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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34916?offset=920</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7153/phd-student-in-computational-systems-biology</guid>
  <pubDate>Tue, 10 Dec 2013 18:46:05 -0600</pubDate>
  <link></link>
  <title><![CDATA[Ph.D. student in Computational Systems Biology]]></title>
  <description><![CDATA[
<p>Ph.D. student in Computational Systems Biology</p>

<p>Location : The Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, Luxembourg, Luxembourg<br />Deadline for applications : unknown.<br />Description :</p>

<p>The Luxembourg Centre for Systems Biomedicine (LCSB) was created within the Health Technologies Initiative from the Government of Luxembourg as one of the research priorities of the University of Luxembourg. The LCSB is an Interdisciplinary Centre of the University that combines experimental and computational approaches to analyse complex biological systems and disease processes. The Computational Biology Group (CBG) provides the LCSB with a solid infrastructure in developing theoretical framework for computational modeling on biomedical problems, especially in the area of network biology in the context of cellular programming/reprogramming. The CBG group includes researchers with theoretical, computational and wet lab backgrounds, thereby providing an unusually interdisciplinary environment.<br />The Computational Biology Group seeks a highly-skilled Ph.D. student to work on an exciting project on reconstruction and analysis of an integrated gene regulatory network model to elucidate key mechanisms of cellular reprogramming. The model will rely on the integration and mining of diverse transcriptomics and epigenomics data of different cell types from the Central Nervous System. The Ph.D. student is expected to collaborate with other members of the CBG to develop a computational methodology aiming at designing, in-silico, cellular reprogramming events, with a focus on the nervous system. This project will be carried out in collaboration with Prof. Noel Buckleys lab at Kings College London.<br />Requirements of the ideal candidate:<br />Master degree in Bioinformatics, Computer Science, Biology or a related discipline<br />Prior experience in mathematical modelling of biological networks, especially in network inference and analysis<br />Excellent working knowledge in English.<br />.<br />We offer:<br />Full contract for Ph.D. student for three years with possibility of renewal<br />Opportunity to do applied research to medical problems within a highly dynamic research institution (LCSB) and in collaboration with internationally recognized partners<br />An exciting international environment<br />A very competitive salary</p>

<p>For further information, please contact:</p>

<p>Prof. Dr. Antonio del Sol<br />E-mail: antonio.delsol@uni.lu</p>

<p>Applications should contain the following documents:<br />A detailed curriculum vitae<br />cover letter mentioning the reference number<br />description of past research experience and future interests<br />name and addresses of three referees</p>

<p>All applications should be sent preferably in electronic version until December 31st, 2013 to the following address:</p>

