<?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/44934?offset=10</link>
	<atom:link href="https://bioinformaticsonline.com/related/44934?offset=10" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</guid>
	<pubDate>Sun, 06 Aug 2017 06:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</link>
	<title><![CDATA[Sequence - Evolution - Function; Computational Approaches in Comparative Genomics]]></title>
	<description><![CDATA[<p><em>Sequence - Evolution - Function</em><span>&nbsp;is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK20260/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK20260/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40945/the-clark-lab</guid>
  <pubDate>Fri, 07 Feb 2020 13:57:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Clark Lab]]></title>
  <description><![CDATA[
<p>Study the process of Adaptive Evolution, during which species adopt novel traits to overcome challenges. We retrace the evolutionary histories of genomic elements to determine the changes underlying adaptation and to discover previously unknown genetic networks. These discoveries have already led to advances in human health, species conservation, and molecular biology. </p>

<p>More at http://clark.genetics.utah.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44226/rotifers-lab</guid>
  <pubDate>Wed, 08 Mar 2023 23:23:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Rotifers Lab]]></title>
  <description><![CDATA[
<p>For scientists in the MBL’s Gribble Lab, the rotifer (Brachionus manjavacas) is used as a model organism to study evolution, stress responses, the biology of aging, and maternal effects. Rotifers are small, easy to grow in the lab, have a short lifespan, and share many of their genes with humans. That makes them ideal specimens in which to address questions relevant to human health as well as understand basic biological and evolutionary processes. Brachionus rotifers produces eggs that can be completely dried and frozen for decades, then hatch within a day when exposed to water and light.</p>

<p>https://www.mbl.edu/research/research-organisms/rotifer<br />https://gribblebiolab.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44679/rennison-lab</guid>
  <pubDate>Sat, 26 Oct 2024 15:10:32 -0500</pubDate>
  <link></link>
  <title><![CDATA[Rennison Lab !]]></title>
  <description><![CDATA[
<p>Welcome to the Rennison lab in the School of Biological Sciences at the University of California San Diego. We are a group interested in the evolution and maintenance of biodiversity. We study the processes related to biodiversity using methods from the fields of evolution, ecology, population genomics, and theory. </p>

