Relevant bibliographies by topics / Salmonella ; Next-generation sequencing ; Bioinformatics

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Salmonella ; Next-generation sequencing ; Bioinformatics'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Salmonella ; Next-generation sequencing ; Bioinformatics"

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Krejčí, Adam, Petr Müller, and Bořivoj Vojtěšek. "Bioinformatics and Next- generation Sequencing." Klinicka onkologie 28, Suppl 2 (2015): 2S91–2S96. http://dx.doi.org/10.14735/amko20152s91.

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Kim, Ki-Bong. "Next Generation Sequencing and Bioinformatics." Journal of Life Science 25, no. 3 (2015): 357–67. http://dx.doi.org/10.5352/jls.2015.25.3.357.

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Olawoye, Idowu B., Simon D. W. Frost, and Christian T. Happi. "The Bacteria Genome Pipeline (BAGEP): an automated, scalable workflow for bacteria genomes with Snakemake." PeerJ 8 (October 27, 2020): e10121. http://dx.doi.org/10.7717/peerj.10121.

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Next generation sequencing technologies are becoming more accessible and affordable over the years, with entire genome sequences of several pathogens being deciphered in few hours. However, there is the need to analyze multiple genomes within a short time, in order to provide critical information about a pathogen of interest such as drug resistance, mutations and genetic relationship of isolates in an outbreak setting. Many pipelines that currently do this are stand-alone workflows and require huge computational requirements to analyze multiple genomes. We present an automated and scalable pip
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Magi, Alberto, Matteo Benelli, Alessia Gozzini, Francesca Girolami, Francesca Torricelli, and Maria Luisa Brandi. "Bioinformatics for Next Generation Sequencing Data." Genes 1, no. 2 (2010): 294–307. http://dx.doi.org/10.3390/genes1020294.

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Oliver, Gavin R., Steven N. Hart, and Eric W. Klee. "Bioinformatics for Clinical Next Generation Sequencing." Clinical Chemistry 61, no. 1 (2015): 124–35. http://dx.doi.org/10.1373/clinchem.2014.224360.

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Abstract BACKGROUND Next generation sequencing (NGS)-based assays continue to redefine the field of genetic testing. Owing to the complexity of the data, bioinformatics has become a necessary component in any laboratory implementing a clinical NGS test. CONTENT The computational components of an NGS-based work flow can be conceptualized as primary, secondary, and tertiary analytics. Each of these components addresses a necessary step in the transformation of raw data into clinically actionable knowledge. Understanding the basic concepts of these analysis steps is important in assessing and add
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Jiwan, A., and S. Singh. "Next Generation Sequencing an Emerging Bioinformatics Field." International Journal of Computer Sciences and Engineering 5, no. 12 (2017): 130–34. http://dx.doi.org/10.26438/ijcse/v5i12.130134.

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Scholtalbers, J., J. Rossler, P. Sorn, et al. "Galaxy LIMS for next-generation sequencing." Bioinformatics 29, no. 9 (2013): 1233–34. http://dx.doi.org/10.1093/bioinformatics/btt115.

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Yohe, Sophia, and Bharat Thyagarajan. "Review of Clinical Next-Generation Sequencing." Archives of Pathology & Laboratory Medicine 141, no. 11 (2017): 1544–57. http://dx.doi.org/10.5858/arpa.2016-0501-ra.

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Context.— Next-generation sequencing (NGS) is a technology being used by many laboratories to test for inherited disorders and tumor mutations. This technology is new for many practicing pathologists, who may not be familiar with the uses, methodology, and limitations of NGS. Objective.— To familiarize pathologists with several aspects of NGS, including current and expanding uses; methodology including wet bench aspects, bioinformatics, and interpretation; validation and proficiency; limitations; and issues related to the integration of NGS data into patient care. Data Sources.— The review is
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Huang, Weichun, Leping Li, Jason R. Myers, and Gabor T. Marth. "ART: a next-generation sequencing read simulator." Bioinformatics 28, no. 4 (2011): 593–94. http://dx.doi.org/10.1093/bioinformatics/btr708.

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García-Alcalde, Fernando, Konstantin Okonechnikov, José Carbonell, et al. "Qualimap: evaluating next-generation sequencing alignment data." Bioinformatics 28, no. 20 (2012): 2678–79. http://dx.doi.org/10.1093/bioinformatics/bts503.

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Dissertations / Theses on the topic "Salmonella ; Next-generation sequencing ; Bioinformatics"

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Richardson, Emily Jane. "Next-generation bioinformatics analysis of bacterial genomes, with a focus on serovar host specificity and pathogenicity in Salmonella." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8793.

