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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31014?offset=440</link>
	<atom:link href="https://bioinformaticsonline.com/related/31014?offset=440" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/39471/bioinformatics-for-precision-oncology-online-training-program-summer-2019</guid>
	<pubDate>Wed, 05 Jun 2019 15:04:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/39471/bioinformatics-for-precision-oncology-online-training-program-summer-2019</link>
	<title><![CDATA[Bioinformatics for Precision Oncology - Online Training Program, Summer 2019]]></title>
	<description><![CDATA[<p><img src="https://edu.t-bio.info/wp-content/uploads/2019/05/OncologyBioinformatics.jpeg" width="600" height="337.5" alt="image" style="border: 0px;"></p><p>The bioinforamtics for precision oncology online course provides an opportunity to learn about bioinformatics methods used in precision oncology research and practice. As a subset of precision medicine, precision oncology deals with molecular factors involved in the biological rpocesses that lead to cancer and can help diagnose, treat or prevent this disease. Oncology is driven by data, often times generated using Next Generation Sequencing (NGS) that helps us study the genomic and transcriptomic sub-cellular processes. Learn more and register:&nbsp;https://edu.t-bio.info/bioinformatics-training-precision-oncology/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8122/internships-indian-institute-of-science</guid>
  <pubDate>Sun, 02 Feb 2014 03:05:58 -0600</pubDate>
  <link></link>
  <title><![CDATA[Internships @ Indian Institute of Science]]></title>
  <description><![CDATA[
<p>Internships available for Bachelors and Masters students</p>

<p>Each node will host student interns interested in pursuing a research career in mathematical or computational biology at institutions located in its region.</p>

<p>Eligibility: Bachelors (3rd or 4th year) and Masters students</p>

<p>Average duration: 3 months (could be more in certain cases). These internships can be availed at any time during 2014 subject to consent from the faculty mentor.</p>

<p>Fellowship amount: Rs. 10,000 per month. In addition, outstation interns can receive up to Rs. 5000 per month for accommodation and Rs. 3000 for travel from and to their home place.</p>

