Relevant bibliographies by topics / DNA - Data processing

Contents

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

Academic literature on the topic 'DNA - Data processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "DNA - Data processing"

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Belov, D. A., Yu V. Belov, and V. V. Manoylov. "DNA MELTING DATA PROCESSING TECHNIQUES DEVELOPMENT." NAUCHNOE PRIBOROSTROENIE 27, no. 1 (February 28, 2017): 83–89. http://dx.doi.org/10.18358/np-27-1-i8389.

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Wendl, M. C., I. Korf, A. T. Chinwalla, and L. W. Hillier. "Automated processing of raw DNA sequence data." IEEE Engineering in Medicine and Biology Magazine 20, no. 4 (2001): 41–48. http://dx.doi.org/10.1109/51.940044.

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Ghoneimy, Samy, and Samir Abou El-Seoud. "A MapReduce Framework for DNA Sequencing Data Processing." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 4, no. 4 (December 30, 2016): 11. http://dx.doi.org/10.3991/ijes.v4i4.6537.

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<p class="Els-1storder-head">Genomics and Next Generation Sequencers (NGS) like Illumina Hiseq produce data in the order of ‎‎200 billion base pairs in a single one-week run for a 60x human genome coverage, which ‎requires modern high-throughput experimental technologies that can ‎only be tackled with high performance computing (HPC) and specialized software algorithms called ‎‎“short read aligners”. This paper focuses on the implementation of the DNA sequencing as a set of MapReduce programs that will accept a DNA data set as a FASTQ file and finally generate a VCF (variant call format) file, which has variants for a given DNA data set. In this paper MapReduce/Hadoop along with Burrows-Wheeler Aligner (BWA), Sequence Alignment/Map (SAM) ‎tools, are fully utilized to provide various utilities for manipulating alignments, including sorting, merging, indexing, ‎and generating alignments. The Map-Sort-Reduce process is designed to be suited for a Hadoop framework in ‎which each cluster is a traditional N-node Hadoop cluster to utilize all of the Hadoop features like HDFS, program ‎management and fault tolerance. The Map step performs multiple instances of the short read alignment algorithm ‎‎(BoWTie) that run in parallel in Hadoop. The ordered list of the sequence reads are used as input tuples and the ‎output tuples are the alignments of the short reads. In the Reduce step many parallel instances of the Short ‎Oligonucleotide Analysis Package for SNP (SOAPsnp) algorithm run in the cluster. Input tuples are sorted ‎alignments for a partition and the output tuples are SNP calls. Results are stored via HDFS, and then archived in ‎SOAPsnp format. ‎ The proposed framework enables extremely fast discovering somatic mutations, inferring population genetical ‎parameters, and performing association tests directly based on sequencing data without explicit genotyping or ‎linkage-based imputation. It also demonstrate that this method achieves comparable accuracy to alternative ‎methods for sequencing data processing.‎‎</p><p class="Abstract"><em></em><em><br /></em></p>
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Bei barth, T., K. Fellenberg, B. Brors, R. Arribas-Prat, J. M. Boer, N. C. Hauser, M. Scheideler, et al. "Processing and quality control of DNA array hybridization data." Bioinformatics 16, no. 11 (November 1, 2000): 1014–22. http://dx.doi.org/10.1093/bioinformatics/16.11.1014.

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Mendizabal-Ruiz, Gerardo, Israel Román-Godínez, Sulema Torres-Ramos, Ricardo A. Salido-Ruiz, Hugo Vélez-Pérez, and J. Alejandro Morales. "Genomic signal processing for DNA sequence clustering." PeerJ 6 (January 24, 2018): e4264. http://dx.doi.org/10.7717/peerj.4264.

