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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30124?offset=1340</link>
	<atom:link href="https://bioinformaticsonline.com/related/30124?offset=1340" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30825/open-positions-in-pasini%E2%80%99s-lab</guid>
  <pubDate>Sat, 04 Feb 2017 08:17:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Open Positions in Pasini’s lab]]></title>
  <description><![CDATA[
<p>Computational Biologists<br />Open to PhD-student and Post-doc candidates<br />We are looking for wet and computational biologists to work on an ERC funded project in our<br />laboratory located at the Department of Experimental Oncology of the European Institute of<br />Oncology in Milan (Italy). The project will focus on different aspects of the function of Polycomb<br />Group proteins and other chromatin modifying activities in relation to their role in regulating cellular<br />identity in the development of adult tissues.<br />The candidates will be in charge of computational analysis and data management related to the<br />project. She/he will directly interact with the wet scientists working in our laboratory while working<br />embedded in the community of computational biologists present at our institution. The work will<br />involve the analysis of sequencing data produced with cutting edge technologies to study gene<br />expression and chromatin environment including data produced on rare cell populations and single<br />cells. The applicants must have a good knowledge of programming in python/perl/java along with<br />strong statistical background and performing analysis in R platform. A biological background is<br />also recommended however it’s not mandatory for application.<br />Each applicant should submit a full CV (with a detailed description of her/his background,<br />expertise, achievements and publication records) together with a letter of intent and at least two<br />contacts for recommendations (for a post-doc position). Competitive salary will be offered based<br />on the experience of the candidate. Non Italian as well as Italian applicants that have been working<br />outside Italy (&gt;3yrs.) will have the opportunity to benefit of a full tax deduction for the first three<br />years of contract.<br />Applications should be submitted as single PDF to diego.pasini@ieo.it</p>

<p>Lab https://www.ieo.it/en/RESEARCH/People/Researchers/Pasini-Diego/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30889/phd-program-in-computer-science-at-university-of-essex</guid>
  <pubDate>Sat, 11 Feb 2017 13:11:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD program in Computer Science at University of Essex]]></title>
  <description><![CDATA[
<p>As part of the PhD program in Computer Science at University of Essex, I am looking for a PhD student in computational and synthetic biology.<br />The ideal candidate is interested in designing new biological design automation methods for genome scale projects and/or network modelling of genomic, transcriptomic and proteomic data.<br />Candidates interested in developing optimization algorithms for biological problems are encouraged to apply as well.<br />A summary of the research work in the lab can be found on o this page.</p>

<p>Candidates interested in the position should contact me in advance by email to: g.stracquadanio@essex.ac.uk</p>

<p>The deadline for the application is 28/02/2017; info about the application can be found on the Essex CSEE website.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31976/snpgenie</guid>
	<pubDate>Thu, 30 Mar 2017 17:38:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31976/snpgenie</link>
	<title><![CDATA[SNPGenie]]></title>
	<description><![CDATA[<p>SNPGenie is a Perl script for estimating evolutionary parameters, mainly from pooled next-generation sequencing (NGS) single-nucleotide polymorphism (SNP) variant data. SNP reports (acceptable in a variety of formats) much each correspond to a single population, with variants called relative to a single reference sequence (one sequence in one FASTA file). Just run the main script, <strong>snpgenie.pl</strong>, in a directory containing the necessary <a href="https://github.com/hugheslab/snpgenie#snpgenie-input">input files</a>, and we take care of the rest! For the earlier version, see <a href="http://ww2.biol.sc.edu/~austin/">Hughes Lab Bioinformatics Resource</a>.</p><p>Address of the bookmark: <a href="https://github.com/hugheslab/snpgenie" rel="nofollow">https://github.com/hugheslab/snpgenie</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32496/bioinformatician-at-23andme</guid>
  <pubDate>Sat, 06 May 2017 17:57:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician at 23andMe]]></title>
  <description><![CDATA[
<p>23andMe’s mission is to help people access, understand, and benefit<br />from the human genome. We are a group of passionate individuals excited<br />to push the boundaries of what’s possible to help turn genetic insight<br />into better health and personal understanding.</p>

<p>Our Research Team prides itself on driving cutting edge, industrial-scale<br />science to make an impact that belies the team’s size, in an environment<br />and culture that fosters creativity, innovation, collaboration, and fun.</p>

<p>More than 80% of our customers consent to participate in research, and as<br />a result of their participation, we have one of the largest recontactable,<br />genotyped, and phenotyped research cohorts in the world. The scope and<br />breadth of our vision means that most of the methods and tools necessary<br />to unlock the potential of this unique resource for discovery have yet<br />to be developed.</p>

<p>Our science has garnered the respect of many members of the<br />broader scientific community. For a list of our publications, see<br />www.23andme.com/publications/for-scientists/.</p>

<p>Join us! Visit our Careers page (www.23andMe.com/careers) to learn more<br />about these open positions:</p>

<p>•	Scientist, Research Communications<br />•	Bioinformaticist<br />•	Computational Biologist, Ancestry R&amp;D<br />•	Scientist/Senior Scientist, Statistical Genetics<br />•	Scientist/Senior Scientist, Survey Methodology<br />•	Scientist/Senior Scientist, Health R&amp;D<br />•	Senior Computational Biologist<br />•	Biostatistician</p>

<p>pfontanillas@23andme.com</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</guid>
	<pubDate>Wed, 07 Feb 2018 09:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</link>
	<title><![CDATA[HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution]]></title>
	<description><![CDATA[<p>Software accompanying "HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution"</p>
<ul>
<li>
<p>Preprint:&nbsp;<a href="http://biorxiv.org/content/early/2016/08/01/062117">http://biorxiv.org/content/early/2016/08/01/062117</a></p>
</li>
<li>
<p>Paper:&nbsp;<a href="http://genome.cshlp.org/content/27/5/747.full">http://genome.cshlp.org/content/27/5/747.full</a></p>
</li>
<li>
<p>An ipython notebook to reproduce results in the paper can be found in this&nbsp;<a href="https://github.com/govinda-kamath/HINGE-analyses">repository</a>.</p>
</li>
</ul>
<p>HINGE is an OLC(Overlap-Layout-Consensus) assembler. The idea of the pipeline is shown below.</p>
<p><a href="https://github.com/HingeAssembler/HINGE/blob/master/misc/High_level_overview.png" target="_blank"><img src="https://github.com/HingeAssembler/HINGE/raw/master/misc/High_level_overview.png" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/HingeAssembler/HINGE" rel="nofollow">https://github.com/HingeAssembler/HINGE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <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>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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