<p>Application procedure: Apply online at http://nnmcb.appzone.co.in/</p>

<p>Deadline: February 10, 2014</p>

<p>Contact Information:</p>

<p>National Network for Mathematical and Computational Biology</p>

<p>Department of Mathematics</p>

<p>Indian Institute of Science</p>

<p>Bangalore 560 012</p>

<p>Tel: 080-2293 2893</p>

<p>Email: nnmcb@math.iisc.ernet.in</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/8265/list-of-generic-simulation-softwaretoolsresource-with-brief-description-and-homepage</guid>
	<pubDate>Mon, 10 Feb 2014 05:57:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/8265/list-of-generic-simulation-softwaretoolsresource-with-brief-description-and-homepage</link>
	<title><![CDATA[List of generic simulation software/tools/resource with brief description and homepage !!!]]></title>
	<description><![CDATA[<p>List of generic simulation software/tools/resource with brief description and homepage</p><p><img src="http://www.evolution-of-life.com/fileadmin/images/carousel/genetic.PNG" alt="image" style="border: 0px;"></p><p>ALF <br />A Simulation Framework for Genome Evolution <br />http://www.cbrg.ethz.ch/alf<br /><br />Bayesian Serial SimCoal <br />Bayesian Serial SimCoal, (BayeSSC) is a modification of SIMCOAL 1.0, a program written by Laurent Excoffier, John Novembre, and Stefan Schneider. <br />http://www.stanford.edu/group/hadlylab/ssc/index.html<br /><br />BEERS <br />BEERS was designed to benchmark RNA-Seq alignment algorithms and also algorithms that aim to reconstruct different isoforms and alternate splicing from RNA-Seq data <br />http://cbil.upenn.edu/beers/<br /><br />BOTTLENECK <br />Bottleneck is a program for detecting recent effective population size reductions from allele data frequencies <br />http://www.ensam.inra.fr/urlb/bottleneck/bottleneck.html<br /><br />BottleSim <br />BottleSim is a computer simulation program for simulating the process of population bottlenecks <br />http://chkuo.name/software/bottlesim.html<br /><br />CASS <br />Protein Sequence Simulation <br />http://www.wyomingbioinformatics.org/liberlesgroup/cass/<br /><br />CDPOP <br />CDPOP is a landscape genetics tool for simulating the emergence of spatial genetic structure in populations resulting from specified landscape processes governing organism movement behavior. <br />http://cel.dbs.umt.edu/cdpop<br /><br />CoalFace <br />CoalFace is a simulation of the coalescent process with the visual display of gene genealogies. <br />http://web.up.ac.za/default.asp?ipkcategoryid=3283<br /><br />CoaSim <br />CoaSim is a tool for simulating the coalescent process with recombination and geneconversion under various demographic models. <br />http://users-birc.au.dk/mailund/coasim/index.html<br /><br />cosi <br />The cosi package is written in C and is available as a tar file. <br />http://www.broadinstitute.org/~sfs/cosi/<br /><br />CS-PSeq-Gen <br />A program to simulate the evolution of protein sequences under the constraints of the information of a particular reconstructed phylogeny <br />http://bioserv.rpbs.univ-paris-diderot.fr/software/cs-pseq-gen.html<br /><br />DAWG <br />An application designed to simulate the evolution of recombinant DNA sequences in continuous time <br />http://scit.us/projects/dawg<br /><br />Easypop <br />EASYPOP is an individual based model intended to simulate datasets under a very broad range of conditions <br />http://www.unil.ch/dee/page36926_fr.html<br /><br />EggLib <br />EggLib is a C++/Python library and program package for evolutionary genetics and genomics. <br />http://egglib.sourceforge.net/<br /><br />EvolSimulator <br />A simulation test bed for hypotheses of genome evolution <br />http://acb.qfab.org/acb/evolsim/<br /><br />EvolveAGene <br />A realistic coding sequence simulation program that separates mutation from selection and allows the user to set selection conditions <br />http://bellinghamresearchinstitute.com/software/index.html<br /><br />fastsimcoal <br />A continuous-&not;‐time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios <br />http://cmpg.unibe.ch/software/fastsimcoal/<br /><br />FastSLINK <br />Simulation of Marker and Phenotype Data in Pedigrees <br />http://watson.hgen.pitt.edu/<br /><br />FFPopSim <br />C++/Python library for population genetics. <br />http://webdav.tuebingen.mpg.de/ffpopsim/<br /><br />FLUX SIMULATOR <br />The Flux Simulator aims at providing a deterministic in silico reproduction of the experimental pipelines for RNA-Seq, employing a minimal set of parameters. <br />http://flux.sammeth.net/simulator.html<br /><br />ForSim <br />ForSim: A Forward Evolutionary Computer Simulation <br />http://www.anthro.psu.edu/weiss_lab/research.shtml<br /><br />ForwSim <br />The program given below is based on the algorithm described in Padhukasahasram et al. 2008 to simulate genetic drift in a standard Wright-Fisher process. <br />http://badri-populationgeneticsimulators.blogspot.com/<br /><br />FPG <br />Forward Population Genetic simulation <br />http://genfaculty.rutgers.edu/hey/software#fpg<br /><br />FREGENE <br />FREGENE is a C++ program that simulates sequence-like data over large genomic regions in large diploid populations. <br />http://www.ebi.ac.uk/projects/bargen/download/fregen/documentation_html.html<br /><br />GAMETES <br />Genetic Architecture Model Emulator for Testing and Evaluating Software: Simulates complex SNP models with pure, strict epistatic interactions