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Titlebook: Extended Abstracts Fall 2015; Biomedical Big Data; Elizabeth A. Ainsbury,M.Luz Calle,Pere Puig Conference proceedings 2017 Springer Interna

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樓主: GERM
11#
發(fā)表于 2025-3-23 11:04:48 | 只看該作者
New Perspectives in German Political Studiessteopenia, and osteoporosis. A linear mixed model for the MTS is fitted, the estimated ages at osteopenia and osteoporosis onset are imputed, and the transition probabilities between the states are estimated.
12#
發(fā)表于 2025-3-23 14:57:28 | 只看該作者
13#
發(fā)表于 2025-3-23 20:42:01 | 只看該作者
Immigration Detention in the European Unionods, one based on mutual information, and a new one based on clustering the coefficients of fitted curves. The methods are tested on a Cancer Colon study and the biological analysis of the resulting lists suggests that at least some of the genes selected are indeed genes regulated by methylation, opening the door to an automatic mining method.
14#
發(fā)表于 2025-3-23 23:04:06 | 只看該作者
15#
發(fā)表于 2025-3-24 03:52:12 | 只看該作者
Sovereign Bias, Crimmigration, and Risk,an diseases. We propose a pathway analysis approach in which we integrate multiple molecular datasets using multivariate analysis and apply dynamical importance to extract topology-based pathway scores.
16#
發(fā)表于 2025-3-24 07:57:08 | 只看該作者
17#
發(fā)表于 2025-3-24 11:02:19 | 只看該作者
18#
發(fā)表于 2025-3-24 15:29:19 | 只看該作者
19#
發(fā)表于 2025-3-24 20:59:38 | 只看該作者
Integrative Analysis of Transcriptomics and Proteomics Data for the Characterization of Brain Tissuee different levels of the omics cascade are particularly appropriate in these cases and many multivariate methods have been adapted or developed in recent years to taggle this approach. In this work Multiple Co-inertia and Regularized Canonical Correlation with Sparse Partial Least Squares Regressio
20#
發(fā)表于 2025-3-24 23:51:28 | 只看該作者
Applying INAR-Hidden Markov Chains in the Analysis of Under-Reported Datarough a na?ve method based on the theoretical expression of the autocorrelation function of the underlying process, and also by means of the forward algorithm. The hidden process is reconstructed using the Viterbi algorithm, and a real data example is discussed.
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