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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30833?offset=1030</link>
	<atom:link href="https://bioinformaticsonline.com/related/30833?offset=1030" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36846/gblocks-eliminates-poorly-aligned-positions-and-divergent-regions-of-a-dna-or-protein-alignment</guid>
	<pubDate>Sat, 02 Jun 2018 07:36:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36846/gblocks-eliminates-poorly-aligned-positions-and-divergent-regions-of-a-dna-or-protein-alignment</link>
	<title><![CDATA[Gblocks: eliminates poorly aligned positions and divergent regions of a DNA or protein alignment]]></title>
	<description><![CDATA[<p><a href="http://molevol.cmima.csic.es/castresana/Gblocks.html">Gblocks</a><span>&nbsp;eliminates poorly aligned positions and divergent regions of a DNA or protein alignment so that it becomes more suitable for phylogenetic analysis. This server implements the most important features of the Gblocks program to make its use as simple as possible without loosing the functionality that it is necessary in most of the cases. Other options can be changed in the stand-alone program. You can see here an&nbsp;</span><a href="http://molevol.cmima.csic.es/castresana/Gblocks_server/nad3.pir-gb.htm">example output file</a><span>&nbsp;showing the blocks selected from a protein alignment. Further information can be found in the&nbsp;</span><a href="http://molevol.cmima.csic.es/castresana/Gblocks/Gblocks_documentation.html">online documentation</a><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="http://molevol.cmima.csic.es/castresana/Gblocks_server.html" rel="nofollow">http://molevol.cmima.csic.es/castresana/Gblocks_server.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24041/junior-bioinformatic-position</guid>
  <pubDate>Wed, 26 Aug 2015 05:35:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[Junior Bioinformatic position]]></title>
  <description><![CDATA[
<p>Junior Bioinformatic position in the laboratory of Inflammation and immunology in cardiovascular pathologies at Humanitas:</p>

<p>We are seeking a highly motivated young PhD student with strong interest in high throughput data analysis.<br />Detailed descriptions of our recent research activities may be found here:<br />http://www.humanitas-research.org/condorelli-gianluigi-md-phd/</p>

<p>Position is available starting from October/November. A probationary period of one month will be required.<br /> <br />Please send a CV along with a cover letter stating the reasons for applying and contact details of one or more referees to Dr. Paolo Kunderfranco (paolo.kunderfranco@humanitasresearch.it).</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38501/fgenesh-program-for-predicting-multiple-genes-in-genomic-dna-sequences</guid>
	<pubDate>Thu, 20 Dec 2018 11:55:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38501/fgenesh-program-for-predicting-multiple-genes-in-genomic-dna-sequences</link>
	<title><![CDATA[FGENESH - Program for predicting multiple genes in genomic DNA sequences]]></title>
	<description><![CDATA[<p>FGENESH is the fastest (50-100 times faster than GenScan) and most accurate gene finder available - see the figure and the table below. In recent rice genome sequencing projects, it was cited "the most successful (gene finding) program (Yu&nbsp;<em>et al</em>. (2002) Science 296:79) and was used to produce 87% of all high-evidence predicted genes (Goff&nbsp;<em>et al</em>. (2002) Science 296:79).</p><p>Address of the bookmark: <a href="http://www.softberry.com/berry.phtml?topic=fgenesh&amp;group=help&amp;subgroup=gfind" rel="nofollow">http://www.softberry.com/berry.phtml?topic=fgenesh&amp;group=help&amp;subgroup=gfind</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6268/project-fellow-national-institute-of-malaria-research</guid>
  <pubDate>Tue, 12 Nov 2013 07:40:51 -0600</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow @ National Institute of Malaria Research]]></title>
  <description><![CDATA[
<p>National Institute of Malaria Research</p>

<p>Sector 8, Dwarka, Delhi -110077</p>

<p>WALK IN INTERVIEW</p>

<p>One position of project fellow is to be filled up in a DRL- funded research project on Molecular and morphological characterization of An. fluviatilis in North-eastern states and bordering areas. The position is purely temporary for one year and can be extended</p>

<p>Essential qualifications</p>

<p>Master’s degree in any branch of Life Sciences with hands on experience in molecular biology and/or bioinformatics.</p>

<p>Age limit: 28 years, (relaxation for SC/ST/OBC candidates as per government of India rules)</p>

<p>Stipend: Rs.12, 000.00 per month (fixed)</p>

<p>Eligible candidates may walk in for an interview on 15 November 2013 at 11 AM at the above mentioned address along with a copy of CV (with a passport size photograph affixed), photocopies of all mark sheets/certificates and originals (for verifications). No TA/DA will be paid for attending the interview .Registration of candidates will start at 10:00AM and end at 10:45 AM.</p>