with n-loci. <br />http://sourceforge.net/projects/gametes/?source=navbar<br /><br />GASP <br />Genometric Analysis Simulation Program. A software tool for testing and investigating methods in statistical genetics by generating samples of family data based on user specified models. <br />http://research.nhgri.nih.gov/gasp/<br /><br />GemSIM <br />Next generation sequencing read simulator <br />http://sourceforge.net/projects/gemsim/<br /><br />GeneArtisan <br />Simulation of Markers in Case-Control Study Designs <br />http://www.rannala.org/?page_id=241<br /><br />GENOME <br />A rapid coalescent-based whole genome simulator <br />http://www.sph.umich.edu/csg/liang/genome/<br /><br />GenomePop2 <br />GenomePop2 is a specialization of the program GenomePop just to manage SNPs under more flexible and useful settings. If you need models with more than 2 alleles please use the GenomePop program version. <br />http://webs.uvigo.es/acraaj/genomepop2.htm<br /><br />GenomeSimla <br />GenomeSIMLA is currently under development- however, we have a beta release that we are asking to be tested <br />http://chgr.mc.vanderbilt.edu/genomesimla/<br /><br />GENS2 <br />Simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. <br />https://sourceforge.net/projects/gensim/<br /><br />GWAsimulator <br />A rapid whole genome simulation program <br />http://biostat.mc.vanderbilt.edu/wiki/main/gwasimulator<br /><br />HAP-SAMPLE <br />An association simulator for candidate regions or genome scans <br />http://www.hapsample.org/<br /><br />HAPGEN <br />A simulator for the simulation of case control datasets at SNP markers <br />https://mathgen.stats.ox.ac.uk/genetics_software/hapgen/hapgen2.html<br /><br />HapSim <br />A simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients <br />http://cran.r-project.org/web/packages/hapsim/index.html<br /><br />HAPSIMU <br />A program that simulates heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model <br />http://l.web.umkc.edu/liujian/<br /><br />IBDsim <br />IBDSim is a computer package for the simulation of genotypic data under general isolation by distance models. <br />http://raphael.leblois.free.fr/<br /><br />indel-Seq-Gen <br />A biological sequence simulation program that simulates highly divergent DNA sequences and protein superfamilies <br />http://bioinfolab.unl.edu/~cstrope/isg/<br /><br />Indelible <br />A powerful and flexible simulator of biological evolution <br />http://abacus.gene.ucl.ac.uk/software/indelible/<br /><br />invertFREGENE <br />InvertFREGENE is a forward-in-time simulator of inversions in population genetic data <br />http://www.ebi.ac.uk/projects/bargen/<br /><br />kernalPop <br />A spatially explicit population genetic simulation engine <br />http://cran.r-project.org/src/contrib/archive/kernelpop/<br /><br />MaCS <br />Markovian Coalescent Simulator <br />http://www-hsc.usc.edu/~garykche/<br /><br />Mason <br />A package for the simulation of nucleotide data. <br />http://www.seqan.de/projects/mason/<br /><br />mbs <br />modifying Hudson's ms software to generate samples of DNA sequences with a biallelic site under selection <br />http://www.sendou.soken.ac.jp/esb/innan/innanlab/software.html<br /><br />Mendel's Accountant <br />Mendel's Accountant (MENDEL) is an advanced numerical simulation program for modeling genetic change over time and was developed collaboratively by Sanford, Baumgardner, Brewer, Gibson and ReMine <br />http://mendelsaccount.sourceforge.net/<br /><br />MetaSim <br />A tool to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets <br />http://ab.inf.uni-tuebingen.de/software/metasim/<br /><br />mlcoalsim <br />Multilocus Coalescent Simulations <br />http://code.google.com/p/mlcoalsim-v1/<br /><br />ms <br />The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br />http://home.uchicago.edu/~rhudson1/source/mksamples.html<br /><br />msHOT <br />The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br />http://home.uchicago.edu/~rhudson1/<br /><br />msms <br />A coalescent Simlation tool with selection. <br />http://www.mabs.at/ewing/msms/index.shtml<br /><br />MySSP <br />A program for the simulation of DNA sequence evolution across a phylogenetic tree <br />http://www.rosenberglab.net/software.php<br /><br />Nemo <br />A forward-time, individual-based, genetically explicit, and stochastic simulation program designed to study the evolution of genetic markers, life history traits, and phenotypic traits in a flexible (meta-)population framework. <br />http://nemo2.sourceforge.net/<br /><br />NetRecodon <br />Coalescent simulation of coding DNA sequences with recombination (inter and intracodon), migration and demography <br />http://code.google.com/p/netrecodon/<br /><br />PEDAGOG <br />Software for simulating eco-evolutionary population dynamics <br />https://bcrc.bio.umass.edu/pedigreesoftware/node/5<br /><br />phenosim <br />A tool to add phenotypes to simulated genotypes <br />http://evoplant.uni-hohenheim.de/doku.php?id=software:software<br /><br />PhyloSim <br />An R package for the Monte Carlo simulation of sequence evolution <br />http://bit.ly/rlsim-git<br /><br />pIRS <br />Profile-based Illumina pair-end reads simulator <br />https://code.google.com/p/pirs/<br /><br />ProteinEvolver <br />Simulation of protein evolution along phylogenies under structure-based substitution models <br />http://code.google.com/p/proteinevolver/<br /><br />QMSim <br />QTL and