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Genomic signal processing (GSP) methods which convert DNA data to numerical values have recently been proposed, which would offer the opportunity of employing existing digital signal processing methods for genomic data. One of the most used methods for exploring data is cluster analysis which refers to the unsupervised classification of patterns in data. In this paper, we propose a novel approach for performing cluster analysis of DNA sequences that is based on the use of GSP methods and the K-means algorithm. We also propose a visualization method that facilitates the easy inspection and analysis of the results and possible hidden behaviors. Our results support the feasibility of employing the proposed method to find and easily visualize interesting features of sets of DNA data.
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WANG, Ting-Zhang, Gao SHAN, Jian-Hong XU, and Qing-Zhong XUE. "Genome-scale sequence data processing and epigenetic analysis of DNA methylation." Hereditas (Beijing) 35, no. 6 (September 29, 2013): 685–94. http://dx.doi.org/10.3724/sp.j.1005.2013.00685.

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Wilhelm-Benartzi, C. S., D. C. Koestler, M. R. Karagas, J. M. Flanagan, B. C. Christensen, K. T. Kelsey, C. J. Marsit, E. A. Houseman, and R. Brown. "Review of processing and analysis methods for DNA methylation array data." British Journal of Cancer 109, no. 6 (August 27, 2013): 1394–402. http://dx.doi.org/10.1038/bjc.2013.496.

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Merkel, Angelika, Marcos Fernández-Callejo, Eloi Casals, Santiago Marco-Sola, Ronald Schuyler, Ivo G. Gut, and Simon C. Heath. "gemBS: high throughput processing for DNA methylation data from bisulfite sequencing." Bioinformatics 35, no. 5 (August 21, 2018): 737–42. http://dx.doi.org/10.1093/bioinformatics/bty690.

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Nersisyan, Stepan, Maxim Shkurnikov, Andrey Poloznikov, Andrey Turchinovich, Barbara Burwinkel, Nikita Anisimov, and Alexander Tonevitsky. "A Post-Processing Algorithm for miRNA Microarray Data." International Journal of Molecular Sciences 21, no. 4 (February 12, 2020): 1228. http://dx.doi.org/10.3390/ijms21041228.

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One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison.
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Hutchinson, Franklin. "Use of data from bacteria to interpret data on DNA damage processing in mammalian cells." Mutation Research/Reviews in Genetic Toxicology 220, no. 2-3 (March 1989): 269–78. http://dx.doi.org/10.1016/0165-1110(89)90031-6.

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Dissertations / Theses on the topic "DNA - Data processing"

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高銘謙 and Ming-him Ko. "A multi-agent model for DNA analysis." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31222778.

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Camerlengo, Terry Luke. "Techniques for Storing and Processing Next-Generation DNA Sequencing Data." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1388502159.

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Huang, Songbo, and 黄颂博. "Detection of splice junctions and gene fusions via short read alignment." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B45862527.

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Leung, Chi-ming, and 梁志銘. "Motif discovery for DNA sequences." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B3859755X.

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Oelofse, Andries Johannes. "Development of a MAIME-compliant microarray data management system for functional genomics data integration." Pretoria : [s.n.], 2006. http://upetd.up.ac.za/thesis/available/etd-08222007-135249.

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Cheng, Lok-lam, and 鄭樂霖. "Approximate string matching in DNA sequences." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29350591.

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Karanam, Suresh Kumar. "Automation of comparative genomic promoter analysis of DNA microarray datasets." Thesis, Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04062004-164658/unrestricted/karanam%5Fsuresh%5Fk%5F200312%5Fms.pdf.

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Labuschagne, Jan Phillipus Lourens. "Development of a data processing toolkit for the analysis of next-generation sequencing data generated using the primer ID approach." University of the Western Cape, 2018. http://hdl.handle.net/11394/6736.

