http://code.ohloh.net/search?s=bioinformatics" rel="nofollow">http://code.ohloh.net/search?s=bioinformatics</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</guid>
	<pubDate>Fri, 27 Sep 2013 11:28:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</link>
	<title><![CDATA[Evolution and Cancer]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/j3uKOcNwYBw" frameborder="0" allowfullscreen></iframe>Air date:  Wednesday, January 04, 2012, 3:00:00 PM
Time displayed is Eastern Time, Washington DC Local  
 
Category:  Wednesday Afternoon Lectures  
Description:  There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." 

David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. 

In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series  
Author:  Dr. David Botstein, Princeton University  
Runtime:  00:59:58  

Permanent link:  http://videocast.nih.gov/launch.asp?17046]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5191/programming-language-to-build-synthetic-dna</guid>
	<pubDate>Mon, 30 Sep 2013 16:37:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5191/programming-language-to-build-synthetic-dna</link>
	<title><![CDATA[Programming language to build synthetic DNA]]></title>
	<description><![CDATA[<p style="color: #333333; font-size: 13px; font-style: normal; font-weight: normal; text-align: start;">A team led by <a href="http://homes.cs.washington.edu/~seelig/index.html">Georg Seelig</a>&nbsp;(<a href="http://homes.cs.washington.edu/~seelig/index.html">http://homes.cs.washington.edu/~seelig/index.html</a>) at&nbsp;University of Washington has developed a programming language for chemistry that it hopes will streamline efforts to design a network that can guide the behavior of chemical-reaction mixtures in the same way that embedded electronic controllers guide cars, robots and other devices. In medicine, such networks could serve as &ldquo;smart&rdquo; drug deliverers or disease detectors at the cellular level.</p><p style="color: #333333; font-size: 13px; font-style: normal; font-weight: normal; text-align: start;">Reference &amp; More @</p><p style="color: #333333; font-size: 13px; font-style: normal; font-weight: normal; text-align: start;"><a href="http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2013.189.html">http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2013.189.html</a></p><p style="color: #333333; font-size: 13px; font-style: normal; font-weight: normal; text-align: start;"><a href="http://www.washington.edu/news/2013/09/30/uw-engineers-invent-programming-language-to-build-synthetic-dna/">http://www.washington.edu/news/2013/09/30/uw-engineers-invent-programming-language-to-build-synthetic-dna/</a></p><p style="color: #333333; font-size: 13px; font-style: normal; font-weight: normal; text-align: start;">Image source:&nbsp;washington.edu</p><p style="color: #333333; font-size: 13px; font-style: normal; font-weight: normal; text-align: start;"><img src="http://www.washington.edu/news/files/2013/09/Programmable-chemistry-2.jpg" alt="image" style="border: 0px; border: 0px;"></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22938/research-assistant-in-computational-biology</guid>
  <pubDate>Wed, 24 Jun 2015 07:55:16 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research assistant in computational biology]]></title>
  <description><![CDATA[
<p>http://www.au.dk/en/about/vacant-positions/scientific-positions/stillinger/Vacancy/show/743161/5283/</p>

<p>Qualifications:<br />MSc degree in computer science, engineering, genetics or similar field with a strong emphasis on computational methods.</p>

