Auswahl der wissenschaftlichen Literatur zum Thema „Sequence similarity analysis“
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Zeitschriftenartikel zum Thema "Sequence similarity analysis"
Wei, Dan, Qingshan Jiang und Sheng Li. „A New Approach for DNA Sequence Similarity Analysis based on Triplets of Nucleic Acid Bases“. International Journal of Nanotechnology and Molecular Computation 2, Nr. 4 (Oktober 2010): 1–11. http://dx.doi.org/10.4018/978-1-60960-064-8.ch006.
Der volle Inhalt der QuelleLi, Hongliang, und Bin Liu. „BioSeq-Diabolo: Biological sequence similarity analysis using Diabolo“. PLOS Computational Biology 19, Nr. 6 (20.06.2023): e1011214. http://dx.doi.org/10.1371/journal.pcbi.1011214.
Der volle Inhalt der Quellede Oliveira Martins, Leonardo, Alison E. Mather und Andrew J. Page. „Scalable neighbour search and alignment with uvaia“. PeerJ 12 (06.03.2024): e16890. http://dx.doi.org/10.7717/peerj.16890.
Der volle Inhalt der QuelleVan Reenen, C. A., W. H. Van Zyl und L. M. T. Dicks. „Expression of the Immunity Protein of Plantaricin 423, Produced by Lactobacillus plantarum 423, and Analysis of the Plasmid Encoding the Bacteriocin“. Applied and Environmental Microbiology 72, Nr. 12 (20.10.2006): 7644–51. http://dx.doi.org/10.1128/aem.01428-06.
Der volle Inhalt der QuellePacheco, Richard C., Jonas Moraes-Filho, Arlei Marcili, Leonardo J. Richtzenhain, Matias P. J. Szabó, Márcia H. B. Catroxo, Donald H. Bouyer und Marcelo B. Labruna. „Rickettsia monteiroi sp. nov., Infecting the Tick Amblyomma incisum in Brazil“. Applied and Environmental Microbiology 77, Nr. 15 (17.06.2011): 5207–11. http://dx.doi.org/10.1128/aem.05166-11.
Der volle Inhalt der QuelleSmallwood, M., J. N. Keen und D. J. Bowles. „Purification and partial sequence analysis of plant annexins“. Biochemical Journal 270, Nr. 1 (15.08.1990): 157–61. http://dx.doi.org/10.1042/bj2700157.
Der volle Inhalt der QuelleGyörgyey, János, Danièle Vaubert, José I. Jiménez-Zurdo, Celine Charon, Liliane Troussard, Ádám Kondorosi und Éva Kondorosi. „Analysis of Medicago truncatula Nodule Expressed Sequence Tags“. Molecular Plant-Microbe Interactions® 13, Nr. 1 (Januar 2000): 62–71. http://dx.doi.org/10.1094/mpmi.2000.13.1.62.
Der volle Inhalt der QuelleXu, Fuyu, und Kate Beard. „A Unifying Framework for Analysis of Spatial-Temporal Event Sequence Similarity and Its Applications“. ISPRS International Journal of Geo-Information 10, Nr. 9 (09.09.2021): 594. http://dx.doi.org/10.3390/ijgi10090594.
Der volle Inhalt der QuelleNikhila, K. S., und Vrinda V. Nair. „Protein Sequence Similarity Analysis Using Computational Techniques“. Materials Today: Proceedings 5, Nr. 1 (2018): 724–31. http://dx.doi.org/10.1016/j.matpr.2017.11.139.
Der volle Inhalt der QuelleHark Gan, Hin, Rebecca A. Perlow, Sharmili Roy, Joy Ko, Min Wu, Jing Huang, Shixiang Yan et al. „Analysis of Protein Sequence/Structure Similarity Relationships“. Biophysical Journal 83, Nr. 5 (November 2002): 2781–91. http://dx.doi.org/10.1016/s0006-3495(02)75287-9.
Der volle Inhalt der QuelleDissertationen zum Thema "Sequence similarity analysis"
Joseph, Arokiya Louis Monica. „Sequence Similarity Search portal“. CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3124.
Der volle Inhalt der QuelleChen, Zhuo. „Smart Sequence Similarity Search (S⁴) system“. CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2458.