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Philosophiae Doctor - PhD
Sequencing an HIV quasispecies with next generation sequencing technologies yields a dataset with significant amplification bias and errors resulting from both the PCR and sequencing steps. Both the amplification bias and sequencing error can be reduced by labelling each cDNA (generated during the reverse transcription of the viral RNA to DNA prior to PCR) with a random sequence tag called a Primer ID (PID). Processing PID data requires additional computational steps, presenting a barrier to the uptake of this method. MotifBinner is an R package designed to handle PID data with a focus on resolving potential problems in the dataset. MotifBinner groups sequences into bins by their PID tags, identifies and removes false unique bins, produced from sequencing errors in the PID tags, as well as removing outlier sequences from within a bin. MotifBinner produces a consensus sequence for each bin, as well as a detailed report for the dataset, detailing the number of sequences per bin, the number of outlying sequences per bin, rates of chimerism, the number of degenerate letters in the final consensus sequences and the most divergent consensus sequences (potential contaminants). We characterized the ability of the PID approach to reduce the effect of sequencing error, to detect minority variants in viral quasispecies and to reduce the rates of PCR induced recombination. We produced reference samples with known variants at known frequencies to study the effectiveness of increasing PCR elongation time, decreasing the number of PCR cycles, and sample partitioning, by means of dPCR (droplet PCR), on PCR induced recombination. After sequencing these artificial samples with the PID approach, each consensus sequence was compared to the known variants. There are complex relationships between the sample preparation protocol and the characteristics of the resulting dataset. We produce a set of recommendations that can be used to inform sample preparation that is the most useful the particular study. The AMP trial infuses HIV-negative patients with the VRC01 antibody and monitors for HIV infections. Accurately timing the infection event and reconstructing the founder viruses of these infections are critical for relating infection risk to antibody titer and homology between the founder virus and antibody binding sites. Dr. Paul Edlefsen at the Fred Hutch Cancer Research Institute developed a pipeline that performs infection timing and founder reconstruction. Here, we document a portion of the pipeline, produce detailed tests for that portion of the pipeline and investigate the robustness of some of the tools used in the pipeline to violations of their assumptions.
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Bärmann, Daniel. "Aufzählen von DNA-Codes." Master's thesis, Universität Potsdam, 2006. http://opus.kobv.de/ubp/volltexte/2006/1026/.

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In dieser Arbeit wird ein Modell zum Aufzählen von DNA-Codes entwickelt. Indem eine Ordnung auf der Menge aller DNA-Codewörter eingeführt und auf die Menge aller Codes erweitert wird, erlaubt das Modell das Auffinden von DNA-Codes mit bestimmten Eigenschaften, wie Überlappungsfreiheit, Konformität, Kommafreiheit, Stickyfreiheit, Überhangfreiheit, Teilwortkonformität und anderer bezüglich einer gegebenen Involution auf der Menge der Codewörter. Ein auf Grundlage des geschaffenen Modells entstandenes Werkzeug erlaubt das Suchen von Codes mit beliebigen Kombinationen von Codeeigenschaften. Ein weiterer wesentlicher Bestandteil dieser Arbeit ist die Untersuchung der Optimalität von DNA-Codes bezüglich ihrer Informationsrate sowie das Finden solider DNA-Codes.
In this work a model for enumerating DNA codes is developed. By applying an order on the set of DNA codewords and extending this order on the set of codes, this model assists in the discovery of DNA codes with properties like non-overlappingness, compliance, comma-freeness, sticky-freeness, overhang-freeness, subword-compliance, solidness and others with respect to a given involution on the set of codewords. This tool can be used to find codes with arbitrary combinations of code properties with respect to the standard Watson-Crick-DNA involution. The work also investigates DNA codes with respect to the optimizing of the information rate, as well as finding solid DNA codes.
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Shmeleva, Nataliya V. "Making sense of cDNA : automated annotation, storing in an interactive database, mapping to genomic DNA." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/25178.

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Books on the topic "DNA - Data processing"

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IV, Louis W. Storms, and Scott J. Peterson. Microsoft Windows DNA exposed. Indianapolis, IN: Sams, 1999.