Marker Simulator <br />http://www.aps.uoguelph.ca/~msargol/qmsim/<br /><br />quantiNEMO <br />An individual-based program for the analysis of quantitative traits with explicit genetic architecture potentially under selection in a structured population <br />http://www2.unil.ch/popgen/softwares/quantinemo/<br /><br />RECOAL <br />Simulates new haplotype data from a reference population of haplotypes. <br />ftp://popgen.usc.edu/<br /><br />Recodon <br />Coalescent simulation of coding DNA sequences with recombination, migration and demography <br />http://code.google.com/p/recodon/<br /><br />rlsim <br />A package for simulating RNA-seq library preparation with parameter estimation <br />http://bit.ly/rlsim-git<br /><br />Rmetasim <br />Rmetasim is a front-end for the metasim engine that is implemented as a package that runs in the statistical computing environment R <br />http://linum.cofc.edu/software.html#metasim<br /><br />RNA Seq Simulator <br />RSS takes SAM alignment files from RNA-Seq data and simulates over dispersed, multiple replica, differential, non-stranded RNA-Seq datasets. <br />http://useq.sourceforge.net/cmdlnmenus.html#rnaseqsimulator<br /><br />Rose <br />Random model of sequence evolution <br />http://bibiserv.techfak.uni-bielefeld.de/rose/<br /><br />SelSim <br />SelSim is a program for Monte Carlo simulation of DNA polymorphism data for a recom- bining region within which a single bi-allelic site has experienced natural selection <br />http://www.well.ox.ac.uk/~spencer/selsim/<br /><br />Seq-Gen <br />An application for the Monte Carlo simulation of molecular sequence evolution along phylogenetic trees. <br />http://tree.bio.ed.ac.uk/software/seqgen/<br /><br />SEQPower <br />Statistical power analysis for sequence-based association studies <br />http://bioinformatics.org/spower/<br /><br />SeqSIMLA <br />SeqSIMLA can simulate sequence data with user-specified disease and quantitative trait models. Family or unrelated case-control data can be simulated. <br />http://seqsimla.sourceforge.net/<br /><br />Serial NetEvolve <br />A flexible utility for generating serially-sampled sequences along a tree or recombinant network <br />http://biorg.cis.fiu.edu/sne/<br /><br />SFS_CODE <br />SFS_CODE can perform forward population genetic simulations under a general Wright-Fisher model with arbitrary migration, demographic, selective, and mutational effects. <br />http://sfscode.sourceforge.net/sfs_code/index/index.html<br /><br />SIBSIM <br />Quantitative phenotype simulation in extended pedigrees <br />http://sourceforge.net/projects/sibsim/<br /><br />SIMCOAL2 <br />A coalescent program for the simulation of complex recombination patterns over large genomic regions under various demographic models <br />http://cmpg.unibe.ch/software/simcoal2/<br /><br />SimCopy <br />An R package simulating the evolution of copy number profiles along a tree. <br />http://bit.ly/simcopy<br /><br />SIMLA <br />SIMLA is a SIMuLAtion program that generates data sets of families for use in Linkage and Association studies. <br />http://www.chg.duke.edu/research/simla.html<br /><br />SimPed <br />A Simulation Program to Generate Haplotype and Genotype Data for Pedigree Structures <br />http://www.hgsc.bcm.tmc.edu/content/simped<br /><br />Simprot <br />A program to simulate protein evolution by substitution, insertion and deletion <br />http://www.uhnresearch.ca/labs/tillier/software.htm#3<br /><br />SimRare <br />Rare variant simulation and analysis tool <br />http://code.google.com/p/simrare/<br /><br />simuGWAS <br />A forward-time simulator that simulates realistic samples for genome-wide association studies. <br />http://simupop.sourceforge.net/cookbook/simucomplexdisease<br /><br />simuPOP <br />simuPOP is a general-purpose individual-based forward-time population genetics simulation environment. <br />http://simupop.sourceforge.net/<br /><br />SISSI <br />A software tool to generate data of related sequences along a given phylogeny, taking into account user defined system of neighbourhoods and instantaneous rate matrices. <br />http://www.cibiv.at/software/sissi/<br /><br />SNPsim <br />Coalescent simulation of hotspot recombination <br />http://code.google.com/p/phylosoftware/<br /><br />SPIP <br />SPIP simulates the transmission of genes from parents to offspring in a population having demographic structure defined by the user <br />http://swfsc.noaa.gov/textblock.aspx?division=fed&amp;id=3434<br /><br />Splatche <br />Spatial and Temporal Coalescences in Heterogeneous Environment <br />http://www.splatche.com/<br /><br />srv <br />Simulator of Rare Varaints (srv) is a simulator for the simulation of the introduction and evolution of (rare) genetic variants. <br />http://simupop.sourceforge.net/cookbook/simurarevariants<br /><br />SUP <br />SLINK/FastSLINK utility program <br />http://mlemire.freeshell.org/software.html<br /><br />TreesimJ <br />A flexible, forward-time population genetic simulator <br />http://code.google.com/p/treesimj/<br /><br />Vortex <br />VORTEX is an individual-based simulation model for population viability analysis (PVA). <br />http://www.vortex9.org/vortex.html<br /><br />References:</p><p>Image www.evolution-of-life.com</p><p>www.cancer.gov</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40882/troyanskaya-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:40:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.</p>