<p>Luxembourg Centre for Systems Biomedicine (LCSB)<br />University of Luxembourg<br />7, avenue des Hauts-Fourneaux<br />L-4362 Esch-sur-Alzette<br />Tel: +352-466644-6982 (Office)<br />Email: antonio.delsol@uni.lu<br />http://www.lcsb.lu</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36392/protein-protein-interaction-sites-predictions</guid>
	<pubDate>Wed, 25 Apr 2018 04:53:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36392/protein-protein-interaction-sites-predictions</link>
	<title><![CDATA[Protein-Protein Interaction Sites Predictions !]]></title>
	<description><![CDATA[<p><span>The study of Protein&ndash;Protein Interactions (PPIs) has a crucial role in biology, medicine and the pharmaceutical industry. PPIs can be investigated from two aspects: The interaction partners of a specific protein and the amino acid residues participating in a given PPI. Information about a protein&rsquo;s interaction partners allows scientists to construct protein interaction networks, such as signaling pathways, which in turn facilitate the understanding of many biological and clinical observations.&nbsp;</span></p><p><span>Following are the list of tools commonly used to PPIs predictions:</span></p><p>Protein-Protein Interaction Sites</p><p><a href="http://pipe.scs.fsu.edu/ppisp.html" target="_blank">PPISP</a></p><p>A consensus neural network method for predicting protein-protein interaction sites</p><p><a href="http://biunit.naist.jp/homcos/" target="_blank">HOMCOS</a></p><p>A server to predict interacting protein pairs and interacting sites by homology modeling of complex structures</p><p><a href="http://prism.ccbb.ku.edu.tr/hotpoint/" target="_blank">HotPOINT</a></p><p>Prediction of protein interfaces using an empirical model</p><p><a href="http://cubic.bioc.columbia.edu/services/isis/" target="_blank">ISIS</a></p><p>Prediction of interaction hotspots from sequence</p><p><a href="http://kfc.mitchell-lab.org/" target="_blank">KFC server</a></p><p>Automated decision-tree approach to predicting protein-protein interaction hot spots</p><p><a href="http://pipe.scs.fsu.edu/meta-ppisp.html" target="_blank">meta-PPISP</a></p><p>A meta server for predicting protein-protein interaction sites. meta-PPISP is built on three individual web servers:&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/binding.htm#cons">cons-PPISP</a>,&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/binding.htm#pin">PINUP</a>, and&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/binding.htm#pro">Promate</a></p><p><a href="http://www.molsoft.com/oda.html" target="_blank">ODA</a></p><p>Identification of optimal surface patches with the lowest docking desolvation energy values</p><p><a href="http://sparks.informatics.iupui.edu/PINUP/" target="_blank">PINUP</a></p><p>Protein binding site prediction with an empirical scoring function</p><p>Other Sites (DNA, RNA, Metals)</p><p><a href="http://ligin.weizmann.ac.il/~lpgerzon/mbs4/mbs.cgi" target="_blank">CHED</a>&nbsp;</p><p>Web server for predicting soft metal binding sites in proteins</p><p><a href="http://cssb.biology.gatech.edu/skolnick/webservice/DBD-Hunter/" target="_blank">DBD-Hunter</a></p><p>A knowledge-based method for the prediction of DNA-protein interactions</p><p><a href="http://pipe.scs.fsu.edu/displar.html" target="_blank">DISPLAR</a></p><p>Given the structure of a protein known to bind DNA, the method predicts residues that contact DNA using neural network method</p><p><a href="http://idbps.tau.ac.il/" target="_blank">iDBPs</a></p><p>Predicts DNA binding proteins for proteins with known 3D structure.</p><p><a href="http://pfp.technion.ac.il/" target="_blank">PFplus</a></p><div style="text-align: left;">A tool for extracting and displaying positive electrostatic patches on protein surfaces which can be indicative of nucleic acid binding interfaces.</div>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6836/research-fellow-mendel-laboratory</guid>
  <pubDate>Tue, 26 Nov 2013 00:07:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Fellow @ Mendel laboratory]]></title>
  <description><![CDATA[
<p>IRCCS Casa Sollievo della Sofferenza – Mendel laboratory is seeking one talented bioinformatician (Rome)<br />Start date: immediate</p>

<p>Duration: 1 year</p>

<p>Funding Source: Institutional<br />Salary on grant: B2 (€ 22.000/year gross)<br />Contact Person (Referent): Tommaso Mazza<br />Ref. E-Mail: t.mazza@css-mendel.it<br />Tel: +39 06 44160526<br />Fax: +39 06 44160548</p>

<p>Job Description: The bioinformatics unit at IRCCS Casa Sollievo della Sofferenza - Mendel laboratory in Rome is looking for one young PhD bioinformatician with specific experience and/or interest in the analysis of transcriptomic data.</p>

<p>The candidate will be mainly in charge of developing research on a range of hot applications and projects, dealing with microarrays, RNA-Seq and miRNA-Seq data. Main activities will be: (i) data analysis (short-reads mapping, variants call and annotation, functional enrichment analysis of gene expression data); (ii) networks analysis and simulation (artificial knockout, redundancy and lethality analysis, gene set essentiality); (iii) developing of ad-hoc software solutions/routines on clusters of CPUs and GPUs.</p>

<p>The correct cultural background (training in Biology / Computer Science / Statistics or a mix of the three) and a strong interest in working with high throughput data analysis will be considered at the same level of specific experience in the above-mentioned fields.<br />Knowledge of molecular modeling and simulation and one of these languages: python, perl, R, Java, C++, C# is a golden plus. Good knowledge of Scientific English will be positively evaluated for this position, together with good presentation and teamwork skills.</p>