<p>More at https://rennisonlab.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/33306/ancestral-sequence-reconstruction-asr-or-ancestral-genesequence-reconstructionresurrection-tools-to-study-molecular-evolution</guid>
	<pubDate>Tue, 30 May 2017 04:20:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/33306/ancestral-sequence-reconstruction-asr-or-ancestral-genesequence-reconstructionresurrection-tools-to-study-molecular-evolution</link>
	<title><![CDATA[Ancestral sequence reconstruction (ASR) or ancestral gene/sequence reconstruction/resurrection tools to study molecular evolution]]></title>
	<description><![CDATA[<p><span><strong>Ancestral sequence reconstruction</strong><span>&nbsp;(</span><strong>ASR</strong><span>) &ndash; also known as&nbsp;</span><strong>ancestral gene</strong><span>/</span><strong>sequence reconstruction</strong><span>/</span><strong>resurrection</strong><span>&nbsp;&ndash; is a technique used in the study of&nbsp;</span>molecular evolution<span>. The method consists of the synthesis of an ancestral&nbsp;</span>gene<span>&nbsp;and expression of the corresponding ancestral&nbsp;</span>protein<span>.&nbsp;</span><sup id="cite_ref-thornton_1-0"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-thornton-1"></a></sup><span>The idea of protein 'resurrection' was suggested in 1963 by Pauling and Zuckerkandl.</span><sup id="cite_ref-2"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-2"></a></sup><span>&nbsp;Some early efforts were made in the eighties-nineties, led by the laboratory of&nbsp;</span>Steven A. Benner<span>, showing the potential of this technique &ndash; one that only started to be fulfilled in the post-genomic era.</span><sup id="cite_ref-3"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-3"></a></sup><span>&nbsp;Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes.</span><sup id="cite_ref-4"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-4"></a></sup><span>&nbsp;Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.&nbsp;</span></span></p><p><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e4/ASR_phylogeny.png/510px-ASR_phylogeny.png" alt="image" width="610" height="435" style="border: 0px; border: 0px;"></p><p><span>Following are the list of&nbsp;</span><strong style="font-size: 12.8px;">Ancestral /sequence/ reconstruction</strong><span>&nbsp;(</span><strong style="font-size: 12.8px;">ASR</strong><span>) tools:&nbsp;</span></p><p><a href="http://www.bx.psu.edu/miller_lab/car/" target="_blank" title="To inferCars official website"><span>inferCars</span></a></p><p><span><span><span><span><span>Reconstructs contiguous regions of an ancestral genome. Given information about adjacencies between conserved segments in each modern species, our goal is to infer segment order in the ancestral genome. To get a clean and precise statement of the problem, we formalize it using graph theory. We develop an algorithm that identifies a most parsimonious scenario for the history of each individual adjacency, although the whole-genome prediction is not guaranteed to optimize traditional measures like the number of breakpoints. We introduce weights to the graph edges to model the reliability of each adjacency.</span></span></span></span></span></p><p><span><span><a href="http://paleogenomics.irmacs.sfu.ca/ANGES/" target="_blank" title="To ANGES official website">ANGES</a>:</span><a href="http://paleogenomics.irmacs.sfu.ca/ANGES/" target="_blank" title="To ANGES official website">reconstructing ANcestral GEnomeS maps</a></span></p><p><span><span><span><span><span><span>A suite of Python programs that allows reconstructing ancestral genome maps from the comparison of the organization of extant-related genomes. ANGES can reconstruct ancestral genome maps for multichromosomal linear genomes and unichromosomal circular genomes. It implements methods inspired from techniques developed to compute physical maps of extant genomes.</span></span></span></span></span></span></p><p><a href="http://virulence.molgen.mpg.de/cocos/" target="_blank" title="To Cocos official website"><span>Cocos</span></a></p><p><span><span><span><span><span><span><span>Constructs phylogenies of multi-domain proteins. With a given species tree and domain phylogenies, the procedure infers the composition of ancestral multi-domain proteins. Cocos implements and extend a suggested algorithmic approach by Behzadi and Vingron in an easy-to-use program. Such method could be applied to reconstruction of partial homologous units such as bacterial operons or protein complexes.</span></span></span></span></span></span></span></p><p><a href="https://github.com/msrosenberg/MySSP" target="_blank" title="To MySSP official website"><span>MySSP</span></a></p><p><span><span><span><span><span><span><span><span>Constructs an initial DNA sequence at the root of the tree and simulates evolution across the tree using a variety of common models of DNA evolution. MySSP is a program for the simulation of DNA sequence evolution across a phylogenetic tree. It is designed for large-scale studies, including simulation of multiple replicates and outputs sequences into NEXUS, MEGA, or FASTA formats. MySSP has a fairly simple graphical user interface (GUI) for basic use, but also has a specialized batch script interpreter to allow for more complicated or large-scale simulations.</span></span></span></span></span></span></span></span></p><p><span><span><a href="http://www.cs.cmu.edu/~ckingsf/software/parana/" target="_blank" title="To PARANA official website">PARANA</a>:&nbsp;</span><a href="http://www.cs.cmu.edu/~ckingsf/software/parana/" target="_blank" title="To PARANA official website">Parsimonious Ancestral Reconstruction And Network Analysis</a></span></p><p><span><span><span><span><span><span><span><span><span>Performs parsimony based inference of ancestral biological networks. Given multiple extant networks and phylogenetic information relating extant nodes, PARANA finds a parsimonious set of ancestral interaction events (edge gains and losses) which explain the extant networks. The framework adopted by PARANA is able to represent network evolution under models that support gene duplication and loss and independent interaction gain and loss. The method works on both directed and undirected networks and can incorporate asymmetric interaction gain and loss costs. In contrast to previous approaches, PARANA does not require knowing the relative ordering of unrelated duplication events and thus, works on phylogenetic trees even where branch lengths are not provided.</span></span></span></span></span></span></span></span></span></p><p><span><span><a href="http://www-labs.iro.umontreal.ca/~mabrouk/" target="_blank" title="To GapAdj official website">GapAdj</a>:&nbsp;</span><a href="http://www-labs.iro.umontreal.ca/~mabrouk/" target="_blank" title="To GapAdj official website">Gapped Adjacencies</a></span></p><p><span><span><span><span><span><span><span><span><span><span>A synteny-based method that is flexible enough to handle a model of evolution involving whole genome duplication events, in addition to rearrangements, gene insertions, and losses. Ancestral relationships between markers are defined in term of Gapped Adjacencies, i.e. pairs of markers separated by up to a given number of markers. It improves on a previous restricted to direct adjacencies, which revealed a high accuracy for adjacency prediction, but with the drawback of being overly conservative, i.e. of generating a large number of contiguous ancestral regions (CARs).