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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28915?offset=1430</link>
	<atom:link href="https://bioinformaticsonline.com/related/28915?offset=1430" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7218/associate-professor-centre-for-bioinformatics-at-maharshi-dayanand-university-rohtak</guid>
  <pubDate>Thu, 12 Dec 2013 20:49:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Associate Professor - Centre for Bioinformatics at Maharshi Dayanand University, Rohtak]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT No. PR-54/2013</p>

<p>No. of Posts and Specialization: 1(UR)</p>

<p>Educational Qualification:</p>

<p>(i) Good academic record with a Ph.D. Degree in the concerned /allied /relevant disciplines.</p>

<p>(ii) The Ph.D. Degree shall be a mandatory qualification for all candidates to be appointed as Associate Professor through direct recruitment.</p>

<p>(iii) A Master‟s Degree with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed).</p>

<p>(iv) A minimum of eight years of experience of teaching and /or research in an academic /research position equivalent to that of Assistant Professor in a University, College or Accredited Research Institution/Industry excluding the period of Ph.D research with evidence of published work and a minimum of 5 publications as books and /or research papers in refereed journals only/policy papers.</p>

<p>(v) Contribution to educations innovation, design of new curricula and courses and technology-mediated teaching learning process with evidence of having guided doctoral candidates and research students.</p>

<p>(vi) A minimum score as stipulated in the Academic Performance Indicator (API) based performance Based Appraisal System (PBAS), set out in this notification in as mentioned in the advertisement.</p>

<p>Send your application to the A.R (Estt.Teaching), M.D.University, Rohtak on or before December 23, 2013.</p>

<p>For more details: http://www.mdurohtak.ac.in/pdf/Notices_Pdf/new_notice/Teaching%20Vacancy%20%28ADVT.%20No.%20PR-54%20of%202013%29.pdf</p>

<p>Last Apply Date: 23 Dec 2013</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5888/nit-calicut-faculty-jobs-2013-in-bioinformatics</guid>
  <pubDate>Thu, 24 Oct 2013 13:00:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[NIT Calicut Faculty Jobs 2013 in Bioinformatics]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY CALICUT, KERALA</p>

<p>NOTIFICATION FOR FACULTY RECRUITMENT – 2013</p>

<p>(Faculty openings in Technology, Science, Architecture and Management at NIT Calicut, Kerala)</p>

<p>National Institute of Technology Calicut, Kerala, established under Act XXIX/ 2007of the Parliament is one of the leading technological institutions in the Country with nearly 6000 students enrolled for various UG, PG and Ph.D. programmes in Technology, Science, Architecture and Management. The Institute invites applications from Indian nationals, possessing consistent excellent academic record, commitment to quality teaching and potential for carrying out outstanding research, for the post of Assistant Professors in various departments against the backlog reserved vacancies for Scheduled Caste (SC), Scheduled Tribe (ST), Other Backward Communities (OBC) and Persons with Disabilities (PWDs) and also under open merit quota as detailed below. Candidates belonging to SC, ST and OBC desirous of considering for selection under UR category also shall specifically indicate so in column 4.</p>

<p>Reservation quota for PWDs will be counted against the respective community. Young, meritorious, dynamic and student friendly academicians are welcome to join hands with the existing team in their effort to transform this Institute to a world class educational institution.</p>

<p>Candidates possessing Ph.D. degree will be considered for appointment on contract basis initially.</p>

<p>They will be considered for movement to AGP `7000 after one year of satisfactory performance.</p>

<p>Meritorious candidates possessing M.Tech./M.Phil. (*) with remarkably good potential to carry out outstanding research and already pursuing Ph.D. or aspiring to pursue Ph.D. will also be considered for appointment on contract, initially for a period of 3 years, extendable for a further period of 2 years on a year to year basis or till the candidate acquires Ph.D. degree whichever is earlier. Renewal of contract<br />will be done on an annual basis, subject to satisfactory progress of Ph.D. work, good conduct and good performance in teaching. Faculty appointed on contract basis will not be treated as regular staff till they are regularized, subject to the conditions stated earlier. The Institute has adopted 4-tier flexible faculty structure recommended by MHRD. </p>