<p>A CV with one professional reference, details on educational background and of the biological and/or bioinformatic and/or data analysis skills and experience should be sent by email for a preliminary selection to: Tommaso Mazza, CSS-Mendel: t.mazza@css-mendel.it</p>

<p>Context<br />Casa Sollievo della Sofferenza is an Institute for hospitalization, care, and scientific research located in San Giovanni Rotondo, Italy. It integrates clinical assistance (with inpatient and outpatient facilities) and research. It has an affiliate institute, CSS-Mendel, located in Rome. Between the two sites, it employs over 100 researchers who focus on genetics. The Center is equipped with state of the art genomics technology (SOLiD 5500XL next generation sequencer, Illumina MiSeq, Affymetrix/Agilent microarray platforms, etc) as well as a dedicated high performance computing facility, a non-conventional workstation of GPUs and a short- and long-term storage disk.</p>

<p>Applications<br />Candidates should send:<br />• a cover letter explaining the role they would like to undertake within the Center, even if it is not listed in this job adv, stating clearly why they would be a good fit to the proposed role, and what they would bring to the Center in terms of expertise, ideas, talent;<br />• a CV including a list of publications;<br />• List of referees;</p>

<p>More at http://www.css-mendel.it/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36508/mitobim-mitochondrial-baiting-and-iterative-mapping</guid>
	<pubDate>Tue, 08 May 2018 04:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36508/mitobim-mitochondrial-baiting-and-iterative-mapping</link>
	<title><![CDATA[MITObim - mitochondrial baiting and iterative mapping]]></title>
	<description><![CDATA[<p>This document contains instructions on how to use the MITObim pipeline described in Hahn et al. 2013. The full article can be found&nbsp;<a href="http://nar.oxfordjournals.org/content/41/13/e129" title="MITObim full article at NAR">here</a>. Kindly cite the article if you are using MITObim in your work. The pipeline was originally developed for&nbsp;<span>Illumina</span>&nbsp;data, but thanks to the versatility of the MIRA assembler, MITObim supports in principle also data from the&nbsp;<span>Iontorrent</span>,&nbsp;<span>454</span>&nbsp;and&nbsp;<span>PacBio</span>&nbsp;sequencing platforms.</p>
<p>Below you can find a few basic tutorials for how to run MITObim and I encorage you to give them a try with the testdata that comes with this Repo, just to make sure everything is running smoothly on your system. It'll only take a few minutes and will potentially safe you a lot of time down the line.</p>
<p>I provide further examples&nbsp;<a href="https://github.com/chrishah/MITObim/tree/master/examples">here</a>&nbsp;as Jupyter notebooks. Get in touch if you feel like sharing your particular MITObim solution and I'd be happy to put it up here, too!</p><p>Address of the bookmark: <a href="https://github.com/chrishah/MITObim" rel="nofollow">https://github.com/chrishah/MITObim</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7212/bioinformatics-group-at-boku-university</guid>
  <pubDate>Thu, 12 Dec 2013 17:53:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics group at Boku University]]></title>
  <description><![CDATA[
<p>The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine</p>

<p>1. Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and<br />2. Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)</p>