</span></span></span></span></span></span></span></span></span></span></p><p><a href="http://ancestors.bioinfo.uqam.ca/"><span><span><span><span><span><span><span><span><span><span>ANCESTOR</span></span></span></span></span></span></span></span></span></span></a></p><p><span><span><span><span><span><span><span><span><span><span><span>A web server allowing one to easily and quickly perform the last three steps of the ancestral genome reconstruction procedure. Ancestors implements several alignment algorithms, an indel maximum likelihood solver and a context-dependent maximum likelihood substitution inference algorithm. The results presented by the server include the posterior probabilities for the last two steps of the ancestral genome reconstruction and the expected error rate of each ancestral base prediction.</span></span></span></span></span></span></span></span></span></span></span></p><p><a href="http://bioinfo.lifl.fr/procars/" target="_blank" title="To ProCARs official website"><span>ProCARs</span></a></p><p>Reconstructs ancestral gene orders as contiguous ancestral regions (CARs) with a progressive homology-based method. ProCARs runs from a phylogeny tree (without branch lengths needed) with a marked ancestor and a block file. This homology-based method is based on iteratively detecting and assembling ancestral adjacencies, while allowing some micro-rearrangements of synteny blocks at the extremities of the progressively assembled CARs. The method starts with a set of blocks as the initial set of CARs, and detects iteratively the potential ancestral adjacencies between extremities of CARs, while building up the CARs progressively by adding, at each step, new non-conflicting adjacencies that induce the less homoplasy phenomenon. The species tree is used, in some additional internal steps, to compute a score for the remaining conflicting adjacencies, and to detect other reliable adjacencies, in order to reach completely assembled ancestral genomes.</p><p><a href="http://fastml.tau.ac.il/" target="_blank" title="To FastML official website"><span>FastML</span></a></p><p>A user-friendly tool for the reconstruction of ancestral sequences. FastML implements various novel features that differentiate it from existing tools: (i) FastML uses an indel-coding method, in which each gap, possibly spanning multiples sites, is coded as binary data. FastML then reconstructs ancestral indel states assuming a continuous time Markov process. FastML provides the most likely ancestral sequences, integrating both indels and characters; (ii) FastML accounts for uncertainty in ancestral states: it provides not only the posterior probabilities for each character and indel at each sequence position, but also a sample of ancestral sequences from this posterior distribution, and a list of the k-most likely ancestral sequences; (iii) FastML implements a large array of evolutionary models, which makes it generic and applicable for nucleotide, protein and codon sequences; and (iv) a graphical representation of the results is provided, including, for example, a graphical logo of the inferred ancestral sequences.</p><p><a href="http://rth.dk/resources/maxAlike/" target="_blank" title="To maxAlike official website"><span>maxAlike</span></a></p><p>Reconstructs a genomic sequence for a specific taxon based on sequence homologs in other species. The input is a multiple sequence alignment and a phylogenetic tree that also contains the target species. For this target species, the algorithm computes nucleotide probabilities at each sequence position. Consensus sequences are then reconstructed based on a certain confidence level.</p><p><span><span><a href="http://www.geneorder.org/server.php" target="_blank" title="To MLGO official website">MLGO</a>:&nbsp;</span><a href="http://www.geneorder.org/server.php" target="_blank" title="To MLGO official website">Maximum Likelihood for Gene Order Analysis</a></span></p><p>A web tool for the reconstruction of phylogeny and/or ancestral genomes from gene-order data. MLGO was designed for analysis of large-scale genomic changes including not only rearrangements but also gene insertions, deletions and duplications. MLGO can be used to infer a phylogeny from genome rearrangement and gene order data, and can also obtain an estimation of ancestral genomes, given an input tree. MLGO takes the advantage of binary encoding on gene-order data, supports a fairly general model of genomic evolution (rearrangements plus duplications, insertions, and losses of genomic regions), and successfully accommodates itself into the framework of maximized likelihood.</p><p>Image Reference : Wiki</p>]]></description>
	<dc:creator>Jit</dc:creator>
</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/bookmarks/view/41493/coronavirus-resources</guid>
	<pubDate>Wed, 25 Mar 2020 17:11:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</link>
	<title><![CDATA[Coronavirus Resources !]]></title>
	<description><![CDATA[<p><span>2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.</span></p>
<p><span>Annotation</span></p>
<p><span><a href="https://bigd.big.ac.cn/ncov/variation/annotation">https://bigd.big.ac.cn/ncov/variation/annotation</a></span></p>
<p><span>Genome wharehouse&nbsp;</span></p>
<p><span><a href="https://bigd.big.ac.cn/gwh/browse/index">https://bigd.big.ac.cn/gwh/browse/index</a></span></p>
<p>Released Genome</p>
<p><a href="https://bigd.big.ac.cn/ncov/release_genome">https://bigd.big.ac.cn/ncov/release_genome</a></p>
<p>Download data&nbsp;</p>
<p><a href="ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/">ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/</a></p>
<p>Raw data</p>
<p><a href="https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae">https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae</a></p><p>Address of the bookmark: <a href="https://bigd.big.ac.cn/ncov/about" rel="nofollow">https://bigd.big.ac.cn/ncov/about</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</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/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</guid>
	<pubDate>Mon, 06 May 2024 06:21:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</link>
	<title><![CDATA[Synorth: exploring the evolution of synteny and long-range regulatory interactions in vertebrate genomes]]></title>
	<description><![CDATA[<p><span>Genomic regulatory blocks are chromosomal regions spanned by long clusters of highly conserved noncoding elements devoted to long-range regulation of developmental genes, often immobilizing other, unrelated genes into long-lasting syntenic arrangements. Synorth&nbsp;</span><a href="http://synorth.genereg.net/" target="_blank">http://synorth.genereg.net/</a><span>&nbsp;is a web resource for exploring and categorizing the syntenic relationships in genomic regulatory blocks across multiple genomes, tracing their evolutionary fate after teleost whole genome duplication at the level of genomic regulatory block loci, individual genes, and their phylogenetic context.</span></p>
<p><span>More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745767/</span></p><p>Address of the bookmark: <a href="http://synorth.genereg.net/" rel="nofollow">http://synorth.genereg.net/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9429/srf-vacancy-at-nipgr</guid>
  <pubDate>Tue, 25 Mar 2014 19:20:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Vacancy at NIPGR]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for filling up the purely temporary position of one Senior Research Fellow in DST’s Indo-Australian Joint project (with ICRISAT) entitled “Genomic Approach for Stress Tolerant Chickpea” under the guidance of Dr. Mukesh Jain, Scientist, NIPGR.</p>