<p>https://function.princeton.edu/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8520/rcb-gurgaon-bioinformatics-rapa-openings</guid>
  <pubDate>Thu, 27 Feb 2014 08:42:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[RCB Gurgaon Bioinformatics RA/PA Openings]]></title>
  <description><![CDATA[
<p>Advt. No.1/2014</p>

<p>Recruitment for Research Associate and Project Assistant positions</p>

<p>Regional Centre for Biotechnology (RCB) is an autonomous academic institution established by the Department of Biotechnology, Govt. of India with regional and global partnerships synergizing with the programmes of UNESCO as a Category II Centre. The primary focus of RCB is to provide world class education, training and conduct innovative research at the interface of multiple disciplines to create high quality human resource in disciplinary and interdisciplinary areas of biotechnology in a globally competitive research milieu. </p>

<p>Research Associate (02 Position)</p>

<p>Consolidated emoluments Rs.22000/- + 30% H.R.A. p.m.</p>

<p>Essential: Ph.D. in Natural Sciences, minimum 60% marks in all qualifying exams and below 35 years of age.</p>

<p>Desirable: Prior experience at the PhD level in Biochemistry, Bioinformatics and Proteomics with a strong motivation for a career in research is highly desirable.</p>

<p>Strong PhD level training with proteins chemistry, protein purification and statistical analysis of proteomics or genomics dataset will be preferred. Either/ both qualifications should be substantiated by published papers.</p>

<p>Inter-Institutional Program for  Maternal, Neonatal and Infant  Sciences: A translational approach to studying preterm birth. </p>

