<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/45306?offset=440</link>
	<atom:link href="https://bioinformaticsonline.com/related/45306?offset=440" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44934/genomic-basis-of-evolutionary-innovations-gevol</guid>
	<pubDate>Sat, 06 Dec 2025 06:11:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44934/genomic-basis-of-evolutionary-innovations-gevol</link>
	<title><![CDATA[Genomic Basis of Evolutionary Innovations (GEvol)]]></title>
	<description><![CDATA[<p>The Priority Programme (SPP 2349) funded by German Science Foundation (DFG) started 2022: &bdquo;Genomic Basis of Evolutionary Innovations (GEvol)&ldquo;</p>
<p>GEvol is unique as it will use, for the first time, a large taxonomic group to focus on one goal: to characterise the dynamics and mechanisms of genomic innovations underlying novel traits using comparative evolutionary genomics (and related data).<br>Thus, projects participating in GEvol we will ask fundamental evolutionary questions such as:<br>1. At what level is evolution repeatable?<br>2. How does genomic plasticity interfere with phenotypic plasticity during evolution?<br>3. How do inter- and intra-specific interactions influence genomic architectures?<br>4. How predictable is phenotypic variation given some knowledge about the dynamics and mechanisms of underlying genome evolution?</p><p>Address of the bookmark: <a href="https://g-evol.uni-muenster.de/open-positions/" rel="nofollow">https://g-evol.uni-muenster.de/open-positions/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/45297/comparative-genomics-of-gene-expression-lab</guid>
  <pubDate>Wed, 09 Sep 2026 03:35:46 -0500</pubDate>
  <link></link>
  <title><![CDATA[Comparative genomics of gene expression lab]]></title>
  <description><![CDATA[
<p>The core expertise of the lab is comparative genomics. We combine evolutionary bioinformatics and molecular biology to understand the mechanism, function and evolution of genes.<br />We study the processes of gene expression and protein synthesis, and we are particularly interested in the phenomenon of translational recoding (programmed exceptions to the genetic code). For more information, see Research.</p>

<p>More at https://www.mariottigenomicslab.com/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4546/sowdhamini-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:19:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[SOWDHAMINI Lab]]></title>
  <description><![CDATA[
<p>Genome sequencing projects have enormous potential for benefiting human endeavors. However, just as acquiring a language's vocabulary does not enable one to speak it, databases that list the amino acid composition of proteins do not directly tell us much about these proteins' higher-level structure and function. The most productive way to indirectly exploit these databases has been to start with the small number of proteins that are fully-characterised and to assume that other "similar" proteins will have a related structure and function. Proteins with very similar amino acid sequence are "no-brainers", but the real test, which our group largely focuses on, is to detect the "essential" similarity in proteins whose non-critical sections have experienced random rearrangements during evolution. In such cases functionally similar proteins may have less than 25% sequence overlap.</p>

<p>More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/38383/sidow-lab</guid>
  <pubDate>Fri, 07 Dec 2018 09:06:30 -0600</pubDate>
  <link></link>
  <title><![CDATA[Sidow Lab]]></title>
  <description><![CDATA[
<p>We study mechanisms of cancer evolution by using state-of-the-art genomic approaches at the bench and in analysis. Accurate genome reconstruction is our other major area of interest. We also collaborate on important questions for which our expertise in genomics and computation is relevant. Arend's biosketch highlights some of our past contributions.</p>

<p>http://www.sidowlab.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43769/ideaslab-workshop</guid>
  <pubDate>Wed, 02 Feb 2022 06:13:48 -0600</pubDate>
  <link></link>
  <title><![CDATA["IdeasLab"* workshop !]]></title>
  <description><![CDATA[
<p>A new, grant-funded opportunity seeks early career researchers interested<br />in life's origins: https://templetonideaslab.umbc.edu/</p>