<p>(A) Senior Research Fellow (One Post):    Emoluments as per DST/DBT norms.</p>

<p>Candidates having M.Sc. degree (with minimum of 55% marks) or equivalent in Life Sciences/Biotechnology/Bioinformatics/ Molecular Biology or any other related field with minimum of two years of post M.Sc. research experience are eligible to apply. The candidate having computer skill (Linux, Perl, Java, MySQL) and/or experience in advanced molecular biology, next generation sequencing data analysis and molecular markers analysis will be preferred.</p>

<p>The position is completely on temporary basis and co-terminus with the project. The initial appointment will be for one year, which can be curtailed/extended on the basis of assessment of the candidate’s performance and discretion of the Competent Authority. NIPGR reserves the right to select the candidate against the above posts depending upon the qualifications and experience of the candidates. Reservation of posts shall be as per Govt. of India norms.</p>

<p>Eligible candidates may apply by sending hard copy of completed application in the given format with a cover letter showing interest and attested copies of the certificates and proof of research experience. The applications should reach at the address given below within 15 days from the date of the advertisement. The subject line on envelope must be superscribed by “Application for the Post of SRF in DST - AISRF project”.</p>

<p>Note: ONLY hard copy of the application in the given format will be accepted.</p>

<p>Last date April 03, 2014</p>

<p>Dr. Mukesh Jain<br />Staff Scientist<br />National Institute of Plant Genome Research<br />Aruna Asaf Ali Marg, P.O. Box NO. 10531,<br />New Delhi - 110067</p>

<p>Advertisement: http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>

</channel>
</rss>