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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41493?offset=180</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</guid>
	<pubDate>Wed, 06 Dec 2017 09:45:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</link>
	<title><![CDATA[ACANA: An accurate and consistent alignment tool for DNA sequences]]></title>
	<description><![CDATA[<p><span>ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.</span></p><p>Address of the bookmark: <a href="https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm" rel="nofollow">https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37987/ropebwt2-incremental-construction-of-fm-index-for-dna-sequences</guid>
	<pubDate>Thu, 25 Oct 2018 04:48:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37987/ropebwt2-incremental-construction-of-fm-index-for-dna-sequences</link>
	<title><![CDATA[RopeBWT2: Incremental construction of FM-index for DNA sequences]]></title>
	<description><![CDATA[<p><span>RopeBWT2 is an tool for constructing the FM-index for a collection of DNA sequences. It works by incrementally inserting one or multiple sequences into an existing pseudo-BWT position by position, starting from the end of the sequences. This algorithm can be largely considered a mixture of&nbsp;</span><a href="http://dx.doi.org/10.1007/978-3-642-21458-5_20">BCR</a><span>&nbsp;and&nbsp;</span><a href="http://dfmi.sourceforge.net/">dynamic FM-index</a><span>. Nonetheless, ropeBWT2 is unique in that it may&nbsp;</span><em>implicitly</em><span>sort the input into reverse lexicographical order (RLO) or reverse-complement lexicographical order (RCLO) while building the index.</span></p><p>Address of the bookmark: <a href="https://github.com/lh3/ropebwt2" rel="nofollow">https://github.com/lh3/ropebwt2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45244/the-ghost-ancestors-hidden-in-our-dna</guid>
	<pubDate>Tue, 18 Aug 2026 22:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45244/the-ghost-ancestors-hidden-in-our-dna</link>
	<title><![CDATA[The Ghost Ancestors Hidden in Our DNA]]></title>
	<description><![CDATA[<p>Imagine standing in a museum of human evolution.</p><p>There are Neanderthal bones. Denisovan remains. Fossils from ancient relatives of our species. Each specimen gives us another piece of the story of how Homo sapiens came to be.</p><p>But now imagine that one of the most important characters in that story has left behind no fossil, no skull, no bone, and no genome.</p><p>Nothing that a paleontologist could put behind glass.</p><p>And yet, somehow, that ancient population is still speaking.</p><p>It is speaking through us.</p><p>A fascinating new study published in Science (https://www.science.org/doi/10.1126/science.aef8874?) introduces a computational method called TRACE, which allows scientists to search modern human genomes for genetic traces of ancient populations that have never been directly identified.</p><p>For years, scientists have known that our ancestors interacted with Neanderthals and Denisovans. Their DNA still survives in modern human populations. But these may not have been the only ancient humans who crossed paths with our ancestors.</p><p>Using TRACE, researchers found evidence of an unknown archaic population that contributed DNA to the ancestors of modern humans before humans spread beyond Africa.</p><p>Even more surprisingly, they found evidence of a much older lineage&mdash;possibly around 1.8 million years old&mdash;whose genetic legacy may have reached some modern humans indirectly through Denisovans.</p><p>The extraordinary part is that researchers did not need DNA from these mysterious populations to detect them. Instead, they studied the ancestry of modern genomes and looked for genetic patterns that revealed unusually ancient branches of our family history.</p><p>It is almost like finding the footprints of someone who disappeared thousands of years ago&mdash;without ever finding the person themselves.</p><p>These discoveries suggest that human evolution was far more complicated than a simple family tree. Ancient human populations repeatedly separated, migrated, met and exchanged genes. Some eventually disappeared, but pieces of their genetic legacy survived.</p><p>And that means our DNA is more than a biological instruction manual.</p><p>It is also an archive of human history.</p><p>Some of the people recorded in that archive may never have a name or a fossil. But thanks to methods like TRACE, their genetic echoes are finally becoming visible.</p><p>The next big discovery about our ancient past may not come from a fossil in the ground.</p><p>It may already be inside us.</p><p>Reference: Zhang et al., &ldquo;Recovering signatures of archaic hominin introgression using ancestral recombination graphs,&rdquo; Science (2026), DOI: 10.1126/science.aef8874. Detail paper @&nbsp;https://www.science.org/doi/10.1126/science.aef8874?</p><p><br />The TRACE repository (https://github.com/YulinZhang9806/trace) contains the Python package and command-line tools used to infer archaic admixture tracts from ancestral recombination graphs.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/914/welch-lab</guid>
  <pubDate>Mon, 15 Jul 2013 18:21:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Welch Lab]]></title>
  <description><![CDATA[
<p>They are based in the Department of Genetics at the University of Cambridge. </p>

