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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/21444?offset=1230</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/32358/list-of-goi-approved-peer-reviewed-bioinformatics-and-computational-biology-journals</guid>
	<pubDate>Tue, 25 Apr 2017 05:03:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/32358/list-of-goi-approved-peer-reviewed-bioinformatics-and-computational-biology-journals</link>
	<title><![CDATA[List of GOI approved peer reviewed bioinformatics and computational biology journals]]></title>
	<description><![CDATA[<p>Unfortunately, we now live in a world where the integrity of peer-reviewed journals is being threatened by the rise of the academic version of fake news &ndash; something many call &ldquo;predatory publishing". &nbsp;Mostly in academic publishing world, "predatory open access publishing" is an exploitative open-access publishing business model that involves charging publication fees to authors without providing the editorial and publishing services associated with legitimate journals (open access or not).</p><p>Nearly 20% of the such journals have a flashy impact factor and quick publication time, which are quick give-aways. Interestingly, under contact address, some journal websites do not even provide any address to contact. All of this has led to the emergence of a new and dark market of deceptive publishers that exploit the concept of open access and provide channels for &ldquo;scientific journal&rdquo; publication with little or no peer review. For a fee, they will publish almost anything &ndash; even if the study was fatally flawed. And these journals provide a forum that can be used as a channel to publish fraudulent &ldquo;advocacy research.&rdquo; You can find list of certain such publishers at "Beall's List" http://beallslist.weebly.com/</p><p>Keeping all these in mind, Government of India (GOI) decided to approved certain bioinformatics and computational biology journals for your research publication.<br /> <br />Following are the list of GOI validated and peer reviewed bioinformatics and computational biology journals:</p><p><strong>NOTE:Each journal details are in following order Tittle\nSource\nSubject. </strong><br /><strong>Point to remember: The list of journals are NOT sorted in any ascending or descending order.</strong></p><p><em>If I missed any other GOI validated bioinformatics journal, then please report me in comment section.</em></p><p><strong>Open Bioinformatics Journal</strong> <br />Scopus <br />Computer Science; Engineering; Medicine</p><p><strong>PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS</strong> <br />WoS <br />BIOLOGY &amp; BIOCHEMISTRY</p><p><strong>Advances and Applications in Bioinformatics and Chemistry</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology Chemistry; Computer Science</p><p><strong>Advances in Bioinformatics</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science; Engineering</p><p><strong>Applied Bioinformatics</strong><br />Scopus<br />Agricultural and Biological Sciences; Computer Science</p><p><strong>BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Bioinformatics and Biology Insights</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science; Mathematics</p><p><strong>BMC BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>BRIEFINGS IN BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Computational systems bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference</strong> <br />Scopus <br />Medicine</p><p><strong>Current Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Current Protocols in Bioinformatics</strong> <br />Scopus <br />Biochemistry, Genetics and Molecular Biology</p><p><strong>JOURNAL OF COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS</strong> <br />ICI <br />BIOLOGICAL SCIENCE</p><p><strong>Journal of integrative bioinformatics</strong> <br />Scopus <br />Medicine</p><p><strong>Journal of Proteomics and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science</p><p><strong>Mathematical Biology and Bioinformatics</strong> <br />Scopus <br />Engineering; Mathematics</p><p><strong>Trends in Bioinfprmatics</strong><br />Scopus <br />Computer Science</p><p><strong>Eurasip Journal on Bioinformatics and Systems Biology</strong> <br />Scopus<br />General; Computer Science; Mathematics; Medicine</p><p><strong>Evolutionary Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Genomics, Proteomics and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Mathematics</p><p><strong>IEEE/ACM Transactions on Computational Biology and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Mathematics</p><p><strong>IEEE-ACM Transactions on Computational Biology and Bioinformatics</strong> <br />WoS <br />COMPUTER SCIENCE</p><p><strong>International Journal of Bioinformatics Research and Application</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Medicine, Health</p><p><strong>International Journal o f Data M ining and Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>IPSJ Transactions on Bioinformatics</strong> <br />Scopus <br />Biochemistry, Genetics and Molecular Biology;Computer Science</p><p><strong>Journal of Bioinformatics and Computational Biology</strong> <br />WoS &amp; Scopus<br />COMPUTER SCIENCE</p><p><strong>Journal of Clinical Bioinformatics</strong> <br />Scopus <br />Medicine</p><p><strong>PLoS Computational Biology</strong> <br />WoS &amp; Scopus <br />BIOLOGY &amp; BIOCHEMISTRY</p><p><strong>Reviews in Computational Chemistry</strong> <br />WoS &amp; Scopus <br />CHEMISTRY</p><p><strong>RSC Theoretical and Computational Chemistry Series</strong><br />Scopus <br />Chemistry; Computer Science</p><p><strong>Annual Reports in Computational Chemistry</strong> <br />Scopus <br />Chemistry; Mathematics</p><p><strong>Computational and Structural Biotechnology Journal</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science</p><p><strong>Computational and Theoretical Chemistry</strong> <br />WoS &amp; Scopus <br />CHEMISTRY</p><p><strong>COMPUTATIONAL BIOLOGY AND CHEMISTRY</strong> <br />WoS &amp; Scopus<br />COMPUTER SCIENCE</p><p><strong>COMPUTATIONAL CHEMISTRY</strong> <br />WoS <br />CHEMISTRY</p><p><strong>Journal of Theoretical and Computational Chemistry</strong> <br />Scopus<br />Chemistry; Computer Science</p><p><strong>Theoretical and Computational Chemistry</strong> <br />Scopus <br />Chemistry</p><p><strong>Wiley Interdisciplinary Reviews: Computational Molecular Science</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Chemistry; Computer Science; Materials Science; Mathematics</p><p><strong>Wiley Interdisciplinary Reviews- Computational Molecular Science</strong> <br />WoS <br />CHEMISTRY</p><p><strong>Interdisciplinary sciences, computational life sciences</strong><br />Scopus<br />Medicine</p><p><strong>Interdisciplinary Sciences-Computational Life Science</strong><br />WoS<br />Biology and Biochemistry</p><p><strong>International Journal of Computational Biology and Drug Design</strong><br />Scopus<br />Computer Science; Pharmacology, Toxicology and Pharmaceutics</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/871/postdoctoral-position-in-bioinformatics-sweden</guid>
  <pubDate>Sun, 14 Jul 2013 13:49:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral position in bioinformatics @ Sweden]]></title>
  <description><![CDATA[
<p>Information about the department<br />The Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg has about 170 faculty and staff and is the largest department of mathematical sciences in the Nordic countries. The department belongs to both Chalmers University of Technology and the University of Gothenburg (for more information see http://www.chalmers.se/math/).</p>