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1957-, Lin Simon M., and Johnson Kimberly F. 1972-, eds. Methods of microarray data analysis II: Papers from CAMDA '01. Boston: Kluwer Academic, 2002.

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Yang, Po-sŏk. Twaeji yujŏnch'e taeryang yŏmgi sŏyŏl punsŏk mit yuyong yujŏnja palgul =: High-throughput DNA sequence analysis and identification of trait genes in pigs. [Kyŏnggi-do Suwŏn-si]: Nongch'on Chinhŭngch'ŏng, 2009.

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DNA he dan bai zhi xu lie shu ju fen xi gong ju: Tools for analysis of DNA and protein sequence data. 2nd ed. Beijing: Ke xue chu ban she, 2010.

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Ulʹi͡anov, A. V. Paket programm dli͡a opredelenii͡a i analiza pervichnoĭ struktury DNK. Pushchino: Nauch. t͡sentr biologicheskikh issledovaniĭ AN SSSR v Pushchine, 1985.

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A, Lazere Cathy, ed. Natural computing: DNA, quantum bits, and the future of smart machines. New York: W. W. Norton, 2010.

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Understanding and programming COM+: A practical guide to Windows 2000 DNA. Upper Saddle River, NJ: Prentice Hall, 2000.

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Interface between Computation Science and Nucleic Acid Sequencing Workshop ((1988 Santa Fe, N.M.). Computers and DNA: The proceedings of the Interface between Computation Science and Nucleic Acid Sequencing Workshop, held December 12 to 16, 1988 in Santa Fe, New Mexico. Edited by Bell George I and Marr Thomas G. Redwood City, Calif: Addison-Wesley Pub. Co, 1989.

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Interface between Computation Science and Nucleic Acid Sequencing Workshop (1988 Santa Fe, N.M.). Computers and DNA: The proceedings of the Interface between Computation Science and Nucleic Acid Sequencing Workshop, held December 12 to 16, 1988 in Santa Fe, New Mexico. Redwood City, Calif: Addison-Wesley Pub. Co., 1990.

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Fung, Wing Kam. Statistical DNA Forensics. New York: John Wiley & Sons, Ltd., 2008.

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Book chapters on the topic "DNA - Data processing"

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Skvortsova, Ksenia, and Ozren Bogdanovic. "TAB-seq and Data Processing for DNA Profiling." In Methods in Molecular Biology, 163–78. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1294-1_9.

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Choi, Sun-Wook, and Chong Ho Lee. "DNA Computing Hardware Design and Application to Multiclass Cancer Data." In Advances in Neuro-Information Processing, 1072–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03040-6_130.

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Ryu, Keun Ho, and Erdenebileg Batbaatar. "Improved Cancer Classification with Supervised Variational Autoencoder on DNA Methylation Data." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 36–43. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6757-9_5.

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Pazzaglia, Jean-Christophe, and Daniel Alonso. "Big Data Value Creation by Example." In The Elements of Big Data Value, 245–68. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68176-0_10.

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AbstractThe Big Data Value contractual Public-Private Partnership between the European Commission and the Big Data Value Association (BDVA) was signed in October 2014. Since then, more than 50 projects and numerous BDVA members have explored how data can drive innovation across the data stack and how industries can transform business practices. Meanwhile, start-ups have been working at the confluence of new sources of data (e.g. IoT, DNA, HD pictures, satellite data) and new or revisited processing paradigms (e.g. Edge computing, blockchain, machine learning) to tackle new use cases and to provide disruptive solutions for known problems. This chapter details a collection of stories showing concrete examples of the value created thanks to a renewed usage of data.
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Matougui, Brahim, Hacene Belhadef, and Ilham Kitouni. "An Approach Based Natural Language Processing for DNA Sequences Encoding Using the Global Vectors for Word Representation." In Lecture Notes on Data Engineering and Communications Technologies, 577–85. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70713-2_53.