<p>Lab page @ http://bioinf.boku.ac.at/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 11 May 2018 05:07:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads]]></title>
	<description><![CDATA[<p>MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>. MECAT performance were compared with&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>,&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>&nbsp;and&nbsp;<a href="http://canu.readthedocs.io/en/latest/">Canu(v1.3)</a>&nbsp;in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>&nbsp;and&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>.&nbsp;</p>
<p>https://www.nature.com/articles/nmeth.4432</p><p>Address of the bookmark: <a href="https://github.com/xiaochuanle/MECAT" rel="nofollow">https://github.com/xiaochuanle/MECAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/7216/free-math-books</guid>
	<pubDate>Thu, 12 Dec 2013 19:38:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/7216/free-math-books</link>
	<title><![CDATA[Free math books]]></title>
	<description><![CDATA[<p>Bioinformatics require some match skills, therefore I decided to provide this wonderful math eBooks links to the BOL community.</p>
<p>Please add ur links/bookmarks in comment section.</p><p>Address of the bookmark: <a href="http://physicsdatabase.com/free-math-books/" rel="nofollow">http://physicsdatabase.com/free-math-books/</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44213/bioinformatics-tools-to-explore-ssrs-in-genomes</guid>
	<pubDate>Tue, 07 Mar 2023 13:06:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44213/bioinformatics-tools-to-explore-ssrs-in-genomes</link>
	<title><![CDATA[Bioinformatics tools to explore SSRs in genomes !]]></title>
	<description><![CDATA[<p>There are several bioinformatics tools that can be used to explore Simple Sequence Repeats (SSRs), which are also known as microsatellites. Here are a few examples:</p><ol>
<li>
<p>MISA: MISA (MIcroSAtellite) is a web-based tool that can identify SSRs in DNA sequences. It can be used to analyze nucleotide sequences from various organisms and can identify perfect, compound, and imperfect SSRs.</p>
</li>
<li>
<p>SSR Locator: SSR Locator is a web-based tool that identifies SSRs in both DNA and RNA sequences. It can identify perfect, compound, and imperfect SSRs, and can also filter out low complexity regions.</p>
</li>
<li>
<p>SciRoKo: SciRoKo is a software tool that can identify SSRs in DNA sequences. It can be used to analyze genomic and transcriptomic sequences from various organisms and can identify perfect, compound, and imperfect SSRs.</p>
</li>
<li>
<p>Primer3: Primer3 is a web-based tool that designs PCR primers for SSRs. It can design primers for perfect and imperfect SSRs, and can be used to design primers for SSRs in various organisms.</p>
</li>
<li>
<p>QDD: QDD (Quick Detection of Duplication) is a software tool that can identify SSRs in DNA sequences and can also identify duplicate loci. It can be used to analyze genomic and transcriptomic sequences from various organisms.</p>
</li>
</ol><p>These are just a few examples of the many bioinformatics tools available for exploring SSRs. Depending on your specific needs and research questions, you may find that other tools are more appropriate for your analysis.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7753/jrf-pondicherry-university</guid>
  <pubDate>Fri, 03 Jan 2014 16:48:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF @ PONDICHERRY UNIVERSITY]]></title>
  <description><![CDATA[
<p>PONDICHERRY UNIVERSITY</p>

<p>CENTRE FOR BIOINFORMATICS</p>

<p>PUDUCHERRY</p>

<p>Applications are invited for one Project Assistant to work in the UGC sponsored Research Award "Molecular Docking and Dynamics studies to understand the interacting mechanism of oncogenic 101 protein with its cellular proteins".</p>

<p>The duration for the fellowship is 12months only with consolidated pay ofRs. 5,000 per month.</p>

<p>Application on plain paper with following details: Name, Address, Data of Birth, Father's Name, Nationality, Educational Qualification (SSLC onwards-enclose attested copies of certificate) and Researcb Experience may be addressed to Dr. R. Krishna, Principle Investigator (PI), UGC Research Award, Centre for Bioinformatics, Pondicherry University, Pondicherry - 605 014.</p>

<p>Application should reach in January 261h , 2013.</p>

<p>Essential Qualification: M.Sc. in Bioinformatics/Biophysics with good academic record.</p>

<p>Qualification for Project Fellow:</p>

<p>M.Sc in Bioinformatics/Biophysics.</p>

<p>The person to be considered for appointment as Project Fellow must have second class master degree with a minimum of 55% marks in the subject concerned or a related subject.</p>

<p>The candidate to be appointed as Project Fellows should be below thc age of40 years at the time of appointment.</p>

<p>Desirable Qualification for this Project: Research Experience in Small/Macromolecule Crystallography and Structural Bioinformatics.</p>

<p>For more details, refer the web site: www.pondiuni.edu.in/sites/default/files/BIC-311213.pdf</p>
]]></description>
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