<p>Job description<br />We are looking for a motivated, self-driven post-doctoral researcher to work with large-scale sequence data analysis. The position is for 24 months and located at Mathematical Statistics, Department of Mathematical Sciences in Erik Kristiansson’s research group. We are focused on methods development for and analysis of next generation DNA sequencing, in particular comparative metagenomics and gene expression analysis (RNA-seq). We have strong interdisciplinary profile and are actively collaborating with several experimental groups, especially within the environmental sciences, ecology, infectious diseases and cancer genomics. More information is available at http://bioinformatics.math.chalmers.se.</p>

<p>The Post-doctoral position is an appointment that offers an opportunity to qualify for further research positions within academia or industry. The majority of your working time is devoted to your own research, normally as a member of a research group. Included in your work is also to take part in supervision of Ph.D. students and M.Sc thesis students. Teaching of undergraduate students may also be included to a small extent.</p>

<p>The employment is limited to a maximum of 2 years (1+1).</p>

<p>Qualifications<br />The applicant should have Ph.D. degree preferably in bioinformatics, mathematics, statistics, computer science or equivalent by the start of the appointment. Experience from analysis of large-scale data, in particular from next generation DNA sequencing, is highly valued. The applicant should also be proficient in programming (e.g. Python/Java/C) and comfortable with Unix/Linux systems. Interaction with experimental biologists is central and good collaborative skills are therefore important. Fluency in written and spoken English is a strong requirement. As a post-doctoral researcher you are expected to work independently and to be able to supervise/co-supervise PhD and Master’s students.</p>

<p>Application procedure<br />The application should be marked with Ref 20130126 and written in English. The application should be sent electronically via Chalmers webpage.</p>

<p>Application deadline: September 8, 2013.</p>

<p>For questions, please contact: <br />Ass prof. Erik Kristiansson, Matematiska Vetenskaper, erik.kristiansson@chalmers.se, +46 31-772 3521, +46 70-5259751.</p>