<p>Advertisement: http://www.mrcindia.org/vacancy/add-4.doc</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40865/dminda2-an-integrated-web-server-for-dna-motif-identification-and-analyses</guid>
	<pubDate>Sun, 02 Feb 2020 14:26:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40865/dminda2-an-integrated-web-server-for-dna-motif-identification-and-analyses</link>
	<title><![CDATA[DMINDA2: an integrated web server for DNA motif identification and analyses]]></title>
	<description><![CDATA[<p><span>DMINDA (</span><strong>D</strong><span>NA&nbsp;</span><strong>m</strong><span>otif&nbsp;</span><strong>i</strong><span>dentification a</span><strong>nd a</strong><span>nalyses) is an integrated web server for DNA motif identification and analyses</span></p>
<p><span>More at&nbsp;http://bmbl.sdstate.edu/DMINDA2/</span></p>
<p><span><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086085/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086085/</a></span></p><p>Address of the bookmark: <a href="http://bmbl.sdstate.edu/DMINDA2/" rel="nofollow">http://bmbl.sdstate.edu/DMINDA2/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6560/the-graveley-lab</guid>
  <pubDate>Tue, 19 Nov 2013 18:02:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Graveley Lab]]></title>
  <description><![CDATA[
<p>Research in the Graveley lab is primarily focused on the regulation of alternative splicing and small RNA mediated gene regulation. These are fascinating and extraordinarily important mechanisms by which genes can be regulated. Our long-term goals are to understand how these processes are regulated at a mechanistic level and to understand the logic of these processes in significant biological settings. To achieve these goals, we strive to think outside the box to creatively attack the problems being addressed using a wide variety of approaches that include biochemistry, genetics, imaging, deep sequencing, large-scale RNAi screening and bioinformatics.</p>

<p>Lab page @ http://graveleylab.cam.uchc.edu/Graveley/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44227/common-methods-to-discover-tandem-repeats</guid>
	<pubDate>Thu, 09 Mar 2023 02:40:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44227/common-methods-to-discover-tandem-repeats</link>
	<title><![CDATA[Common methods to discover tandem repeats]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Tandem repeats are DNA sequences that are repeated in a contiguous manner in the genome. These sequences are often used as genetic markers and are important in many areas of genetics and genomics research. Here are some methods for discovering tandem repeats in genomes:</p><ol>
<li>
<p>Tandem Repeat Finder: Tandem Repeat Finder is a software tool that identifies tandem repeats in DNA sequences. It is available for free download and can be used on both nucleotide and protein sequences. The tool uses a statistical algorithm to identify repeats based on their length, copy number, and overall composition.</p>
</li>
<li>
<p>RepeatMasker: RepeatMasker is another software tool that can identify tandem repeats in DNA sequences. It works by comparing the input sequence to a database of known repeats and then identifies any tandem repeats that match those in the database.</p>
</li>
<li>
<p>PCR-based methods: Polymerase chain reaction (PCR) can be used to amplify and detect tandem repeats in genomic DNA. PCR primers are designed to flank the tandem repeat region, and amplification of the target DNA fragment can be visualized on a gel. This method can be useful for detecting novel tandem repeats and for genotyping.</p>
</li>
<li>
<p>Southern blotting: Southern blotting is a classic method for detecting DNA fragments in a sample. It can be used to detect tandem repeats by digesting genomic DNA with a restriction enzyme, separating the fragments by gel electrophoresis, and then probing the blot with a tandem repeat-specific probe.</p>
</li>
</ol><p>Overall, a combination of these methods can be used to comprehensively identify tandem repeats in genomes.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <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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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44616/basics-of-blast-programs</guid>
	<pubDate>Fri, 26 Jul 2024 06:04:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44616/basics-of-blast-programs</link>
	<title><![CDATA[Basics of BLAST Programs !]]></title>
	<description><![CDATA[<p>The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.</p><p>Key Features of BLAST:<br />1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.</p><p>2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.</p><p>3. Versatility: There are several versions of BLAST for different types of sequence comparisons:<br /> - blastn: Compares a nucleotide query sequence against a nucleotide sequence database.<br /> - blastp: Compares a protein query sequence against a protein sequence database.<br /> - blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.<br /> - tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.<br /> - tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.</p><p>4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.</p><p>5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.</p><p>Applications of BLAST:<br />- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.<br />- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.<br />- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.<br />- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.</p><p>Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.</p>]]></description>
	<dc:creator>BioStar</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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