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Bayesian inference

Tìm thấy 10+ kết quả cho từ khóa "Bayesian inference"

Chloroplast phylogenomics and divergence times of Lagerstroemia (Lythraceae)

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Molecular phylogeny of Lagerstroemia resulting from ML (maximum likelihood) and BI (Bayesian inference) analyses using LSC regions (dataset-4). Molecular phylogeny of Lagerstroemia resulting from ML (maximum likelihood) and BI (Bayesian inference) analyses using IR regions (dataset-5). Molecular phylogeny of Lagerstroemia resulting from ML (maximum likelihood) and BI (Bayesian inference) analyses using SSC regions (dataset-6).

Comparative chloroplast genome analysis of Artemisia (Asteraceae) in East Asia: Insights into evolutionary divergence and phylogenomic implications

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Phylogenetic analysis of the whole plastomes based on maximum likelihood and Bayesian inference analyses yielded five groups of Artemisia plastomes clustered in the monophyletic subgenus Dracunculus and paraphyletic subgenus Artemisia, suggesting that the whole plastomes can be used as molecular markers to infer the chloroplast haplotypes of Artemisia taxa. Conclusions: The complete sequences of the Artemisia plastomes are sufficiently polymorphic to be used as super- barcodes for this genus.

Tóm tắt luận án tiến sĩ Công nghệ sinh học: Xây dựng chỉ thị phân tử nhận dạng và nghiên cứu nhân giống bảo tồn loài Xáo tam phân (Paramignya trimera)

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Đối với chương trình BEAST sử dụng thuật toán thống kê Bayesian inference (Hình 2.23b) cho thấy các trình tự của các mẫu nhóm P. Như vậy, đối với trình tự rbcL khi sử dụng cả 2 chương trình MegaX và BEAST đều cho thấy có sự đan xen giữa các mẫu P. Điều này cho thấy, khả năng sử dụng trình tự rbcL làm chỉ thị để nhận dạng loài Xáo tam phân P.. Phân tích trình tự ITS.

Khóa luận tốt nghiệp: Nghiên cứu phân loại chi Cóc (Spondias L.) ở Việt Nam dựa trên hình thái và phân tử

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Nghiên cứu này sử dụng hai phương pháp dựng cây phát sinh là Maximum Likelihood (ML) và Bayesian Inference (BI), sau đó được tiến hành chạy trên CIPRES Science Gateway Portal [17]. Trình tự DNA của gen rbcL, matK, và trnLF của 4 mẫu nghiên cứu đã được giải trình tự thành công với kích thước thu được lần lượt là bp.

The complete chloroplast genome of Stauntonia chinensis and compared analysis revealed adaptive evolution of subfamily Lardizabaloideae species in China

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Tree constructed by Maximum likelihood (ML) and Bayesian inference (BI) methods with the posterior probabilities of BI and the bootstrap values of ML above the branches based on: a protein-coding genes CDs sequences, b the complete chloroplast genome sequences.

“Integrative genomic analysis of the bioprospection of regulators and accessory enzymes associated with cellulose degradation in a filamentous fungus (Trichoderma harzianum)”

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The induction and repression networks were constructed based on the expres- sion data of a set of genes that were identified in the secre- tome of the CEL growth condition by the Bayesian inference method [63]. If the secreted protein was present in the condition, it was assigned a value of one. The treatment conditions were considered regulators of the network to detect the direct relationships between the con- ditions and the genes.

Secretory RING finger proteins function as effectors in a grapevine galling insect

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Secretory RING protein genes are more likely to duplicate and express at feeding stage. viti- foliae, we constructed the Bayesian inference of phylogen- etic trees separately for secretory and no-secretory RING proteins because of the sequence divergence between these two groups. Based on a 0.9 posterior probabilities threshold to cluster ≥3 RING proteins, only six (6%) non- secretory proteins formed two clusters, NSE-1 and NSE-2 (Fig.

Summary of Biotechnology doctoral thesis: Study on development of DNA barcodes and research on in vitro micropropagation of Paramignya trimera

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For the BEAST program using the Bayesian inference statistical algorithm (Figure 2.23b), the sequences of the P. trimera samples with other species of the genus Paramignya.. trimera is still likely to be confused with some close species of the same genus such as P. Construction of DNA barcode for the identification of P.trimera 3.4.5.1.

Whole genome sequencing reveals the emergence of a Pseudomonas aeruginosa shared strain sub-lineage among patients treated within a single cystic fibrosis centre

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To determine the emergence of the M3L7 sub-type, Bayesian inference of the evolutionary rates was conducted using BEAST 1.8.2 [32].

International Capital Flows and Boom-Bust Cycles in the Asia Pacific Region +

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For example, an increase in the real GDP may attract more capital, and improve the capital account. 15 We adopt the Bayesian inference, which is not subject to conventional criticism in the presence of unit root and co-integration. We relate the capital flow shocks identified in the model to the financial market liberalization and the global common shocks under a more liberalized financial market. In Singapore, capital inflows did not generate a boom in the economy.