<p>Applications are invited to an all-expenses paid position at a 5-day<br />"IdeasLab"* workshop to be held near Prague CZ in June 2022. Thirty<br />successful applicants will be drawn in equal number from the relevant<br />sectors biological evolution, A-Life anbd theoretical physics. The week's<br />activities will lead these thirty to form interdisciplinary teams which<br />each propose how they can advance frontiers of abiogenesis research. Up to<br />$5 million total funding will be available for developing these ideas<br />produced by the week's activities. Further details of the event,<br />including the online application form, are found at the link posted above</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1161/genomics-for-bioinformatician</guid>
	<pubDate>Sat, 20 Jul 2013 07:03:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1161/genomics-for-bioinformatician</link>
	<title><![CDATA[Genomics for Bioinformatician]]></title>
	<description><![CDATA[<p>Genomics is the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping efforts. The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy and other interactions between loci and alleles within the genome. In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology or genetics and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genome's networks.<br /><br />Genomics was established by Fred Sanger when he first sequenced the complete genomes of a virus and a mitochondrion. His group established techniques of sequencing, genome mapping, data storage, and bioinformatic analyses in the 1970-1980s. A major branch of genomics is still concerned with sequencing the genomes of various organisms, but the knowledge of full genomes has created the possibility for the field of functional genomics, mainly concerned with patterns of gene expression during various conditions. The most important tools here are microarrays and bioinformatics. Study of the full set of proteins in a cell type or tissue, and the changes during various conditions, is called proteomics. A related concept is materiomics, which is defined as the study of the material properties of biological materials (e.g. hierarchical protein structures and materials, mineralized biological tissues, etc.) and their effect on the macroscopic function and failure in their biological context, linking processes, structure and properties at multiple scales through a materials science approach. The actual term 'genomics' is thought to have been coined by Dr. Tom Roderick, a geneticist at the Jackson Laboratory (Bar Harbor, ME) over beer at a meeting held in Maryland on the mapping of the human genome in 1986.<br /><br />The outcome of almost two years of intense discussions with literally hundreds of scientists and members of the public, has three major areas of focus: Genomics to Biology, Genomics to Health, and Genomics to Society.<br /><br /><strong><em>Genomics to Biology:</em></strong>&nbsp;<br />The human genome sequence provides foundational information that now will allow development of a comprehensive catalog of all of the genome's components, determination of the function of all human genes, and deciphering of how genes and proteins work together in pathways and networks.<br /><br /><strong><em>Genomics to Health:<br /></em></strong>Completion of the human genome sequence offers a unique opportunity to understand the role of genetic factors in health and disease, and to apply that understanding rapidly to prevention, diagnosis, and treatment. This opportunity will be realized through such genomics-based approaches as identification of genes and pathways and determining how they interact with environmental factors in health and disease, more precise prediction of disease susceptibility and drug response, early detection of illness, and development of entirely new therapeutic approaches.<br /><br /><strong><em>Genomics to Society:</em>&nbsp;<br /></strong>Just as the HGP has spawned new areas of research in basic biology and in health, it has created new opportunities in exploring the ethical, legal, and social implications (ELSI) of such work. These include defining policy options regarding the use of genomic information in both medical and non-medical settings and analysis of the impact of genomics on such concepts as race, ethnicity, kinship, individual and group identity, health, disease, and "normality" for traits and behaviors.<br /><br />This vision for the future of genomics is not just about the NHGRI. It encompasses the whole field of genomics, including the work of all the other Institutes and Centers at the NIH and of a number of other federal agencies. All of the NIH Institutes are already taking full advantage of the sequence and will apply its data to the better understanding of both rare and common diseases, almost all of which have a genetic component. A recent example of the way that the HGP and the knowledge and new technologies it has spawned are already facilitating science is the extremely rapid sequencing by groups in Canada and at the Centers for Disease Control and Prevention (CDC) in Atlanta of the genome of the virus that causes Severe Acute Respiratory Syndrome (SARS). The sequencing of the SARS virus genome provides insight into this new and deadly disease at a speed never before possible in science. In turn, this should lead to the rapid development of diagnostic tests and, in time, vaccines and effective treatments.