收藏品
发表于 2025-3-23 12:03:09
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壕沟
发表于 2025-3-23 16:03:12
a combination of various data sources, e.g. transcriptomic, proteomic, and clinical data. We have integrated clinical data and lung cancer microarray data that were generated on two different oligonucleotide platforms. We were interested in the question whether the prediction of survival outcome ben
Coronation
发表于 2025-3-23 20:18:42
]). In this article, we describe a statistical learning theory-based method to construct lung cancer probability models that are conditioned on gene expression microarray data. Our models do more than classify—they indicate an estimate of the probability. We find our estimate for the conditional pro
Cholecystokinin
发表于 2025-3-24 00:48:55
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ineptitude
发表于 2025-3-24 03:54:30
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态学
发表于 2025-3-24 07:58:29
etween pairs of sample types. We use this data set to analyze methods of determining genes which are likely to be differentially expressed between ALL T-cells and ALL B-cells. To this end, we employ non-parametric methods, in the context of multiple testing, for attaching statistical measures of con
committed
发表于 2025-3-24 13:06:30
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Humble
发表于 2025-3-24 16:29:36
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Habituate
发表于 2025-3-24 20:46:14
s decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. .Methods of Microarray Data Analysis II. is the second book
overhaul
发表于 2025-3-25 01:59:34
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