<p>Principal Investigator: Dr. Dinakar M. Salunke </p>

<p>Applicants may apply along with the requisite documents (attested copies) pertaining to proof of date of birth, academic/professional qualifications, experience (if any), in the prescribed format available on our websites: www.rcb.res.in and www.rcb.ac.in. Applications should be sent to the Registrar, Regional Centre for Biotechnology, 180 Udyog Vihar Phase 1, Gurgaon-122016, Haryana, India, through Registered Post on or before Feb 28, 2014. A soft copy of the application should be sent by email to registrar@rcb.res.in. Incomplete applications or applications received after Feb 28, 2014 will not be entertained. </p>

<p>More at https://www.rcb.res.in/Advt-1._for_websites_PTB-revised.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41394/ngsymposium-in-computational-biology</guid>
  <pubDate>Mon, 09 Mar 2020 06:00:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[NGSymposium in Computational Biology]]></title>
  <description><![CDATA[
<p>We have a great pleasure to invite you to the NGSymposium in Computational Biology to celebrate the 5th anniversary of the NGSchool Summer Schools. This international conference will make way for exchanging knowledge and experiences between experienced and early-stage researchers as well as bioinformaticians. The meeting will be held on 31.07 - 1.08.2020 in Warsaw. It will be a satellite event to the #NGSchool2020: Statistical Learning in Genomics. It will cover a wide range of topics from basic and applied biomedical sciences: bioinformatics, genomics, transcriptomics, computational biology, Machine Learning.</p>

<p>Registration of active participants will be open from February, 27 12 PM CET to April 17, 23:59 CET. In registration forms you will be asked for providing us with some basic information about yourself. You will also be able to submit your abstract. You can save your registration form after filling it partially and come back later to supply more data e.g. upload an abstract. Your registration will be completed only with the payment of the registration fee reaching our accounts - please make sure to transfer the money in advance!</p>

<p>Registration of passive participants will be open after closing of registration of active participants.</p>