<p>Chalmers continuously strive to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32420/fastq-format</guid>
	<pubDate>Wed, 03 May 2017 04:23:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32420/fastq-format</link>
	<title><![CDATA[Fastq format]]></title>
	<description><![CDATA[<p><strong>FASTQ format</strong>&nbsp;is a text-based&nbsp;<a href="https://en.wikipedia.org/wiki/File_format" title="File format">format</a>&nbsp;for storing both a biological sequence (usually&nbsp;<a href="https://en.wikipedia.org/wiki/Nucleotide_sequence" title="Nucleotide sequence">nucleotide sequence</a>) and its corresponding quality scores. Both the sequence letter and quality score are each encoded with a single&nbsp;<a href="https://en.wikipedia.org/wiki/ASCII" title="ASCII">ASCII</a>&nbsp;character for brevity.</p>
<p>It was originally developed at the&nbsp;<a href="https://en.wikipedia.org/wiki/Wellcome_Trust_Sanger_Institute" title="Wellcome Trust Sanger Institute">Wellcome Trust Sanger Institute</a>&nbsp;to bundle a&nbsp;<a href="https://en.wikipedia.org/wiki/FASTA_format" title="FASTA format">FASTA</a>&nbsp;sequence and its quality data, but has recently become the&nbsp;<em>de facto</em>&nbsp;standard for storing the output of high-throughput sequencing instruments such as the&nbsp;<a href="https://en.wikipedia.org/wiki/Illumina_(company)" title="Illumina (company)">Illumina</a>&nbsp;Genome Analyzer.<sup id="cite_ref-Cock2009_1-0"><a href="https://en.wikipedia.org/wiki/FASTQ_format#cite_note-Cock2009-1">[1]</a></sup></p><p>Address of the bookmark: <a href="https://en.wikipedia.org/wiki/FASTQ_format" rel="nofollow">https://en.wikipedia.org/wiki/FASTQ_format</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</guid>
	<pubDate>Fri, 05 May 2017 06:11:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</link>
	<title><![CDATA[Bacterial genome assembly !!]]></title>
	<description><![CDATA[<p>This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of&nbsp;bacterial sequence data. The bacterial sample used in this tutorial will be referred&nbsp;to simply&nbsp;as &ldquo;Species&rdquo; since it is&nbsp;live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.</p>
<p>https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md</p><p>Address of the bookmark: <a href="http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/" rel="nofollow">http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/918/data-mining-in-bioinformatics</guid>
	<pubDate>Tue, 16 Jul 2013 03:21:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/918/data-mining-in-bioinformatics</link>
	<title><![CDATA[Data Mining in Bioinformatics]]></title>
	<description><![CDATA[<p>Data mining, the extraction of hidden predictive information from large databases. Data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. Data Mining for Bioinformatics enables researchers to meet the challenge of mining vast amounts of biomolecular data to discover real knowledge. In other words, you&rsquo;re a bioinformatician, and data has been dumped in your lap. Find the patterns, trend, answers, or what ever meaningful knowledge the data is hiding. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations.This page Covering theory, algorithms, and methodologies, as well as data mining technologies. Unfortunately life is never simple. In molecular biology, it&rsquo;s becoming more common to generate reams of data then ask someone in bioinformatics to produce an answer. This is exploratory data analysis, one of the most difficult things to do well. Especially if you&rsquo;re thrown in at the deep end.</p><p><strong>Data mining commonly involves four classes of tasks:</strong></p><ul>
<li>Classification - Arranges the data into predefined groups. For example, an email program might attempt to classify an email as legitimate or spam. Common algorithms include decision tree learning, nearest neighbor, naive Bayesian classification and neural networks.</li>
<li>Clustering - Is like classification but the groups are not predefined, so the algorithm will try to group similar items together.</li>
<li>Regression - Attempts to find a function which models the data with the least error.</li>
<li>Association rule learning - Searches for relationships between variables. For example a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes. This is sometimes referred to as market basket analysis.</li>
<li>From experience, I can say that is one of the most frustrating positions to be in. Data mining is a huge field and can easily be bewildering for a beginner. However, high through-put techniques in molecular biology require, more and more, that bioinformatics is required to interpret the data. Furthermore, people working in bioinformatics generally come from computer science, or biology backgrounds. Data mining, however, involves statistics to one degree or another, which means entering a field that is may not be your strong point.</li>
<li>Excel is fine for creating graphs. If you&rsquo;re serious about data mining though, you&rsquo;ll need something more heavy weight. I use R, free, and with good data mining packages such as vegan and labdsv. For beginners R can be impenetrable, I recommend this book an introduction to R as well as the underlying statistics.</li>