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Salmonella is one of the most important pathogens of mankind and animals alike, causing several billion pounds worth of damage worldwide each year. We have sequenced, annotated and published 4 genomes of Salmonella of well-defined virulence in farm animals. This provides valuable measures of intraserovar diversity and opportunities to formally link genotypes to phenotypes in target animals. Specifically, we have examined pathway detrition and mutagenesis and linked this to host specificity of the serovars. With the advent of next generation sequencing there has been a boom in genomic sequence
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Odelgard, Anna. "Coverage Analysis in Clinical Next-Generation Sequencing." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-379228.

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With the new way of sequencing by NGS new tools had to be developed to be able to work with new data formats and to handle the larger data sizes compared to the previous techniques but also to check the accuracy of the data. Coverage analysis is one important quality control for NGS data, the coverage indicates how many times each base pair has been sequenced and thus how trustworthy each base call is. For clinical purposes every base of interest must be quality controlled as one wrong base call could affect the patient negatively. The softwares used for coverage analysis with enough accuracy
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Yu, Xiaoqing. "Statistical Methods and Analyses for Next-generation Sequencing Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1403708200.

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Pyon, Yoon Soo. "Variant Detection Using Next Generation Sequencing Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1347053645.

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Quinlan, Aaron Ryan. "Discovery and interpretation of genetic variation with next‐generation sequencing technologies." Thesis, Boston College, 2008. http://hdl.handle.net/2345/32.

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Thesis advisor: Gabor T. Marth<br>Improvements in molecular and computational technologies have driven and will continue to drive advances in our understanding of genetic variation and its relationship to phenotypic diversity. Over the last three years, several new DNA sequencing technologies have been developed that greatly improve upon the cost and throughput of the capillary DNA sequencing technologies that were used to sequence the first human genome. The economy of these so‐called “next‐generation” technologies has enabled researchers to conduct genome‐wide studies in genetic variation th
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Fedewa, Gregory. "Quantifying Nucleotide Variation in RNA Virus Populations by Next-generation Sequencing." Thesis, University of California, San Francisco, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10936274.

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<p> RNA viruses include several notable human pathogens including HIV, hepatitis C virus, West Nile virus, influenza, and Ebola virus. This group of viruses includes viruses with incredibly diverse genome structures, such as single-stranded genomes, double-stranded genomes, multipart genomes, negative-stranded genomes, and positive-stranded genomes. They also exist as heterogeneous populations that can mutate and rapidly evolve due to their error-prone polymerases. These errors then accumulate as they are passed down through generation. They can, therefore, be used as a historical marker for g
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Huang, Liren [Verfasser]. "Cloud-based Bioinformatics Framework for Next-Generation Sequencing Data / Liren Huang." Bielefeld : Universitätsbibliothek Bielefeld, 2019. http://d-nb.info/1196644020/34.

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Kislyuk, Andrey O. "Algorithm development for next generation sequencing-based metagenome analysis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/42779.

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We present research on the design, development and application of algorithms for DNA sequence analysis, with a focus on environmental DNA (metagenomes). We present an overview and primer on algorithm development for bioinformatics of metagenomes; work on frameshift detection in DNA sequencing data; work on a computational pipeline for the assembly, feature prediction, annotation and analysis of bacterial genomes; work on unsupervised phylogenetic clustering of metagenomic fragments using Markov Chain Monte Carlo methods; and work on estimation of bacterial genome plasticity and diversity, pote
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Ramsay, Trevor. "A Motif Discovery and Analysis Pipeline for Heterogeneous Next-Generation Sequencing Data." Thesis, University of California, Davis, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1599520.

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<p> Bioinformatics has made great strides in understanding the regulation of gene expression, but many of the tools developed for this purpose depend on data from a limited number of species. Despite their unique genetic attributes, there remains a dearth of research into undomesticated trees. The poplar tree, <i> Populus trichocarpa</i>, has undergone multiple rounds of genome duplication during its evolution. In addition its life cycle varies from other annual crop and model plants previously studied, leading to significant technical challenges to understand the unique biology of these trees
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Khuder, Basil. "Human Genome and Transcriptome Analysis with Next-Generation Sequencing." University of Toledo Health Science Campus / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=mco1501886695490104.

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Books on the topic "Salmonella ; Next-generation sequencing ; Bioinformatics"

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Next-generation DNA sequencing informatics. Cold Spring Harbor Laboratory, 2013.

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Next-generation Sequencing and Bioinformatics for Plant Science. Caister Academic Press, 2017. http://dx.doi.org/10.21775/9781910190654.

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Next-generation sequencing : current technologies and applications. Caister Academic Press, 2014.

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Next-Generation DNA Sequencing Informatics. Cold Spring Harbor Laboratory Press, 2015.

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Next generation sequencing technologies and challenges in sequence assembly. Springer, 2014.

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Low, Lloyd Wai Yee, and Martti Tapani Tammi. Bioinformatics: A Practical Handbook of Next Generation Sequencing and Its Applications. World Scientific Publishing Co Pte Ltd, 2017.