<p>Details an registration: https://ngschool.eu/conference/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</guid>
	<pubDate>Tue, 27 Oct 2020 19:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</link>
	<title><![CDATA[Frequent parameters for bioinformatics tools !]]></title>
	<description><![CDATA[<div><div>Third party executable parameters and options.</div><div>&nbsp;</div><div>Trimmomatic</div><div>&nbsp;</div><div>&ldquo;ILLUMINACLIP:...:2:30:10&rdquo;</div><div>&ldquo;LEADING:15&rdquo;</div><div>&ldquo;TRAILING:15&rdquo;</div><div>&ldquo;SLIDINGWINDOW:4:20&rdquo;</div><div>&ldquo;MINLEN:20&rdquo;</div><div>&ldquo;TOPHRED33&rdquo;</div><div>&nbsp;</div><div>Filtlong</div><div>--min_length 500</div><div>--min_mean_q 85</div><div>--min_window_q 65</div><div>&nbsp;</div><div>FastQ Screen</div><div>--aligner bowtie2' (bwa for PacBio)</div><div>--subset 1000 (for PacBio)</div><div>&nbsp;</div><div>SPAdes</div><div>--careful</div><div>--disable-gzip-output</div><div>--cov-cutoff auto</div><div>--phred-offset 33</div><div>&nbsp;</div><div>HGAP</div><div>Pbalign.task_options.min_accuracy: 70</div><div>Pbalign.task_options.no_split_subreads: false</div><div>Genomic_consensus.task_options.min_confidence: 40</div><div>falcon_ns.task_options.HGAP_GenomeLength_str:</div><div>6000000</div><div>Pbcoretools.task_options.read_length: 0</div><div>Genomic_consensus.task_options.use_score: 0</div><div>Pbalign.task_options.min_length: 50</div><div>Pbalign.task_options.algorithm_options: --minMatch 12</div><div>--bestn 10 --minPctSimilarity 70.0</div><div>Pbalign.task_options.hit_policy: randombest</div><div>Pbcoretools.task_options.other_filters: rq &gt;= 0.7</div><div>Pbalign.task_options.concordant: false</div><div>Genomic_consensus.task_options.min_coverage: 5</div><div>falcon_ns.task_options.HGAP_SeedCoverage_str: 30</div><div>falcon_ns.task_options.HGAP_AggressiveAsm_bool: false</div><div>Genomic_consensus.task_options.algorithm: best</div><div>falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1</div><div>Genomic_consensus.task_options.diploid: false</div><div>&nbsp;</div><div>MeDuSa</div><div>-random 100</div><div>&nbsp;</div><div>Prokka</div><div>--usegenus</div><div>--force</div><div>--addgenes</div><div>--rfam</div><div>--rawproduct</div><div>&nbsp;</div><div>cmsearch (taxonomy, 16S)</div><div>--rfam</div><div>--noali</div><div>&nbsp;</div><div>blastn (taxonomy, 16S)</div><div>-evalue 1E-10</div><div>&nbsp;</div><div>blastn (MLST)</div><div>-ungapped</div></div><div><div>-dust no</div><div>-evalue 1E-20</div><div>-word_size 32</div><div>-culling_limit 2</div><div>-perc_identity 95</div><div>&nbsp;</div><div>blastp (VF)</div><div>-culling_limit 2</div><div>&nbsp;</div><div>RGI (ABR)</div><div>--input_type contig</div><div>&nbsp;</div><div>bowtie2 (mapping)</div><div>--sensitive</div><div>&nbsp;</div><div>minimap2 (mapping)</div><div>-a</div><div>-x map-ont</div><div>&nbsp;</div><div>samtools mpileup (SNP&nbsp;detection)</div><div>-uRI</div><div>&nbsp;</div><div>bcftools call (SNP detection)</div><div>--variants-only</div><div>--skip-variants indels</div><div>--output-type v</div><div>--ploidy 1</div><div>-c</div><div>&nbsp;</div><div>SNPsift filter (SNP detection)</div><div>"( QUAL &gt;= 30 ) &amp; (( na FILTER ) | (FILTER = 'PASS')) &amp;</div><div>( DP &gt;= 20 ) &amp; ( MQ &gt;= 20 )"</div><div>&nbsp;</div><div>SNPeff ann (SNP detection)</div><div>-nodownload</div><div>-no-intron</div><div>-no-downstream</div><div>-no SPLICE_SITE_REGION</div><div>-upDownStreamLen 250</div><div>&nbsp;</div><div>bcftools consensus</div><div>(phylogenetic tree)</div><div>--haplotype 1</div><div>&nbsp;</div><div>fasttreemp</div><div>-nt</div><div>-boot 100</div><div>&nbsp;</div><div>roary</div><div>-e</div><div>-n</div><div>-cd 100</div><div>-g 100000</div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8857/junior-research-fellow-at-iari</guid>
  <pubDate>Mon, 10 Mar 2014 13:10:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[Junior Research Fellow at IARI]]></title>
  <description><![CDATA[
<p>DIVISION OF NEMATOLOGY<br />INDIAN AGRICULTURAL RESEARCH INSTITUTE<br />NEW DELHI 110012</p>

<p>Applications are invited for the posts of one Junior Research Fellow in the DBT funded project entitled “Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.</p>

<p>Essential qualifications for JRF: First class M. Sc. / M. Tech in Bioinformatics. Knowledge of programming language, pearl, Statistics and database – HTML, CSS, Java script.</p>

<p>Desirable qualifications: Experience in handling next generation sequencing data</p>

<p>Age limit: 35 years maximum (5 year relaxation for SC/ST and women candidates) Emoluments: 16,000 + 30% HRA.</p>

<p>The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.</p>

<p>Those who are interested in pursuing Ph.D with strong research aptitude are preferred.</p>

<p>Interested candidates may attend the Walk in interview on 25th March 2014 along with the duly filled application forms (format in the following page) with all the relevant documents.</p>