<p>More Info : http://www.nitc.ac.in/index.php/?url=content/submenu/2345/5</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43804/agora-algorithm-for-gene-order-reconstruction-in-ancestors</guid>
	<pubDate>Mon, 28 Feb 2022 23:26:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43804/agora-algorithm-for-gene-order-reconstruction-in-ancestors</link>
	<title><![CDATA[AGORA: Algorithm for Gene Order Reconstruction in Ancestors]]></title>
	<description><![CDATA[<p dir="auto">AGORA stands for &ldquo;Algorithm for Gene Order Reconstruction in Ancestors&rdquo; and was developed by Matthieu Muffato in the DYOGEN Laboratory at the &Eacute;cole normale sup&eacute;rieure in Paris in 2008.</p>
<div>
<pre><code>    // | |     //   ) )  //   ) ) //   ) )  // | |
   //__| |    //        //   / / //___/ /  //__| |
  / ___  |   //  ____  //   / / / ___ (   / ___  |
 //    | |  //    / / //   / / //   | |  //    | |
//     | | ((____/ / ((___/ / //    | | //     | |
</code></pre>
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<p dir="auto">AGORA is used to generate ancestral genomes for the&nbsp;<a href="https://www.genomicus.biologie.ens.fr/genomicus">Genomicus</a>&nbsp;online server for gene order comparison, and has been in constant use in the group since.</p><p>Address of the bookmark: <a href="https://github.com/DyogenIBENS/Agora" rel="nofollow">https://github.com/DyogenIBENS/Agora</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5958/srfjrf-national-institute-of-immunology</guid>
  <pubDate>Wed, 30 Oct 2013 06:45:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF/JRF @ National Institute of Immunology]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT OF WALK-IN-INTERVIEW</p>

<p>NAME OF THE POST : SRF/JRF (Four Posts only)</p>

<p>DURATION : Indicated with the respective project mentioned below:</p>

<p>NAME OF THE PROJECT : As Mentioned below:</p>

<p>1. Serological diversity and molecular characterization of Dichelobector nodusus and development of vaccine against virulent footroot funded by NAIP. (Tenable upto 31.03.2014)</p>

<p>2. Development of oral vaccine against Clostridium perfringenes employing translational fusion of immunodominant epitopes of beta toxin with heat labile entertoxin B funded by DBT. (Tenable upto 25.02.2014)</p>

<p>3. Indo-Norwegian project, “Evaluation of major porins, ompC and ompR of Areomonas hydrophila as potential vaccine candidates and identification and characterization of immune genes of Indian major carp, Labeo rohita” (Tenable upto 31.03.2014)</p>

<p>EDUCATIONAL QUALIFICATIONS: For JRF- M.Sc/M.Tech in any subject of Biological  Sciences/Life Sciences</p>

<p>For SRF- M.Sc/M.Tech in any subject of Biological Sciences/Life Sciences with 2 years of Research Experience.</p>

<p>JOB DESCRIPTION : The Candidate should have experience in gene Expression, protein purification, molecular biology techniques and bioinformatics<br />EMOLUMENTS : SRF: Rs. 18,000/- per month consolidated plus 30% HRA if /NET/GATE qualified otherwise Rs. 14,000/- per month consolidated + 30% HRA.</p>

<p>JRF: Rs. 16,000/- per month consolidated + 30% HRA if NET/GATE qualified otherwise Rs. 12,000/- per month consolidated + 30% HRA</p>

<p>SCIENTIST NAME : Dr. Lalit C. Garg, SS-VII (Gene Regulation Lab)</p>

<p>SCIENTIST’S EMAIL : lalit@nii.ac.in</p>

<p>WALK IN INTERVIEW ON : October 31st, 2013</p>

<p>REGISTRATION OF CANDIDATES: 10.30 AM to 11.00 AM </p>

<p>Advertisement: http://www1.nii.res.in/sites/default/files/project-Dr.Lalit-31oct2013.pdf</p>
]]></description>
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	<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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6104/incob-2014</guid>
  <pubDate>Thu, 07 Nov 2013 17:53:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[InCoB 2014]]></title>
  <description><![CDATA[
<p>The 13th International Conference on Bioinformatics (InCoB 2014) will be held in Novotel Sydney Brighton Beach, Sydney, New South Wales, Australia. This year, the InCoB will be held earlier from 31st July to 2nd August 2014 to run back-to-back with the International Biophysics Congress 2014 at the Brisbane Convention and Exhibition Centre, Queensland (3-7 Aug).</p>