<p>Deadline<br />01.08.2015</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34146/phylogenetic-molecular-genetics-terms-and-definitions</guid>
	<pubDate>Tue, 08 Aug 2017 08:20:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34146/phylogenetic-molecular-genetics-terms-and-definitions</link>
	<title><![CDATA[Phylogenetic &amp; Molecular Genetics Terms and Definitions]]></title>
	<description><![CDATA[<p><strong>analog </strong>-- A feature that appears similar in two taxa which have originated from two different ancestors.</p><p><strong>ancestor</strong> -- Any organism, population, or species from which some other organism, population, or species is descended by reproduction.</p><p><strong>apomorphy </strong>-- specialized (=derived) characters of an organism.</p><p><strong>basal group</strong> -- The earliest diverging group within a clade; for instance, to hypothesize that sponges are basal animals is to suggest that the lineage(s) leading to sponges diverged from the lineage that gave rise to all other animals.</p><p><strong>biological classification </strong>-- The orderly arrangement of organisms in hierarchical system that ideally reflects evolutionary history.</p><p><strong>cDNA</strong> -- Complementary DNA; DNA that is synthesized, by reverse transcriptase, from a Messenger RNA template ( Messenger RNA contains the coded information for protein synthesis).</p><p><strong>character</strong> -- Heritable trait possessed by an organism.</p><p><strong>character state</strong> -- characters are usually described in terms of their states, for example: "hair present" vs. "hair absent," where "hair" is the character, and "present" and "absent" are its states.</p><p><strong>clade</strong> -- A monophyletic taxon; a group of organisms which includes the most recent common ancestor of all of its members and all of the descendants of that most recent common ancestor. From the Greek word "klados", meaning branch or twig.</p><p><strong>cladogenesis</strong> -- The development of a new clade; the splitting of a single lineage into two distinct lineages; speciation.</p><p><strong>cladogram</strong> -- A diagram, resulting from a cladistic analysis, which depicts a hypothetical branching sequence of lineages leading to the taxa under consideration. The points of branching within a cladogram are called nodes. All taxa occur at the endpoints of the cladogram.</p><p><strong>convergence</strong> -- Similarities which have arisen independently in two or more organisms that are not closely related. Contrast with homology.&nbsp;</p><p><strong>crown group</strong> -- All the taxa descended from a major cladogenesis event, recognized by possessing the clade's synapomorphy. See: stem group.</p><p><strong>derived</strong> -- Describes a character state that is present in one or more subclades, but not all, of a clade under consideration. A derived character state is inferred to be a modified version of the primitive condition of that character, and to have arisen later in the evolution of the clade. For example, "presence of hair" is a primitive character state for all mammals, whereas the "hairlessness" of whales is a derived state for one subclade within the Mammalia.</p><p><strong>diversity</strong> -- Term used to describe numbers of taxa, or variation in morphology.&nbsp;</p><p><strong>evolution</strong> -- Darwin's definition: descent with modification. The term has been variously used and abused since Darwin to include everything from the origin of man to the origin of life.</p><p><strong>evolutionary tree</strong> -- A diagram which depicts the hypothetical phylogeny of the taxa under consideration. The points at which lineages split represent ancestor taxa to the descendant taxa appearing at the terminal points of the cladogram.</p><p><strong>expressed sequence tag (EST)</strong> -- A partial coding sequence isolated at random from a cDNA library, used for identification and mapping of coding sequences, for discovery of new genes and (by reference to sequence data banks) for discovery of identities with other genes.</p><p><strong>extinction</strong> -- When all the members of a clade or taxon die, the group is said to be extinct.</p><p><strong>genetic marker -- </strong>A DNA sequence that can be recognized and thus used to characterize the larger DNA sequence and the chromosome in which it occurs.&nbsp;</p><p><strong>homolog </strong>-- A feature that appears similar in two or more taxa with a common ancestor that also possessed that feature.</p><p><strong>homology</strong> -- Two structures are considered homologous when they are inherited from a common ancestor which possessed the structure. This may be difficult to determine when the structure has been modified through descent.</p><p><strong>hypothesis</strong> -- A concept or idea that can be falsified by various scientific methods.</p><p><strong>ingroup</strong> -- In a cladistic analysis, the set of taxa which are hypothesized to be more closely related to each other than any are to the outgroup.