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

Agnosia

品牌

Conference proceedings 2020s conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, addressing theories, methodologies, and applications in science and technology..

Nefarious

0302-9743 me for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, addressing theories, methodologies, and applications in science and technology..978-3-030-60801-9978-3-030-60802-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

容易生皱纹

A Machine Learning Based Method to Identify Differentially Expressed Geneswell as other methods. A validation on the Platinum Spike dataset indicates that the proposed approach is more reliable with high confidence in identifying DEGs. An analysis of the biological function of the identified genes illustrates that the designed ensemble technique is powerful for identifying biologically relevant expression changes.

Pepsin

A New Method Combining DNA Shape Features to Improve the Prediction Accuracy of Transcription Factorch filter to improve the prediction accuracy of TFBSs. We conduct a series of experiments on 66 . datasets and experimental results show that proposed model DCDS is superior to some state-of-the-art methods.

冲击力

Lumbar-Spine

大气层

A Novel Clustering-Framework of Gene Expression Data Based on the Combination Between Deep Learning but also reduced the dimensionality of raw data effectively without any prior knowledge. The clustering results obtained from this method based on four gene datasets exhibited an impressive performance in efficiency and accuracy.

窗帘等

Tumor Gene Selection and Prediction via Supervised Correlation Analysis Based F-Score Methodndancy from those selected genes. At last SVM is introduced to classify those gene subsets. Some experiments are conducted on benchmark tumor gene expressive data sets and results show the performance of the proposed method.

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