<br /><br /><strong>Links for the addition material available on Net</strong></p><p><a href="http://pevsnerlab.kennedykrieger.org/bioinformatics/bioinf10_genomes.htm">Genomes and genomics:</a></p><p><a href="http://www.123genomics.com/learning.html">Bioinformatics and Genomics:</a></p><p><a href="http://www.ebi.ac.uk/pdbe/docs/roadshow_tutorial/strgenomics/tutorial.html">Structural genomics tutorial:</a></p><p><a href="http://www.hgu.mrc.ac.uk/Users/Philippe.Gautier/tutorial/index.html">Comparative Genomics Tutorial:</a></p><p><a href="http://www.scfbio-iitd.res.in/tutorial/genomics.html">GENOME TUTORIAL:</a></p><p><a href="http://genomebiology.com/content/pdf/gb-2001-3-1-reviews2001.pdf">Tools and resources for identifying protein families, domains and motifs</a></p><p><a href="http://www.ornl.gov/sci/techresources/Human_Genome/posters/chromosome/tools.shtml">Bioinformatics Tools</a><a href="http://www.ornl.gov/sci/techresources/Human_Genome/posters/chromosome/tools.shtml">&nbsp;<br />Tips, Tutorials, and Terminology for Using Selected Resources in Genome Database Guide:</a></p><p><a href="http://www.doe-mbi.ucla.edu/Reprints/R31%20Strong%20A%20Web-based%20Comparative%20Genomics%20tutorial%20Microbiology%20Eduction%202004.pdf">A Web-Based Comparative Genomics Tutorial for Investigating Microbial Genomes:</a></p><p><a href="http://www.genome.gov/27530225">Free Online Tutorials Teach Anyone How to Use Genome Databases:</a></p><p><a href="http://mkweb.bcgsc.ca/circos/?tutorials">Circos to create concise, explanatory, unique and print-ready visualizations of your data:</a></p><p><a href="http://www.igd.cornell.edu/Comparative%20Genomics/Comparative%20Genomics%20Proj.html">Genomics and Comparative Genomics</a><a href="http://www.igd.cornell.edu/Comparative%20Genomics/Comparative%20Genomics%20Proj.html">&nbsp;Learning Module:</a></p><p><a href="http://psb.stanford.edu/psb10/conference-materials/tutorials/compgen-notes.pdf">Computational Challenges in Comparative Genomics</a></p><p><a href="http://psb.stanford.edu/psb10/conference-materials/tutorials/compgen-notes.pdf">A Tutorial:</a></p><p><a href="http://gramene.agrinome.org/tutorials/modules_tutorial.pdf">A Comparative Genomics Resource for Grains</a>:</p><p><a href="http://www.plantcell.org/cgi/content/full/21/12/3718">PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants:</a></p><p><a href="http://en.wikipedia.org/wiki/VISTA_(comparative_genomics)">VISTA</a><a href="http://en.wikipedia.org/wiki/VISTA_(comparative_genomics)">:</a></p><p>Software for Genomics</p><ol>
<li><strong>Artemis</strong>&nbsp;Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation.</li>
<li><strong>Chromas&nbsp;</strong>It will display and prints chromatogram files from ABI automated DNA sequencers, and Staden SCF files which the analysis programs for ALF, Li-Cor and Visible Genetics OpenGene sequencers can create.</li>
<li><strong>Glimmer</strong>&nbsp;A system for finding genes in microbial DNA, especially the genomes of bacteria and archaea.Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DN</li>
<li><strong>Glimmer</strong>&nbsp;HMM&nbsp;A fast and accurate gene finder based on a GHMM architecture, developed specifically for eukaryotes. It incorporates splice site models adapted from the GeneSplicer program and uses interpolated Markov models for evaluating the coding regions.</li>
<li><strong>Glimmer</strong>&nbsp;M&nbsp;A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programming algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. The d</li>
<li><strong>MUMmer</strong>&nbsp;MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form.</li>
<li><strong>pDRAW</strong>&nbsp;pDRAW32 is being developed as a free time hobby project. It is far from finished, but as it has reached a point where it could be helpful for many labs, it is now available to the scientific community.</li>
<li><strong>Sequin</strong>&nbsp;Sequin is a stand-alone software tool developed by the NCBI for submitting and updating entries to the GenBank, EMBL, or DDBJ sequence databases. It is capable of handling simple submissions that contain a single short mRNA sequence, and complex submissio</li>
<li><strong>Staden&nbsp;</strong>The Staden Package consists of a series of tools for DNA sequence preparation (pregap4), assembly (gap4), editing (gap4) and DNA/protein sequence analysis (spin).</li>
</ol><p>For more software @&nbsp;<a href="http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools">http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10391/research-associate-ra-at-iob</guid>
  <pubDate>Mon, 05 May 2014 08:38:54 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate (RA) at IOB]]></title>
  <description><![CDATA[
<p>Applications are invited for a post of Research Associate (RA) or Senior Research Fellow (SRF) in the ICMR project on "Integrated Analysis of Multi-omics Data in Human Gliomas".</p>