<p>The research covers diverse areas of evolutionary biology, and molecular evolution in particular. It combines theoretical and empirical approaches, and particularly evolutionary inference from genome sequence data.</p>

<p>Links @ http://www.gen.cam.ac.uk/research/welch/GroupPage/Home.html</p>
]]></description>
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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/researchlabs/view/5310/bergman-lab</guid>
  <pubDate>Thu, 03 Oct 2013 17:20:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bergman Lab]]></title>
  <description><![CDATA[
<p>Broad area of research:</p>

<p>Genome Annotation and Functional Genomics</p>

<p>Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences.  Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.</p>

<p>Genome and Molecular Evolution<br />Text and Data Mining</p>

<p>More @ http://bergmanlab.smith.man.ac.uk/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</guid>
	<pubDate>Sat, 10 May 2014 21:24:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</link>
	<title><![CDATA[Memories Can Be Passed Down Through DNA]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/tbPwzII_g6o" frameborder="0" allowfullscreen></iframe>The premise of Assassin's Creed is the reliving of other people's memories stored inside DNA. Well scientists have found that in mice, it actually happens! Anthony is joined by special guest and our friend Tara Long from Hard Science to explain how this process works, and if it might apply to humans as well.

Read More: 
Parental olfactory experience influences behavior and neural structure in subsequent generations
http://www.nature.com/neuro/journal/vaop/ncurrent/abs/nn.3594.html
"Using olfactory molecular specificity, we examined the inheritance of parental traumatic exposure, a phenomenon that has been frequently observed, but not understood."

What Is Epigenetics?
http://www.sciencemag.org/content/330/6004/611
"The cells in a multicellular organism have nominally identical DNA sequences (and therefore the same genetic instruction sets), yet maintain different terminal phenotypes. This nongenetic cellular memory, which records developmental and environmental cues (and alternative cell states in unicellular organisms), is the basis of epi-(above)-genetics."

Epigenetics
http://en.wikipedia.org/wiki/Epigenetics

Watch More:
How to Change Your Genes
https://www.youtube.com/watch?v=B5DU9lgbsSE
TestTube Wild Card
http://testtube.com/dnews/dnews-231-how-too-many-screens-affect-our-brain?utm_source=YT&utm_medium=DNews&utm_campaign=DNWC
Is Sexiness Hereditary?
https://www.youtube.com/watch?v=z6STRCncvM8
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Discovery News http://discoverynews.com]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12995/national-center-for-bioinformatics-ncb</guid>
  <pubDate>Wed, 23 Jul 2014 14:10:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[National Center for Bioinformatics (NCB)]]></title>
  <description><![CDATA[
<p>NCB is offering M.Phil and Ph.D programs in the area of Bioinformatics. The major goal of NCB is to promote quality training and research in the area of Bioinformatics. Bioinformatics originated as a cross-disciplinary field as the need for computational sections to research problem raised in biomedicine. </p>

<p>More at http://ncb.qau.edu.pk/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27695/the-kingsley-lab</guid>
  <pubDate>Fri, 03 Jun 2016 09:55:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Kingsley Lab]]></title>
  <description><![CDATA[
<p>The Molecular Basis of Vertebrate Evolution. Naturally occurring species show spectacular differences in morphology, physiology, behavior, disease susceptibility, and life span. Although the genomes of many organisms have now been completely sequenced, Kingsley lab still know relatively little about the specific DNA sequence changes that underlie interesting species-specific traits. Kingsley lab laboratory is using a combination of genetic and genomic approaches to identify the detailed molecular mechanisms that control evolutionary change in vertebrates.</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35125/eugene-v-koonin-lab</guid>
  <pubDate>Tue, 09 Jan 2018 05:01:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[Eugene V. Koonin Lab]]></title>
  <description><![CDATA[
<p>Interested in understanding the evolution of life. To obtain glimpses of such understanding, we employ existing and new methods of computational biology to perform research in several major areas.</p>

<p>https://www.ncbi.nlm.nih.gov/research/groups/koonin/</p>
]]></description>
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