<p>Venue: Division of Nematology, Indian Agricultural Research Institute, New Delhi 110012 (Room No. 306, 3rd floor, LBS building)</p>

<p>Reporting Time: Interested candidates should report strictly between 10.00 to 10.30 AM.</p>

<p>Interview time: 10.30 AM</p>

<p>Short-listed candidates will be called for interview at New Delhi. However, no TA and DA will be paid for attending the interview.</p>

<p>Advertisement:</p>

<p>https://www.iari.res.in/files/JRF_Nema-07032014-20140307-170017.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42664/common-bioinformatics-interview-questions</guid>
	<pubDate>Sat, 23 Jan 2021 06:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42664/common-bioinformatics-interview-questions</link>
	<title><![CDATA[Common Bioinformatics Interview Questions !]]></title>
	<description><![CDATA[<p>The possibility of an interview for a bioinformatics position in the life sciences may be very disquieting, but the same concerns emerge time and again in my experience. So, it is exceedingly worthwhile to plan for future bioinformatics interview questions. Doing this will really give you the advantage in obtaining the position.</p><p>The following 5 questions are those that I have heard many times during the job-search process. There is no reason for not planning responses in such situations.</p><p><strong>1. Tell Us About Yourself</strong><br />This is a very typical opener in interviews. It's a perfect question to ask, and getting something planned will really help you concentrate and ease in the conversation. However, you need to make sure that your response is applicable to the job you're interviewing.<br />It's probably better to keep your answer professional. Try to include these in the answer as well: where did your love of science and bioinformatics come from? How the heck did you end up in this field? Why programming and scripting ?</p><p><strong>2. What is your plan for your bioinformatics career? / How do you look at yourself in five years? / How are your personal objectives to accomplish these goals / What are the plan for your research fundings ?</strong></p><p>Your CV/resume has already impressed the selection panel if you have been invited for an interview. The questions from the bioinformatics interview team provide an incentive for you to market yourself and illustrate the work in question with the most appropriate knowledge.</p><p><strong>3. What do you understand about the job description/What would your suggested research path be if you were a successful candidate?</strong><br />Summarize the specifics of the advertised bioinformatics position in your own words. Follow on with some suggestions of how you want to extend your research and create your own projects within the community.</p><p><strong>4. Will you work as a group or do you want to work on your own?</strong><br />This requirement can vary from jobs to job, so when addressing, be alert. A company/research PI may need a bioinformatician that is able to work on a single project autonomously, or they may need a person who can help direct and organize a team. In your response, refer to the job description.</p><p><strong>5. What particular methods have you used to date with your experiments?</strong><br />You might have experience with all the laboratory techniques described in the job description, but stress the ones you highly experienced with. Highlight your professional abilities and stress that you are extremely capable of mastering new techniques with others ...</p><p>At the end of the day, remember that you're questioning the jury as well as they're interviewing you. You will ought to think of any questions you would like the interview panel to pose. This indicates that you have done your homework and serious about the position.</p><p>All the best for your future job interview.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8972/bioinformaticcomputational-postdoc-at-south-dakota-state-university</guid>
  <pubDate>Wed, 12 Mar 2014 10:02:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatic/computational postdoc at South Dakota State University]]></title>
  <description><![CDATA[
<p>We seek an enthusiastic postdoctoral researcher to work with the Plant Science team within the Biochemical Spatio-temporal NeTwork Resource (BioSNTR). Bio-SNTR</p>

<p>is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.<br />Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.</p>

<p> <br />Required Qualifications:<br />• Ph.D. in plant computational biology or bioinformatics.<br />• Experience in a high performance computing environment.<br />• Perl, Python and Java programming experience<br />• Data management and database development experience</p>

<p>Desired Qualifications:<br />• Parallel computing experience<br />• Experience working in a multidisciplinary environment</p>

<p>Contact Information<br />South Dakota State University<br />Plant Science<br />Anne Fennell<br />anne.fennell@sdstate.edu<br />Tel. Number: 605-688-6373<br />http://www.biosntr.org</p>
]]></description>
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