<p>We are looking for a motivated candidate for handling proteomic and/or transcriptomic and other data with a strong background in bioinformatics tools and database development. The project will include identification of novel peptides from mass spectrometry-based proteomic data.</p>

<p>Familiarity with statistical tools or wet lab experience will be an added advantage. The position is open for immediate appointment and available for two years. The applicant will be appointed as Research Associate or Senior Research Fellow based on qualifications as detailed below:</p>

<p>Research Associate: Ph.D. in Biological Science or Bioinformatics with relevant publications in peer reviewed journals. Familiarity with bioinformatics tools, database development, programming skills and proteomic and/or other omics data analysis. Salary will be as per ICMR rules and guidelines.</p>

<p>Senior Research Fellow: M.Sc./B.Tech. in any branch of biology/ biotechnology/bioinformatics, with minimum 2 years of research experience (essential). Familiarity with bioinformatics tools, database development, programming skills and proteomic data analysis. Salary will be as per ICMR rules and guidelines.</p>

<p>Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.</p>

<p>Interested candidates may send a Letter of Interest and CV by email to: ravi@ibioinformatics.org on or before May 15th, 2014.</p>

<p>Contact:<br />Dr. Ravi Sirdeshmukh<br />Distinguished Scientist &amp; Associate Director, IOB,<br />Principal Advisor MSMC/MSCTR</p>

<p>Advertisement: www.ibioinformatics.org/careers.php</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10457/assistant-professor-bio-informatics-at-health-and-family-welfare-department-medical-education-in-raipur</guid>
  <pubDate>Wed, 07 May 2014 00:08:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor (Bio-Informatics) at Health and Family Welfare Department (Medical Education) in Raipur]]></title>
  <description><![CDATA[
<p>Advertisement No.05/2014/ Exam/Dated 17/04/2014</p>

<p>No of vacancies: 01</p>

<p>Pay scale:Rs. 15600 – 39100 + 6600/-</p>

<p>Essential Academic Qualifications / Experience : Good academic record as defined by the concerned university with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master's Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university.</p>

<p>Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/ SET.</p>

<p>Notwithstanding anything contained in sub-clauses (a) and (b) to this Clause, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.</p>

<p>NET/SLET/SET shall also not be required for such Masters Programmes in disciplines for which NET/SLET/SET is not conducted.</p>

<p>Apply online: http://www.psc.cg.gov.in/htm/OA_ME2014.html</p>

<p>Last Date for Online Registration: 22/05/2014</p>

<p>For more details: http://www.psc.cg.gov.in/pdf/Advertisement/ADV_ME2014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/16686/sequence-viewer-download-transcripts-exons-and-proteins</guid>
	<pubDate>Mon, 15 Sep 2014 17:30:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/16686/sequence-viewer-download-transcripts-exons-and-proteins</link>
	<title><![CDATA[Sequence Viewer: Download Transcripts, Exons and Proteins]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/ZWnLyYKozaI" frameborder="0" allowfullscreen></iframe>How to download FASTA sequence for certain gene features while in the NCBI's Sequence Viewer.

Sequence Viewer homepage:
www.ncbi.nlm.nih.gov/projects/sviewer/

Sequence Viewer playlist:
https://www.youtube.com/playlist?list=PL76D7EE6A6A8AC1C3]]></description>
	
</item>

</channel>
</rss>