<li>Any of us can rush head on into a land of support vector machines, hidden markov models and neural networks. But coming back to the first point, what are you trying to prove? Always question what are you doing, how does it fit in to the wider picture? Try to regularly review, and keep track of where you are going? This will prevent you from falling into data mining despair.</li>
</ul><p><strong>Data Mining Resources on the net:</strong><br /><br />A laboratory of data mining and bioinformatics is headed by Prof. Ambuj Singh. There are currently seven graduate students in the research group. Our research focuses on image informatics and scalable querying and mining of graphs.For more detail visit:&nbsp;<a href="http://www.cs.ucsb.edu/~dbl/">http://www.cs.ucsb.edu/~dbl/</a></p><p>Here are the materials (Lecture notes) from several past courses on data mining and/or Web mining by Stanford: For detail visit:&nbsp;<a href="http://infolab.stanford.edu/~ullman/mining/mining.html">http://infolab.stanford.edu/~ullman/mining/mining.html</a><br />Statistical Data Mining Tutorial Slides by Andrew Moore The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. For detail visit:&nbsp;<a href="http://www.autonlab.org/tutorials/">http://www.autonlab.org/tutorials/</a></p><p>A tutorial on Introduction to Data Mining for Discovering hidden value in your data warehouse:<a href="http://www.thearling.com/text/dmwhite/dmwhite.htm">http://www.thearling.com/text/dmwhite/dmwhite.htm</a>&nbsp;<br />Wiki Links:&nbsp;<a href="http://en.wikipedia.org/wiki/Data_mining">http://en.wikipedia.org/wiki/Data_mining</a><br />Bioinformatics with Clementine&nbsp;<a href="http://www.spss.ch/upload/1051192224_inseratClemBio.pdf">http://www.spss.ch/upload/1051192224_inseratClemBio.pdf</a>&nbsp;<br />Causal Data Mining in Bioinformatics by Ioannis Tsamardinos:&nbsp;<a href="http://www.forth.gr/ics/bmi/In_the_News/2007/EN69-4.pdf">http://www.forth.gr/ics/bmi/In_the_News/2007/EN69-4.pdf</a></p><p>Report on ACM Text Mining in Bioinformatics (TMBIO 006)&nbsp;<a href="http://www.sigir.org/forum/2007J/2007j_sigirforum_song.pdf">http://www.sigir.org/forum/2007J/2007j_sigirforum_song.pdf</a>&nbsp;<br />BIOKDD 2002: Recent Advances in Data Mining for&nbsp;<br />Bioinformatics:&nbsp;<a href="http://www.acm.org/sigs/sigkdd/explorations/issue4-2/zaki.pdf">http://www.acm.org/sigs/sigkdd/explorations/issue4-2/zaki.pdf</a></p><p><strong>Bioinformatics and Medical Informatics:</strong>&nbsp;<br /><br />Tools for Mining and Applying Genetic Information in Patient Care:<a href="http://www.biomedtechalliance.org/pdfs/03_03_05/03_03_05.pdf">http://www.biomedtechalliance.org/pdfs/03_03_05/03_03_05.pdf</a></p><p>DATA MINING OF MICROARRAY DATABASES FOR HUMAN LUNG CANCER:&nbsp;<a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.106.385&amp;rep=rep1&amp;type=pdf">http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.106.385&amp;rep=rep1&amp;type=pdf</a></p><p>Towards knowledge-based gene expression data mining:&nbsp;<a href="http://www.ailab.si/blaz/papers/2007-JBI-BellazziZupan.pdf">http://www.ailab.si/blaz/papers/2007-JBI-BellazziZupan.pdf</a></p><p>DRAFT Accepted for publication in 'Data Mining in Bioinformatics'<br />Jason Wang, Mohammed Zaki, Hannu Toivonen, and Dennis Shasha (Eds.), Springer:<a href="http://www.cs.helsinki.fi/u/htoivone/pubs/gene_mapping_by_pattern_discovery.pdf">http://www.cs.helsinki.fi/u/htoivone/pubs/gene_mapping_by_pattern_discovery.pdf</a></p><p>Data Mining and Text Mining for Bioinformatics: Proceedings of the European Workshop:&nbsp;<a href="http://www.rok.informatik.hu-berlin.de/wbi/research/publications/2003/proceedings_ws_mining.pdf">http://www.rok.informatik.hu-berlin.de/wbi/research/publications/2003/proceedings_ws_mining.pdf</a></p><p><strong>Biological Network Analysis:<br /></strong><br />Graph Mining in Bioinformatics:&nbsp;<a href="http://agbs.kyb.tuebingen.mpg.de/wikis/bg/BNA-5.pdf">http://agbs.kyb.tuebingen.mpg.de/wikis/bg/BNA-5.pdf</a>.</p><p>Text mining in bioinformatics:&nbsp;<a href="http://agbs.kyb.tuebingen.mpg.de/wikis/bg/4.pdf">http://agbs.kyb.tuebingen.mpg.de/wikis/bg/4.pdf</a></p><p>Some datamining books that are available on google books:</p><p>Data mining and bioinformatics: first international workshop, VDMB 2006 By Mehmet M. Dalkilic</p><p>Data mining: concepts and techniques By Jiawei Han, Micheline Kamber</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</guid>
	<pubDate>Fri, 12 May 2017 09:24:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</link>
	<title><![CDATA[Barrnap: Bacterial ribosomal RNA predictor]]></title>
	<description><![CDATA[<p>Barrnap predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).</p>
<p>It takes FASTA DNA sequence as input, and write GFF3 as output. It uses the new NHMMER tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. NHMMER binaries for 64-bit Linux and Mac OS X are included and will be auto-detected. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/tseemann/barrnap" rel="nofollow">https://github.com/tseemann/barrnap</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32716/jrfsrf-project-assistant-ii-recruitment-in-national-agri-food-biotechnology-institute-nabi</guid>
  <pubDate>Mon, 15 May 2017 05:37:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF / Project Assistant-II recruitment in National Agri-Food Biotechnology Institute (NABI)]]></title>
  <description><![CDATA[
<p>National Agri-Food Biotechnology Institute<br />ADVT. No: 2017-Researcher (02)</p>

