忠诚
发表于 2025-3-21 16:16:22
书目名称Discovery Science影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0281063<br><br> <br><br>书目名称Discovery Science读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0281063<br><br> <br><br>
退出可食用
发表于 2025-3-21 22:33:47
https://doi.org/10.1007/978-94-017-3175-1tion. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.
sebaceous-gland
发表于 2025-3-22 00:56:55
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反复拉紧
发表于 2025-3-22 06:25:38
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reperfusion
发表于 2025-3-22 11:36:22
Using Ontologies in Semantic Data Mining with SEGS and g-SEGS,tion. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.
LATE
发表于 2025-3-22 14:06:02
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LATE
发表于 2025-3-22 20:10:57
Application of Semantic Kernels to Literature-Based Gene Function Annotation, solution to deal with class imbalance. From experiments on the TREC Genomics Track data, our approach achieves better ..-score than two state-of-the-art approaches based on string-matching and cross-species information.
Schlemms-Canal
发表于 2025-3-22 23:03:32
Multiple Hypothesis Testing in Pattern Discovery,ives (Type I error). Our contribution in this paper is to extend the multiple hypothesis framework to be used in a generic data mining setting. We provide a method that provably controls the family-wise error rate (FWER, the probability of at least one false positive). We show the power of our solution on real data.
使高兴
发表于 2025-3-23 02:18:56
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interlude
发表于 2025-3-23 06:40:43
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