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Algorithms
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Asignación Latente de Dirichlet
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Biología molecular
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Latent Dirichlet Allocation
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Teoría algebraica de los números
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Topic evolution
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841por Cron, Andrew, Gouttefangeas, Cécile, Frelinger, Jacob, Lin, Lin, Singh, Satwinder K., Britten, Cedrik M., Welters, Marij J. P., van der Burg, Sjoerd H., West, Mike, Chan, Cliburn“…In this manuscript, we develop hierarchical modeling extensions to the Dirichlet Process Gaussian Mixture Model (DPGMM) approach we have previously described for cell subset identification, and show that the hierarchical DPGMM (HDPGMM) naturally generates an aligned data model that captures both commonalities and variations across multiple samples. …”
Publicado 2013
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842por Olendski, Oleg“…Thermodynamic properties of the one-dimensional (1D) quantum well (QW) with miscellaneous permutations of the Dirichlet (D) and Neumann (N) boundary conditions (BCs) at its edges in the perpendicular to the surfaces electric field [Image: see text] are calculated. …”
Publicado 2015
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843“…This generative model, obtained through the Latent Dirichlet Allocation (LDA) algorithm, is then used to classify a large set of genomic sequences. …”
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844“…These boundary conditions are of Dirichlet type, Neumann type or Robin type. A finite-difference method which maintains second-order accuracy in space along the boundary, is developed to solve the parabolic equation. …”
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845por Zhao, Weizhong, Chen, James J, Perkins, Roger, Liu, Zhichao, Ge, Weigong, Ding, Yijun, Zou, Wen“…While mainly used to build models from unstructured textual data, it offers an effective means of data mining where samples represent documents, and different biological endpoints or omics data represent words. Latent Dirichlet Allocation (LDA) is the most commonly used topic modelling method across a wide number of technical fields. …”
Publicado 2015
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846“…METHODS: We explore the use of topic modelling methods to derive a more informative representation of studies. We apply Latent Dirichlet allocation (LDA), an unsupervised topic modelling approach, to automatically identify topics in a collection of studies. …”
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847por Wang, Shi-Heng, Ding, Yijun, Zhao, Weizhong, Huang, Yung-Hsiang, Perkins, Roger, Zou, Wen, Chen, James J.“…METHODS: In this study, a total of 17,723 abstracts from PubMed published from 2000 to 2014 on adolescent substance use and depression were downloaded as objects, and Latent Dirichlet allocation (LDA) was applied to perform text mining on the dataset. …”
Publicado 2016
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848“…(iii) It uses a Bayesian statistical measure of alignment quality based on the minimum description length principle and on Dirichlet mixture priors. Consequently, GISMO aligns sequence regions only when statistically justified. …”
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849por Behr, Aaron A., Liu, Katherine Z., Liu-Fang, Gracie, Nakka, Priyanka, Ramachandran, Sohini“…These methods belong to a broad class of mixed-membership models, such as latent Dirichlet allocation used to analyze text corpora. …”
Publicado 2016
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850por Jacobs, Jonathan P., Goudarzi, Maryam, Singh, Namita, Tong, Maomeng, McHardy, Ian H., Ruegger, Paul, Asadourian, Miro, Moon, Bo-Hyun, Ayson, Allyson, Borneman, James, McGovern, Dermot P.B., Fornace, Albert J., Braun, Jonathan, Dubinsky, Marla“…Individuals were grouped into microbial and metabolomics states using Dirichlet multinomial models. Multivariate models were used to identify microbes and metabolites associated with these states. …”
Publicado 2016
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851“…The questionnaire responses are then used in a Dirichlet draw to create a Bayesian ‘missing not at random’ (MNAR) prior to impute the missing observations. …”
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852“…We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. …”
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853por Chen, Jonathan H, Goldstein, Mary K, Asch, Steven M, Mackey, Lester, Altman, Russ B“…Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. …”
Publicado 2017
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854por Dias, Andreia, Palma, Luís, Carvalho, Filipe, Neto, Dora, Real, Joan, Beja, Pedro“…We approximated the boundaries of 84 territories using Dirichlet tessellation and mapped topography, land cover, and the density of human infrastructures in buffers (250, 500, and 1,000 m) around nest and random sites. …”
Publicado 2017
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855por Chen, Chang-Hua, Lin, Yaw-Ling, Chen, Kuan-Hsueh, Chen, Wen-Pei, Chen, Zhao-Feng, Kuo, Han-Yueh, Hung, Hsueh-Fen, Tang, Chuan Yi, Liou, Ming-Li“…We examined the surface bacterial communities and environmental parameters in the buildings supplied with different ventilation types and compared the results using a Dirichlet multinomial mixture (DMM)-based approach. …”
Publicado 2017
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856“…Three language models were applied and compared: a state-of-the-art deep unsupervised learning algorithm along with two other language models of different types, Term Frequency-Inverse Document Frequency in the bag-of-words and Latent Dirichlet Allocation in the topic modeling category. …”
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857“…Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. …”
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858por Martin, Ivonne, Djuardi, Yenny, Sartono, Erliyani, Rosa, Bruce A., Supali, Taniawati, Mitreva, Makedonka, Houwing-Duistermaat, Jeanine J., Yazdanbakhsh, Maria“…Statistical analysis was performed cross-sectionally at pre-treatment to assess the effect of infection, and at post-treatment to determine the effect of infection and treatment on microbiome composition using the Dirichlet-multinomial regression model. RESULTS: At a phylum level, at pre-treatment, no difference was seen in microbiome composition in terms of relative abundance between helminth-infected and uninfected subjects and at post-treatment, no differences were found in microbiome composition between albendazole and placebo group. …”
Publicado 2018
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859“…Bibliometrics, geographic visualization, collaboration degree calculation, social network analysis, latent dirichlet allocation, and affinity propagation clustering are applied to analyze research quantity, collaboration relations, and hot research topics. …”
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860“…In recent years, researchers have introduced multi-label supervised topic model such as Labeled Latent Dirichlet Allocation (Labeled-LDA) into protein function prediction, which can obtain more accurate and explanatory prediction. …”
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