Titlebook: Intelligent Computing Theories and Application; 16th International C De-Shuang Huang,Kang-Hyun Jo Conference proceedings 2020 Springer Natu

CHORD

書目名稱Intelligent Computing Theories and Application影響因子(影響力)




書目名稱Intelligent Computing Theories and Application影響因子(影響力)學科排名




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書目名稱Intelligent Computing Theories and Application網(wǎng)絡公開度學科排名




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書目名稱Intelligent Computing Theories and Application被引頻次學科排名




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書目名稱Intelligent Computing Theories and Application讀者反饋學科排名

Rejuvenate

DEI

Na Gao,Chen Qiao,Shun Qi,Kai Ren,Jian Chen,Hanfeng Fangmuliert, hat sich der Ausdruck in der neueren Entwicklungsphysiologie auf zoologischer Seite fest eingebürgert; er wird auch von Winkler in seiner Zusammenfassung der Ergebnisse der pflanzlichen Entwicklungsphysiologie (1913) in diesem Sinne verwendet, nachdem bisher in der botanischen Literatur ein

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FLACK

CBC471

Tumor Gene Selection and Prediction via Supervised Correlation Analysis Based F-Score Methodposed. Firstly, all the genes are sorted as their descending F-scores, and then supervised correlation analysis is also recommended to reduce the redundancy from those selected genes. At last SVM is introduced to classify those gene subsets. Some experiments are conducted on benchmark tumor gene exp

single

斷言

Multi-omics Classification on Kidney Samples Exploiting Uncertainty-Aware Modelsconsists of creating a classifier for each omic and subsequently making a consensus among the classifiers that assigns to each sample the most voted class among the outputs on the individual omics..However, this approach does not consider the confidence in the prediction ignoring that a biological i

Eclampsia

dermatomyositis

Exploring lncRNA-MRNA Regulatory Modules Based on lncRNA Similarity in Breast Cancerincluding breast cancer. The development of computational methods to identify lncRNA-related modules is a powerful tool to reveal the role of lncRNA in diseases. Here, we proposed a novel computational method called BCLMM to identify lncRNA-mRNA modules of breast cancer based on lncRNA similarity. F