Der volle Inhalt der QuelleMendoza, Leon Jesus Alexis. „Analysis of DNA sequence similarity within organisms causing New World leishmaniasis“. Thesis, University of Cambridge, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386206.
Der volle Inhalt der QuelleBatra, Sushil Baker Erich J. Lee Myeongwoo. „Identification of phenotypes in Caenorabhditis elegans on the basis of sequence similarity“. Waco, Tex. : Baylor University, 2009. http://hdl.handle.net/2104/5325.
Der volle Inhalt der QuelleOzturk, Ozgur. „Feature extraction and similarity-based analysis for proteome and genome databases“. The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1190138805.
Der volle Inhalt der QuelleMitas̃iūnaite, Ieva. „Mining string data under similarity and soft-frequency constraints : application to promoter sequence analysis“. Lyon, INSA, 2009. http://theses.insa-lyon.fr/publication/2009ISAL0036/these.pdf.
Der volle Inhalt der QuelleAn inductive database is a database that contains not only data but also patterns. Inductive databases are designed to support the KDD process. Recent advances in inductive databases research have given rise to a generic solvers capable of solving inductive queries that are arbitrary Boolean combinations of anti-monotonic and monotonic constraints. They are designed to mine different types of pattern (i. E. , patterns from different pattern languages). An instance of such a generic solver exists that is capable of mining string patterns from string data sets. In our main application, promoter sequence analysis, there is a requirement to handle fault-tolerance, as the data intrinsically contains errors, and the phenomenon we are trying to capture is fundamentally degenerate. Our research contribution to fault-tolerant pattern extraction in string data sets is the use of a generic solver, based on a non-trivial formalisation of fault-tolerant pattern extraction as a constraint-based mining task. We identified the stages in the process of the extraction of such patterns where state-of-art strategies can be applied to prune the search space. We then developed a fault-tolerant pattern match function InsDels that generic constraint solving strategies can soundly tackle. We also focused on making local patterns actionable. The bottleneck of most local pattern extraction methods is the burden of spurious patterns. As the analysis of patterns by the application domain experts is time consuming, we cannot afford to present patterns without any objective clue about their relevancy. Therefore we have developed two methods of computing the expected number of patterns extracted in random data sets. If the number of extracted patterns is strongly different from the expected number from random data sets, one can then state that the results exhibits local associations that are a priori relevant because they are unexpected. Among others applications, we have applied our approach to support the discovery of new motifs in gene promoter sequences with promising results
Sacan, Ahmet. „Similarity Search And Analysis Of Protein Sequences And Structures: A Residue Contacts Based Approach“. Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609754/index.pdf.
Der volle Inhalt der QuelleWessel, Jennifer. „Human genetic-epidemiologic association analysis via allelic composition and DNA sequence similarity methods applications to blood-based gene expression biomarkers of disease /“. Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3237548.
Der volle Inhalt der QuelleTitle from first page of PDF file (viewed December 12, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.
Wang, Danling. „Multifractal characterisation and analysis of complex networks“. Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/48176/1/Danling_Wang_Thesis.pdf.
Der volle Inhalt der QuelleYan, Yiqing. „Scalable and accurate algorithms for computational genomics and dna-based digital storage“. Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS078.
Der volle Inhalt der QuelleCost reduction and throughput improvement in sequencing technology have resulted in new advances in applications such as precision medicine and DNA-based storage. However, the sequenced result contains errors. To measure the similarity between the sequenced result and reference, edit distance is preferred in practice over Hamming distance due to the indels. The primitive edit distance calculation is quadratic complex. Therefore, sequence similarity analysis is computationally intensive. In this thesis, we introduce two accurate and scalable sequence similarity analysis algorithms, i) Accel-Align, a fast sequence mapper and aligner based on the seed–embed–extend methodology, and ii) Motif-Search, an efficient structure-aware algorithm to recover the information encoded by the composite motifs from the DNA archive. Then, we use Accel-Align as an efficient tool to study the random access design in DNA-based storage
Bücher zum Thema "Sequence similarity analysis"
Bilański, Piotr. Trypodendron laeve Eggers w Polsce na tle wybranych aspektów morfologicznych i genetycznych drwalników (Trypodendron spp., Coleoptera, Curculionidae, Scolytinae). Publishing House of the University of Agriculture in Krakow, 2019. http://dx.doi.org/10.15576/978-83-66602-38-0.