</p><p><strong>lineage</strong> -- Any continuous line of descent; any series of organisms connected by reproduction by parent of offspring.</p><p><strong>monophyletic</strong> -- Term applied to a group of organisms which includes the most recent common ancestor of all of its members and all of the descendants of that most recent common ancestor. A monophyletic group is called a clade.</p><p><strong>outgroup</strong> -- In a cladistic analysis, any taxon used to help resolve the polarity of characters, and which is hypothesized to be less closely related to each of the taxa under consideration than any are to each other.</p><p><strong>paraphyletic</strong> -- Term applied to a group of organisms which includes the most recent common ancestor of all of its members, but not all of the descendants of that most recent common ancestor.</p><p><strong>parsimony</strong> -- Refers to a rule used to choose among possible cladograms, which states that the cladogram implying the least number of changes in character states is the best.</p><p><strong>phylogenetics</strong> -- Field of biology that deals with the relationships between organisms. It includes the discovery of these relationships, and the study of the causes behind this pattern.</p><p><strong>phylogeny</strong> -- The evolutionary relationships among organisms; the patterns of lineage branching produced by the true evolutionary history of the organisms being considered.</p><p><strong>plesiomorphy</strong> -- A primitive character state for the taxa under consideration.</p><p><strong>polarity of characters</strong> -- The states of characters used in a cladistic analysis, either original or derived. Original characters are those acquired by an ancestor deeper in the phylogeny than the most recent common ancestor of the taxa under consideration. Derived characters are those acquired by the most recent common ancestor of the taxa under consideration.</p><p><strong>polyphyletic</strong> -- Term applied to a group of organisms which does not include the most recent common ancestor of those organisms; the ancestor does not possess the character shared by members of the group.</p><p><strong>primitive</strong> -- Describes a character state that is present in the common ancestor of a clade. A primitive character state is inferred to be the original condition of that character within the clade under consideration. For example, "presence of hair" is a primitive character state for all mammals, whereas the "hairlessness" of whales is a derived state for one subclade within the Mammalia.</p><p><strong>radiation</strong> -- Event of rapid cladogenesis, believed to occur under conditions where a new feature permits a lineage to move into a new niche or new habitat, and is then called an adaptive radiation.</p><p><strong>rank</strong> -- In traditional taxonomy, taxa are ranked according to their level of inclusiveness. Thus a genus contains one or more species, a family includes one or more genera, and so on.</p><p><strong>relatedness</strong> -- Two clades are more closely related when they share a more recent common ancestor between them than they do with any other clade.</p><p><strong>repetitive DNA</strong> -- Sequences of DNA that are found to be repeated, sometimes thousands of times over.&nbsp;&nbsp;</p><p><strong>reticulation</strong> -- Joining of separate lineages on a phylogenetic tree, generally through hybridization or through lateral gene transfer. Fairly common in certain land plant clades; reticulation is thought to be rare among metazoans.</p><p><strong>selection</strong> -- Process which favors one feature of organisms in a population over another feature found in the population. This occurs through differential reproduction -- those with the favored feature produce more offspring than those with the other feature, such that they become a greater percentage of the population in the next generation.</p><p><strong>sister group</strong> -- The two clades resulting from the splitting of a single lineage.</p><p><strong>stem group</strong> -- All the taxa in a clade preceding a major cladogenesis event. They are often difficult to recognize because they may not possess synapomorpies found in the crown group.</p><p><strong>sympleisiomorphy</strong> &ndash; A ancestral character shared by the taxa under consideration</p><p><strong>synapomorphy</strong> -- A character which is derived, and because it is shared by the taxa under consideration, is used to infer common ancestry (shared derived state).</p><p><strong>synteny</strong> -- Portions of chromosomes in which gene order is conserved.&nbsp;</p><p><strong>systematics</strong> -- Field of biology that deals with the diversity of life. Systematics is usually divided into the two areas of phylogenetics and taxonomy.</p><p><strong>taxon</strong> -- Any named group of organisms, not necessarily a clade</p><p><strong>taxonomy</strong> -- The science of naming and classifying organisms.&nbsp;</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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