antedate
发表于 2025-3-23 11:23:26
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王得到
发表于 2025-3-23 15:20:10
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变白
发表于 2025-3-23 19:42:09
Integrative Analyses of Single-Cell Multi-Omics Data: A Review from a Statistical Perspectivech area will significantly advance our understanding of complex biological systems and human diseases. Here we review computational methods for analysis and integration of single-cell data across different molecular modalities, and we will emphasize on the statistical aspects of these methods.
PACT
发表于 2025-3-23 22:29:38
Book 2022Latest editionon the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilisti
induct
发表于 2025-3-24 02:40:27
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Watemelon
发表于 2025-3-24 09:41:42
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慢慢啃
发表于 2025-3-24 14:42:00
e also consider dispersion alternatives. The tests are derived in the case of the Spearman and the Hamming distance functions. The latter were chosen to exemplify that different approaches may be needed to obtain the asymptotic distributions under the hypotheses.
生气的边缘
发表于 2025-3-24 17:37:06
Zhenwei Zhou,Xiaoyu Zhang,Peitao Wu,Ching-Ti Liuula and derive some consequences with respect to the two-sample problem. This formula assumes knowledge of the underlying distribution of the random variables and leads to an optimal choice of score functions and subsequently to locally most powerful tests. Hence, for any given underlying distributions, we may obtain the optimal test statistic.
frozen-shoulder
发表于 2025-3-24 19:18:25
Shasha Han,Xiao-Hua Zhoupirit in a reasonable form’, as inappropriate to a muddled civilisation where ‘everything was placed wrong’. (., xxxii, 278) If, as Turner suggests, orderly hypotaxis is a correlative for European civilisation, it is not surprising to find the Forster of . exploring ways to discard or at least disrupt it.
Sciatica
发表于 2025-3-25 01:47:15
Deep Learning Methods for Single-Cell Omics Datas on the low-dimensional space. We also briefly review the losses and penalties that have been proposed in these methods and discuss how they encourage the desired properties on the low-dimensional space.