<p>More at http://incob2014.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36849/glean-an-unsupervised-learning-system-to-integrate-disparate-sources-of-gene-structure-evidence</guid>
	<pubDate>Sat, 02 Jun 2018 07:38:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36849/glean-an-unsupervised-learning-system-to-integrate-disparate-sources-of-gene-structure-evidence</link>
	<title><![CDATA[GLEAN: an unsupervised learning system to integrate disparate sources of gene structure evidence]]></title>
	<description><![CDATA[<p><span>GLEAN is an unsupervised learning system to integrate disparate sources of gene structure evidence (gene model predictions, EST/protein genomic sequence alignments, SAGE/peptide tags, etc) to produce a consensus gene prediction, without prior training.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/glean-gene/" rel="nofollow">https://sourceforge.net/projects/glean-gene/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/6300/list-of-bioinformatics-vacancy-jobs-opportunity-websites</guid>
	<pubDate>Tue, 12 Nov 2013 20:04:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/6300/list-of-bioinformatics-vacancy-jobs-opportunity-websites</link>
	<title><![CDATA[List of Bioinformatics Vacancy, Jobs, Opportunity websites]]></title>
	<description><![CDATA[<p>Bioinformatics cover wide area of biology, and indulge in almost all sort of science related work. Bioinformatician give strong emphasis on open access to biological information as well as Free and Open Source software!!</p>
<p>There are several jobs opening in bioinformatics all around the world, but many of them do not get proper attention due to lack of advertisements, or social connectivity. This bookmark is created for an academic, non-academic, scientists and budding researchers to help and updates the bioinformatics/computational biology jobs links of all know websites around the world.</p>
<p><strong>I also love to stream the live <strong>bioinformatics or Computational biology jobs</strong> updates using Twitter https://twitter.com/search?q=bioinformatics%20jobs&amp;src=typd</strong></p>
<p>Find out here about exciting job opportunities in the life sciences.</p>
<blockquote>
<p>Please add well known bioinformatics jobs websites below in comment section.</p>
</blockquote><p>Address of the bookmark: <a href="http://www.nature.com/naturejobs/science/jobs?utf8=%E2%9C%93&amp;q=bioinformatics&amp;where=&amp;commit=Find+Jobs" rel="nofollow">http://www.nature.com/naturejobs/science/jobs?utf8=%E2%9C%93&amp;q=bioinformatics&amp;where=&amp;commit=Find+Jobs</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38692/geneck-gene-network-construction-kit-is-a-comprehensive-online-tool-kit-that-integrate-various-statistical-methods-to-construct-gene-networks</guid>
	<pubDate>Tue, 15 Jan 2019 09:39:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38692/geneck-gene-network-construction-kit-is-a-comprehensive-online-tool-kit-that-integrate-various-statistical-methods-to-construct-gene-networks</link>
	<title><![CDATA[GeNeCK (Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks]]></title>
	<description><![CDATA[<p><strong>GeNeCK</strong><span>&nbsp;(Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks based on gene expression data and optional hub gene information.</span></p>
<p><span><span>It efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.</span></span></p>
<p><span><span><span>GeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at&nbsp;</span><span><a href="http://lce.biohpc.swmed.edu/geneck" target="_blank"><span>http://lce.biohpc.swmed.edu/geneck</span></a></span></span></span></p><p>Address of the bookmark: <a href="http://lce.biohpc.swmed.edu/geneck/" rel="nofollow">http://lce.biohpc.swmed.edu/geneck/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6561/mathomics-lab</guid>
  <pubDate>Tue, 19 Nov 2013 18:17:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[MATHomics Lab]]></title>
  <description><![CDATA[
<p>Mathomics is a collaborative research group of the Center for Mathematical Modeling and the Center for Genome Regulation at University of Chile, created to play a central role in the development of biotechnological projects, providing state of the art bioinformatics and mathematical modeling tools,  allowing to face these problems from the point of view of Systems Biology. </p>

<p>Lab page @ http://www.mathomics.cl/</p>
]]></description>
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