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Martinez-Val, Ana, Dorte Breinholdt Bekker-Jensen, Alexander Hogrebe, and Jesper Velgaard Olsen. "Data Processing and Analysis for DIA-Based Using." In Methods in Molecular Biology, 95–107. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1641-3_6.

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Schmidt, Katrin, and Angus Atkinson. "Feeding and Food Processing in Antarctic Krill (Euphausia superba Dana)." In Biology and Ecology of Antarctic Krill, 175–224. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29279-3_5.

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Mo, Fu. "An Improvement Method of Power Energy Utilization Rate Based on DEA Model." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), 105–10. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_15.

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Chelly, Zeineb, and Zied Elouedi. "QR-DCA: A New Rough Data Pre-processing Approach for the Dendritic Cell Algorithm." In Adaptive and Natural Computing Algorithms, 140–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37213-1_15.

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Zhu, Beibei. "Analysis of Port Efficiency and Influencing Factors Based on DEA-Tobit." In 2020 International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems, 547–54. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1726-3_67.

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Conference papers on the topic "DNA - Data processing"

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Guo, Tianli, Tao Zhang, and Chuan Jin. "Data Processing in DNA Profiling." In BIC 2021: 2021 International Conference on Bioinformatics and Intelligent Computing. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3448748.3448785.

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Ashrafi, Reza A., Ali E. Pusane, and Suayb S. Arslan. "Next-Generation data storage: Transistor and DNA." In 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018. http://dx.doi.org/10.1109/siu.2018.8404428.

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Haughton, David, and Felix Balado. "Security study of keyed DNA data embedding." In 2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2013. http://dx.doi.org/10.1109/globalsip.2013.6736812.

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Lijun, Jiang, Wenxian Yang, Rongshan Yu, Shiqian Wu, and Anisha Anil Lekshmy. "Comparison of three bioinformatics pipelines for DNA/RNA data processing." In 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2017. http://dx.doi.org/10.1109/iciea.2017.8282818.

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Hern´ndez-Cabronero, Miguel, Ian Blanes, Joan Serra-Sagrista, and Michael W. Marcellin. "A Review of DNA Microarray Image Compression." In 2011 First International Conference on Data Compression, Communications and Processing (CCP). IEEE, 2011. http://dx.doi.org/10.1109/ccp.2011.21.

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Alqallaf, Abdullah K., and Ahmed H. Tewfik. "Classification techniques for recurrent DNA copy number data." In 2008 3rd International Symposium on Communications, Control and Signal Processing (ISCCSP). IEEE, 2008. http://dx.doi.org/10.1109/isccsp.2008.4537411.

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Balado, Felix. "On the Shannon capacity of DNA data embedding." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2010. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495437.

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Kim, Jang Hyun, and Hyunseok Yang. "IPI Noise Reduction by Image Mask Using DNA Coding Method in Holographic Data Storage System." In ASME 2016 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/isps2016-9601.

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A holographic data storage system (HDSS) is very important field in the storage system device. Many researchers study the HDSS about image processing algorithm for reduction of image noise. In this work, we proposed an intelligence virtual mask, parameter values of virtual image mask generated using DNA coding method, it is available to decrease the IPI noise in HDSS. In this paper, an intensity distribution of laser beam in our HDSS is controlled by the virtual mask with an intelligence algorithm. The virtual mask value is changed arbitrarily in real-time with suggested DNA coding method in the HDSS.
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Alakus, Talha Burak, Bihter Das, and Ibrahim Turkoglu. "DNA encoding with entropy based numerical mapping technique for phylogenetic analysis." In 2019 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2019. http://dx.doi.org/10.1109/idap.2019.8875937.

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Karaboga, Dervis, Selcuk ASLAN, and Alperen AKSOY. "Finding DNA Motifs with Collective Parallel Artificial Bee Colony Algorithm." In 2018 International Conference on Artificial Intelligence and Data Processing (IDAP). IEEE, 2018. http://dx.doi.org/10.1109/idap.2018.8620731.

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