Structure and Inference
PERFORMANCE EVALUATION OF THE INFERENCE STRUCTURE IN EXPERT SYSTEM
... II THE NETWORK MODEL OP INFERENCE STRUCTURE. 946 REASONING.[r] ...
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Combining Markers into Haplotypes Can Improve Population Structure Inference
... *Department of Evolutionary Biology, Evolutionary Biology Centre, and † Science for Life Laboratory, Uppsala University, SE-752 36, Uppsala, Sweden ABSTRACT High-throughput genotyping and sequencing technologies can ...
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Recurrent Neural Networks and Their Applications to RNA Secondary Structure Inference
... secondary structure inference and compares them to a standard structure inference tool, the nearest neighbor thermody- namic model ...RNA structure, which are then converted into ...
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An inference method from multi-layered structure of biomedical data
... Integrative inference on biomedical data, Semi-supervised learning, Semi-supervised learning for multiple networks, Symptom-disease multi-layered network, Disease co-occurrence prediction Background Omics is a ...
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Learning with Joint Inference and Latent Linguistic Structure in Graphical Models
... A related line of research also seeks to use end task annotations to guide the induction of a task-specific parser. The major distinction between this and the aforementioned work is the focus on evaluating the latent ...
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Gene regulatory network inference I: Dissecting structure and dynamics
... network structure and its implications for the dynamics, and hence the function, of such ...Network inference is the challenging task of estimating the underlying net- work from dynamical observations at ...
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Alternative Multiple Imputation Inference for Mean and Covariance Structure Modeling
... Li Cai University of California, Los Angeles Model-based multiple imputation has become an indispensable method in the educational and behavioral sciences. Mean and covariance structure models are often fitted to ...
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A non-parametric approach to population structure inference using multilocus genotypes
... Abstract Inference of population structure from genetic markers is helpful in diverse situations, such as association and evolutionary ...population structure using multilocus genotype ...population ...
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fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets
... population structure from genetic data are now used in a wide variety of applications in population ...population structure in large modern data sets imposes severe computational ...approximate ...
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mStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations
... variational inference algorithm, which is much faster than the MCMC algorithm used for Structure, was developed for estimat- ing the structure vectors and other genetic parameters of ...with ...
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A Novel and Fast Approach for Population Structure Inference Using Kernel-PCA and Optimization
... Population structure is a confounding factor in genome-wide association studies, increasing the rate of false positive ...and STRUCTURE have been ...population structure inference using ...
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Protein structure, distribution of homoplasy and phylogenetic inference
... The nucleotide substitution rate has been estimated using likelihood with HKY model. Triangles show peaks analogous to the peaks observed for the likelihood profile[r] ...
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Map LineUps: effects of spatial structure on graphical inference
... Additionally, we did not in this study account for unit shape. This too is likely to result in dissonance between a spatial autocorrelation statistic and its visual perception. This is particularly so where ge- ometric ...
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Map LineUps: effects of spatial structure on graphical inference
... Additionally, we did not in this study account for unit shape. This too is likely to result in dissonance between a spatial autocorrelation statistic and its visual perception. This is particularly so where ge- ometric ...
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Map LineUps: Effects of spatial structure on graphical inference
... Additionally, we did not in this study account for unit shape. This too is likely to result in dissonance between a spatial autocorrelation statistic and its visual perception. This is particularly so where ge- ometric ...
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Statistical inference of the time-varying structure of gene-regulation networks.
... As no particular constraint is imposed to the change- point positions or to the succession in network topologies within phases, the ARTIVA model appears to be highly flexible. The results are not a priori direc- ted ...
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Computational inference of the structure and regulation of the lignin pathway in Panicum virgatum
... pathway structure is often unclear and requires dedicated research for such ...topological structure, it is not surprising that different species have evolved distinct regulatory control ...
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Modelling cofactors in comparative protein structure models by evolutionary inference
... dimensional structure of a protein from its amino acid sequence using homology modelling ...protein structure homology modelling, and has been continuously developed and improved since then [1, 2] [3] ...
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Discovery of low-dimensional structure in high-dimensional inference problems
... Subgraph detection is a difficult problem since connected subgraphs represent a combinatorial structure and systematic approaches to characterizing the space of connected subgraphs of a given graph are relatively ...
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A sequential Monte Carlo algorithm for inference of subclonal structure in cancer
... Genotype assignments validated by the tree structures. One of the advantages of the proposed algorithm is that for each gene, it can consider three different categories of genotype: wild-type, heterozygous and ...
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