Der volle Inhalt der QuelleBuchteile zum Thema "Sequence similarity analysis"
States, David J., und Mark S. Boguski. „Similarity and Homology“. In Sequence Analysis Primer, 89–157. London: Palgrave Macmillan UK, 1991. http://dx.doi.org/10.1007/978-1-349-21355-9_3.
Der volle Inhalt der QuelleAdjeroh, D. A., I. King und M. C. Lee. „Video sequence similarity matching“. In Multimedia Information Analysis and Retrieval, 80–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0016490.
Der volle Inhalt der QuelleYap, Tieng K., Ophir Frieder und Robert L. Martino. „Multiprocessor Sequence Similarity Searching“. In High Performance Computational Methods for Biological Sequence Analysis, 143–57. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1391-5_6.
Der volle Inhalt der QuelleRyšavý, Petr, und Filip Železný. „Estimating Sequence Similarity from Contig Sets“. In Advances in Intelligent Data Analysis XVI, 272–83. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68765-0_23.
Der volle Inhalt der QuelleSubbotin, Sergei A. „Phylogenetic analysis of DNA sequence data.“ In Techniques for work with plant and soil nematodes, 265–82. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781786391759.0265.
Der volle Inhalt der QuelleSubbotin, Sergei A. „Phylogenetic analysis of DNA sequence data.“ In Techniques for work with plant and soil nematodes, 265–82. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781786391759.0015.
Der volle Inhalt der QuelleUng, Huy Quang, Cuong Tuan Nguyen, Hung Tuan Nguyen und Masaki Nakagawa. „GSSF: A Generative Sequence Similarity Function Based on a Seq2Seq Model for Clustering Online Handwritten Mathematical Answers“. In Document Analysis and Recognition – ICDAR 2021, 145–59. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86331-9_10.
Der volle Inhalt der QuelleXie, Bo, und Long Chen. „Automatic Scoring Model of Subjective Questions Based Text Similarity Fusion Model“. In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 586–99. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_60.
Der volle Inhalt der QuelleBonnici, Vincenzo, Andrea Cracco und Giuditta Franco. „A k-mer Based Sequence Similarity for Pangenomic Analyses“. In Machine Learning, Optimization, and Data Science, 31–44. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95470-3_3.
Der volle Inhalt der QuelleYang, Wenlu, Xiongjun Pi und Liqing Zhang. „Similarity Analysis of DNA Sequences Based on the Relative Entropy“. In Lecture Notes in Computer Science, 1035–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11539087_137.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Sequence similarity analysis"
Yusen Zhang und Xiangtian Yu. „Analysis of protein sequence similarity“. In 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA). IEEE, 2010. http://dx.doi.org/10.1109/bicta.2010.5645085.
Der volle Inhalt der QuelleKetterlin, Alain, und Pierre Ganarski. „Sequence Similarity and Multi-Date Image Segmentation“. In 2007 International Workshop on the Analysis of Multi-temporal Remote Sensing Images. IEEE, 2007. http://dx.doi.org/10.1109/multitemp.2007.4293034.
Der volle Inhalt der QuelleLei, H., und Venu Govindaraju. „Similarity-driven sequence classification based on support vector machines“. In Eighth International Conference on Document Analysis and Recognition (ICDAR'05). IEEE, 2005. http://dx.doi.org/10.1109/icdar.2005.217.
Der volle Inhalt der QuelleYang, Lina, Yuan Yan Tang, Yulong Wang, Huiwu Luo, Jianjia Pan, Haoliang Yuan, Xianwei Zheng, Chunli Li und Ting Shu. „Similarity analysis based on sparse representation for protein sequence comparison“. In 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF). IEEE, 2015. http://dx.doi.org/10.1109/cybconf.2015.7175964.
Der volle Inhalt der QuelleKong, Fen, Xu-ying Nan, Ping-an He, Qi Dai und Yu-hua Yao. „A sequence-segmented method applied to the similarity analysis of proteins“. In 2012 IEEE 6th International Conference on Systems Biology (ISB). IEEE, 2012. http://dx.doi.org/10.1109/isb.2012.6314157.
Der volle Inhalt der QuelleHu, Jun, Hongxia Zhao, Xueyou Liang und Dan Chen. „The analysis of similarity for promoter sequence structures in yeast genes“. In 2012 5th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2012. http://dx.doi.org/10.1109/bmei.2012.6513091.