Comparison of chloroplast genomes of Gynura species: Sequence variation, genome rearrangement and divergence studies

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Bayesian inference (BI) phylogenetic tree obtained for 16 Senecioneae species based on the whole chloroplast genome sequences. The Pi value (nucleotide diversity) of chloroplast genome sequences between four Gynura species and five Ligularia species.. WL and JC designed the idea of the article. Hassan Z, Yam MF, Ahmad M, et al. Deng YX, Chen YS, Zhang WR, et al. Rosidah, Yam MF, Sadikun A, et al. Palmer JD, Jansen RK, Michaels HJ, et al.

Dynamic Bayesian Networks.pdf

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DYNAMIC BAYESIAN NETWORKS INFERENCE IN DYNAMIC BAYESIAN NETWORKS + Từđây chúng ta giảđịnhrằng DBN là đồngnhất theo thời gian ( time-homogeneous. dbn2 = set.arc(dbn2, "245094_at at DYNAMIC BAYESIAN NETWORKS. DYNAMIC BAYESIAN NETWORKS INFERENCE IN DYNAMIC BAYESIAN NETWORKS + Cuối cùng, cho chúng ta biếtkiếnthứcvề gen 265768_at và gen 245094_at tạithờiđiểm t – 2 và t , chúng ta có thể nghiên cứu phân phốicủa gen 245094_at tạithờiđiểm t

Bayesian Network

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Initial probabilities of the Bayesian network.. Conditional probabilities of the Bayesian network – P(Grade | Study  Grade-1).. General model of the Markov transition matrix.. Calculating from (4), we obtained the Markov transition matrix (represented by the letter P), presenting the transition probabilities for the states of the variable studied. a r ] and each arcs connects two nodes of the network. Discretized states of the variables pluv_r and commercial

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

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Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty. Background: Single-cell gene expression measurements offer opportunities in deriving mechanistic understanding of complex diseases, including cancer. However, due to the complex regulatory machinery of the cell, gene regulatory network (GRN) model inference based on such data still manifests significant uncertainty..

Probabilistic Inference Using Markov Chain Monte Carlo Methods

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Discusses applications to Bayesian statistical inference of the Gibbs sampler and two other Monte Carlo algorithms. (1981) \On the selection of the particle to be perturbed in the Monte Carlo method", Journal of Computational Physics , vol. A parallel version of the algorithm is described as well.. (with discussion), Journal of the American Statistical Association , vol. (1992) \Use of the Gibbs sampler in expert systems", Articial Intelligence , vol.

A program anomaly intrusion detection scheme based on fuzzy inference

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In this step, the normal database and the HMM model are used to compute the input parameters for the fuzzy inference engine.. Classification of the test sequence by the fuzzy inference engine: In this step, the fuzzy inference engine applies the fuzzy sets and rules to interpret the input parameters in order to produce the output which is the status of the short sequence:. 2 shows the fuzzy inference engine for the classification of short sequences of system calls.

A program anomaly intrusion detection scheme based on fuzzy inference

tainguyenso.vnu.edu.vn

Classification of the test sequence by the fuzzy inference engine: In this step, the fuzzy inference engine applies the fuzzy sets and rules to interpret the input parameters in order to produce the output which is the status of the short sequence: normal or abnormal. 2 shows the fuzzy inference engine for the classification of short sequences of system calls.

Reconstruction of real and simulated phylogenies based on quartet plurality inference

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The plurality inference rule - The plurality inference rule functions as a quartet oracle that helps to reconcile conflicting gene trees. (2) where S 1 is the number of non-trivial splits in t 1 , and b 1. is the number of t 1 tree splits that are not induced by any one of the edges of t 2 .

Summary of Computer doctoral thesis: Some extensions of the complex fuzzy inference system for decision support problem

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SOME EXTENSIONS OF THE COMPLEX FUZZY INFERENCE SYSTEM FOR DECISION SUPPORT. Complex fuzzy inference systems are considered to be an effective tool for solving problems with periodicity and uncertainty. with inference systems in complex fuzzy sets. Complex fuzzy systems have not provided an overall procedure for building complex fuzzy inference systems for decision support systems..

Discovery and genome characterization of three new Jeilongviruses, a lineage of paramyxoviruses characterized by their unique membrane proteins

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The tree is based on Bayesian phylogenetic inference of the concatenated sequences of the N, P, M, F, G and L proteins of all 55 currently recognized paramyxovirus species, as well as 14 putative species that have not yet been classified (marked with. The tree is based on Bayesian phylogenetic inference of the L proteins of all 55 currently recognized paramyxovirus species, as well as 18 putative species that have not yet been classified (marked with.