<p>JRF/SRF / Project Assistant-II recruitment in National Agri-Food Biotechnology Institute (NABI)</p>

<p>Essential Qualification: According to the DST (DST OM No.SR/S9/Z-09/2012 dated 21.10.2014) Post Graduate degree in basic science(M.Sc) in Bioinformatics/Computational Biology/Systems Biology/Information Technology with NET or Graduate degree in professional course with NET or Post Graduate Degree (M.Tech) in professional course in Bioinformatics/Computational Biology/Systems Biology/Information Technology. Desirable qualification/skills: 1) Should be proficient in programming in Perl/Python/R language etc. 2) Should have knowledge and skills for data mining in biological sequence database . sequence analysis tools/packages, NGS Analysis . 3) Should have knowledge and skills to work in linux environment and write shell scripts.</p>

<p>Age : 28 years</p>

<p>Hiring Process : Written-test<br />Job Role : Research/JRF/SRF<br />How to apply</p>

<p>Application should be sent to Administrative officer, National Agri-Food Biotechnology Institute, Knowledge City, Sector-81, Mohali so as to reach latest by 30.05.2017 before 5:30 pm.</p>

<p>More at http://www.nabi.res.in/Vacancies/NABI/ResearchFellowships/JRFSRFRA/2017/ADVT.%20No%202017Researcher%20(02)/ApplicationForm.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1219/research-with-help-of-bioinformatics-helpful</guid>
	<pubDate>Fri, 02 Aug 2013 11:20:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1219/research-with-help-of-bioinformatics-helpful</link>
	<title><![CDATA[Research with help of bioinformatics helpful]]></title>
	<description><![CDATA[<p>Endocrinologist G.R. Sridhar says</p><blockquote><p>Research with the help of bioinformatics with a trans-disciplinary approach is yielding good results.</p><p>http://www.thehindu.com/features/education/research/research-with-help-of-bioinformatics-helpful/article2295629.ece</p></blockquote>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32822/phd-positions-in-genova-at-dibris-univ-of-genoa-italy</guid>
  <pubDate>Thu, 18 May 2017 00:04:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD positions in Genova at DIBRIS - Univ. of Genoa, Italy]]></title>
  <description><![CDATA[
<p>PhD positions in Genova at DIBRIS - Univ. of Genoa (Italy)</p>

