CAJ
发表于 2025-3-28 16:40:35
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Petechiae
发表于 2025-3-28 21:27:34
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不整齐
发表于 2025-3-29 01:15:02
Inverse Bifurcation Analysis of a Model for the Mammalian , ,/, Regulatory Module, can be used to identify small sets of ”influential” submodules and parameters within a given network. In addition, hierarchical strategies can be used to generate parameter solutions of increasing cardinality of non-zero entries. We apply the proposed methods to analyze a model of the mammalian ../. regulatory module.
ostensible
发表于 2025-3-29 06:54:35
0302-9743 periments for investigating disease pathogenesis, was very inspiring and gave new insights into future bioinformatics challenges.978-3-540-71232-9978-3-540-71233-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
Inveterate
发表于 2025-3-29 08:04:49
Bayesian Inference of Gene Regulatory Networks Using Gene Expression Time Series Datachical prior distribution over interaction strenghts favours sparse networks, enabling the method to efficiently deal with small datasets..Results on a simulated dataset show that our method correctly learns network structure and model parameters even for short time series. Furthermore, we are able
同步信息
发表于 2025-3-29 13:56:58
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陈列
发表于 2025-3-29 19:20:17
Individualized Predictions of Survival Time Distributions from Gene Expression Data Using a Bayesianh, combining a Cox regression model with a hierarchical prior distribution on the regression parameters for feature selection. This prior enables the method to efficiently deal with the low sample number, high dimensionality setting characteristic of microarray datasets. We then sample from the post
maculated
发表于 2025-3-29 20:03:06
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缝纫
发表于 2025-3-30 01:52:35
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打折
发表于 2025-3-30 05:39:33
satDNA Analyzer 1.2 as a Valuable Computing Tool for Evolutionary Analysis of Satellite-DNA Familiesre since every utility is automatized and collected in a single software package, so the user does not need to use different programs. Additionally, it significantly reduces the rate of data miscalculations due to human errors, very prone to occur specially in large files.