Der volle Inhalt der QuelleDang, Xiaocui, Lina Yang, Yuan Yan Tang, Pu Wei und Hailong Su. „Nd5 Protein Sequence Similarity Analysis Based On Discrete Wavelet Transform And Fractal Dimension“. In 2019 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2019. http://dx.doi.org/10.1109/icwapr48189.2019.8946464.
Der volle Inhalt der QuelleBai, Fenglan, und Jun Xu. „Sequence Similarity Analysis of Buthus Martensii Neurotoxin Genes Based on Structure Matrix“. In 2012 Fourth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccis.2012.277.
Der volle Inhalt der QuelleZhang, Hainan, Yanyan Lan, Jiafeng Guo, Jun Xu und Xueqi Cheng. „Reinforcing Coherence for Sequence to Sequence Model in Dialogue Generation“. In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/635.
Der volle Inhalt der QuelleGupta, Manoj Kumar, Rajdeep Niyogi und Manoj Misra. „A framework for alignment-free methods to perform similarity analysis of biological sequence“. In 2013 Sixth International Conference on Contemporary Computing (IC3). IEEE, 2013. http://dx.doi.org/10.1109/ic3.2013.6612216.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Sequence similarity analysis"
Gelb, Jr., Jack, Yoram Weisman, Brian Ladman und Rosie Meir. Identification of Avian Infectious Brochitis Virus Variant Serotypes and Subtypes by PCR Product Cycle Sequencing for the Rational Selection of Effective Vaccines. United States Department of Agriculture, Dezember 2003. http://dx.doi.org/10.32747/2003.7586470.bard.
Der volle Inhalt der QuelleDickman, Martin B., und Oded Yarden. Role of Phosphorylation in Fungal Spore Germination. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568761.bard.
Der volle Inhalt der QuelleCohen, Yuval, Christopher A. Cullis und Uri Lavi. Molecular Analyses of Soma-clonal Variation in Date Palm and Banana for Early Identification and Control of Off-types Generation. United States Department of Agriculture, Oktober 2010. http://dx.doi.org/10.32747/2010.7592124.bard.
Der volle Inhalt der QuelleFridman, Eyal, und Eran Pichersky. Tomato Natural Insecticides: Elucidation of the Complex Pathway of Methylketone Biosynthesis. United States Department of Agriculture, Dezember 2009. http://dx.doi.org/10.32747/2009.7696543.bard.
Der volle Inhalt der QuelleMichelmore, Richard, Eviatar Nevo, Abraham Korol und Tzion Fahima. Genetic Diversity at Resistance Gene Clusters in Wild Populations of Lactuca. United States Department of Agriculture, Februar 2000. http://dx.doi.org/10.32747/2000.7573075.bard.
Der volle Inhalt der QuelleUeti, Massaro Wilson, und Monica Leszkowicz Mazuz. Identification, characterization and testing of geographically conserved Babesia bovis vaccine antigen candidates. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2022. http://dx.doi.org/10.32747/2022.8134143.bard.
Der volle Inhalt der QuelleLevisohn, Sharon, Maricarmen Garcia, David Yogev und Stanley Kleven. Targeted Molecular Typing of Pathogenic Avian Mycoplasmas. United States Department of Agriculture, Januar 2006. http://dx.doi.org/10.32747/2006.7695853.bard.
Der volle Inhalt der QuelleParan, Ilan, und Allen Van Deynze. Regulation of pepper fruit color, chloroplasts development and their importance in fruit quality. United States Department of Agriculture, Januar 2014. http://dx.doi.org/10.32747/2014.7598173.bard.
Der volle Inhalt der QuelleOr, Etti, David Galbraith und Anne Fennell. Exploring mechanisms involved in grape bud dormancy: Large-scale analysis of expression reprogramming following controlled dormancy induction and dormancy release. United States Department of Agriculture, Dezember 2002. http://dx.doi.org/10.32747/2002.7587232.bard.
Der volle Inhalt der QuelleRafaeli, Ada, und Russell Jurenka. Molecular Characterization of PBAN G-protein Coupled Receptors in Moth Pest Species: Design of Antagonists. United States Department of Agriculture, Dezember 2012. http://dx.doi.org/10.32747/2012.7593390.bard.
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