<p>http://www.disi.unige.it/person/MasulliF/ricerca/PhDinGenova2017.html</p>

<p>The call for some funded positions for  the 3 years PhD studies  at the Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS) in Genova is available at</p>

<p>http://www.studenti.unige.it/postlaurea/dottorati/XXXIII/ENG/</p>

<p>The deadline for applications is June13, 2017 and the PhD courses and fellowships should start on Nov 2017.</p>

<p>Details for the application to the  PhD Program in Computer Science and Systems Engineering (CODICE 6608) are at http://phd.dibris.unige.it/csse/index.php/how-to-apply</p>

<p>The research activity of my research group is focused on Computational Intelligence, Machine Learning, Bioinformatics, Systems Biology, and Positive Technology as described at http://www.disi.unige.it/person/MasulliF/ricerca/index.html</p>

<p>The research themes proposed by me and Prof. Stefano Rovetta are:</p>

<p>- Computational Intelligence and Machine Learning (see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T1.html)</p>

<p>- Computational Intelligence and Health and Wellbeing Support( see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T3.html)</p>

<p>You can also propose a different research theme belonging to the research activity of my group.</p>

<p>Looking for self-motivated PhD candidates, interested to the mathematical aspects of their research and to the development of new algorithms for intelligent data analysis, and skilled in programming and   in  thorough experimental data analysis. They will be part of my research group and will collaborate to our research projects and publications.</p>

<p>Italian and international students interested to work are invited  to send their cv  and the name/email-addresses of 3 referees to my email address francesco.masulli@unige.it A.S.A.P.</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/33966/ra-bioinformatics-at-national-institute-of-biomedical-genomics-india</guid>
  <pubDate>Wed, 26 Jul 2017 03:49:52 -0500</pubDate>
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  <title><![CDATA[RA Bioinformatics at NATIONAL INSTITUTE OF BIOMEDICAL GENOMICS,  INDIA]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF BIOMEDICAL GENOMICS<br />(An Autonomous Institution of the Government of India) <br />P.O.: N.S.S., Kalyani 741251, West Bengal</p>

<p>Advertisement No. 137/ESTB/NIBMG/17-18 </p>

<p>Position available Project Description: Several positions are available for the project titled: “A unified web-portal for analysis, integration and visualization of multi-omics data”. The goal of this project is to develop a user-accessible resource for integrated analysis and visualization of multi-OMICs data sets (including gene expression, genotype, methylation, microRNA, etc.). Data sets generated on various platforms shall be maintained in a stable database, accessed through standard querying mechanisms, and the results shall be displayed via user-friendly interface. The analysis engine shall run on open-source software (such as R/Bioconductor) developed in-house. All positions are contractual. </p>

<p>Appointment will be initially given for a period of one year which is extendable depending upon performance, availability of funds and requirements of the institute. </p>

<p>Project Code: 20275 Position: (No. of positions available) </p>

<p>Research Associate (3)</p>

<p>Position 1: Ph.D. or equivalent in statistics, computer science, mathematics, bioinformatics, or related subject. <br />Position 1: Those with experience in database management shall be preferred. Experience with UNIX or GNU/Linux operating system. <br />Position 1: Creation and maintenance of a database for population- and diseaseassociated variation resource. Development of programmatic interface for querying the database, filtering of the results and identification of genes of interest. </p>

<p>Rs. 36000/- + 10% HRA </p>

<p>Please apply online via web link http://apply.nibmg.ac.in/ (no other form of application will be accepted). The last date of application is 14-08-2017. All letters to attend screening test and /or interview will be sent only to the short-listed candidates by Email only. No correspondence will be made with applicants who are not shortlisted /not called for screening test and /or interview. No TA/DA will be paid for attending the screening test and /or interview.<br />Detail information at http://www.nibmg.ac.in/academic/Advt_20275.pdf</p>

<p>More Info: http://www.nibmg.ac.in/?q=Project%20Linked%20Personnel</p>
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