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Book chapters on the topic "Salmonella ; Next-generation sequencing ; Bioinformatics"

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Prasad, Anchita, Harshita Bhargava, Ayam Gupta, et al. "Next Generation Sequencing." In Advances in Bioinformatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6191-1_14.

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De Filippis, L. F. "Plant Bioinformatics: Next Generation Sequencing Approaches." In Plant Bioinformatics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67156-7_1.

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Kawabata-Iwakawa, Reika, Hidemasa Bono, and Masahiko Nishiyama. "Next-Generation Sequencing and Bioinformatics." In Molecular Targeted Therapy of Lung Cancer. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2002-5_6.

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Ramsköld, Daniel, Ersen Kavak, and Rickard Sandberg. "How to Analyze Gene Expression Using RNA-Sequencing Data." In Next Generation Microarray Bioinformatics. Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-400-1_17.

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Gogol-Döring, Andreas, and Wei Chen. "An Overview of the Analysis of Next Generation Sequencing Data." In Next Generation Microarray Bioinformatics. Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-400-1_16.

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Zeng, Qifan, Luyang Sun, Qiang Fu, Shikai Liu, and Zhanjiang Liu. "SNP Identification from Next-Generation Sequencing Datasets." In Bioinformatics in Aquaculture. John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781118782392.ch17.

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Singh, Satendra, Anjali Rao, Pallavi Mishra, et al. "Bioinformatics in Next-Generation Genome Sequencing." In Current trends in Bioinformatics: An Insight. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7483-7_2.

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Bansal, Gourja, Kiran Narta, and Manoj Ramesh Teltumbade. "Next-Generation Sequencing: Technology, Advancements, and Applications." In Bioinformatics: Sequences, Structures, Phylogeny. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1562-6_2.

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Hu, Yue, Wenjun Lan, and Daniel Miller. "Next-Generation Sequencing for MicroRNA Expression Profile." In Bioinformatics in MicroRNA Research. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7046-9_12.

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Duan, Junbo, Xiaoying Fu, Jigang Zhang, Yu-Ping Wang, and Hong-Wen Deng. "The Next Generation Sequencing and Applications in Clinical Research." In Translational Bioinformatics. Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-017-7543-4_4.

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Conference papers on the topic "Salmonella ; Next-generation sequencing ; Bioinformatics"

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Wan, Raymond, and Kiyoshi Asai. "Sorting next generation sequencing data improves compression effectiveness." In 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2010. http://dx.doi.org/10.1109/bibmw.2010.5703863.

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Shifu Chen, Yue Han, Lanting Guo, Jingjing Hu, and Jia Gu. "SeqMaker: A next generation sequencing simulator with variations, sequencing errors and amplification bias integrated." In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2016. http://dx.doi.org/10.1109/bibm.2016.7822634.

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Hua, Guan-Jie, Chuan Yi Tang, Che-Lun Hung, and Huiru Zheng. "Drug resistance gene identification algorithm for next-generation sequencing data." In 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2014. http://dx.doi.org/10.1109/bibm.2014.6999381.

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Dharanipragada, Prashanthi, and Nita Parekh. "Copy number variation detection workflow using next generation sequencing data." In 2016 International Conference on Bioinformatics and Systems Biology (BSB). IEEE, 2016. http://dx.doi.org/10.1109/bsb.2016.7552117.

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Ulz, Peter, Michael R. Speicher, and Gerhard G. Thallinger. "Reconstruction of Mitochondrial Genotypes from Diverse next Generation Sequencing Datasets." In 8th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006110200290036.

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Astrinaki, Maria, Alexandros Kanterakis, Helen Latsoudis, George Potamias, and Dimitris Kafetzopoulos. "Zazz: Variant Annotation and Exploration of Next Generation Sequencing Variants." In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2019. http://dx.doi.org/10.1109/bibe.2019.00159.

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Okomo-Adhiambo, Margaret, Edward Ramos, Reagan Kelly, et al. "Automated Next Generation Sequencing Bioinformatics Pipelines for Pathogen Discovery and Surveillance." In BCB '17: 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM, 2017. http://dx.doi.org/10.1145/3107411.3108192.

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Kchouk, Mehdi, and Mourad Elloumi. "A clustering approach for denovo assembly using Next Generation Sequencing data." In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2016. http://dx.doi.org/10.1109/bibm.2016.7822812.

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Srimani, Jaydeep K., Po-Yen Wu, John H. Phan, and May D. Wang. "A distributed system for fast alignment of next-generation sequencing data." In 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2010. http://dx.doi.org/10.1109/bibmw.2010.5703865.

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Kathiresan, Nagarajan, Rashid Al-Ali, Puthen V. Jithesh, Tariq AbuZaid, Ramzi Temanni, and Andrey Ptitsyn. "Optimization of data-intensive next generation sequencing in high performance computing." In 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2015. http://dx.doi.org/10.1109/bibe.2015.7367654.

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