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Zhining Wen

Showing results (21-30 of 53) with videos related to

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Frontiers in Pharmacology|May 14, 2021
Prediction of Synergistic Drug Combinations for Prostate Cancer by Transcriptomic and Network CharacteristicsShiqi Li, Fuhui Zhang, Xiuchan Xiao, et al.
Computational Biology and Chemistry|January 21, 2014
Improving the prediction of chemotherapeutic sensitivity of tumors in breast cancer via optimizing the selection of candidate genesLina Jiang, Liqiu Huang, Qifan Kuang, et al.
Biomed Research International|September 10, 2020
Improving Model Performance on the Stratification of Breast Cancer Patients by Integrating Multiscale Genomic FeaturesYingyi Hao, Li He, Yifan Zhou, et al.
Biomarkers in Medicine|October 27, 2015
Comparative analysis of oncogenes identified by microarray and RNA-sequencing as biomarkers for clinical prognosisYuan Liu, Runyu Jing, Junmei Xu, et al.
BMC Bioinformatics|December 18, 2009
In silico method for systematic analysis of feature importance in microRNA-mRNA interactionsJiamin Xiao, Yizhou Li, Kelong Wang, et al.
Neurological Sciences : Official Journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology|January 19, 2023
A pilot study on identifying gene signatures as markers for predicting patient response to antiseizure medicationsYifei Duan, Liyuan Kang, Yujie He, et al.
Frontiers in Pharmacology|March 14, 2022
Structure-Activity Relationship (SAR) Model for Predicting Teratogenic Risk of Antiseizure Medications in Pregnancy by Using Support Vector MachineLiyuan Kang, Yifei Duan, Cheng Chen, et al.
International Journal of Genomics|August 24, 2017
A New Network-Based Strategy for Predicting the Potential miRNA-mRNA Interactions in TumorigenesisJiwei Xue, Fanfan Xie, Junmei Xu, et al.
Computational Biology and Chemistry|January 23, 2017
Bipartite network analysis reveals metabolic gene expression profiles that are highly associated with the clinical outcomes of acute myeloid leukemiaFanfan Xie, Mingxiong He, Li He, et al.
International Journal of Molecular Sciences|May 14, 2025
A Transfer Learning Framework for Predicting and Interpreting Drug Responses via Single-Cell RNA-Seq DataYujie He, Shenghao Li, Hao Lan, et al.
Pageof 6

Showing results (21-30 of 53) with videos related to

Sort By:
Pageof 6
Frontiers in Pharmacology|May 14, 2021
Prediction of Synergistic Drug Combinations for Prostate Cancer by Transcriptomic and Network CharacteristicsShiqi Li, Fuhui Zhang, Xiuchan Xiao, et al.
Computational Biology and Chemistry|January 21, 2014
Improving the prediction of chemotherapeutic sensitivity of tumors in breast cancer via optimizing the selection of candidate genesLina Jiang, Liqiu Huang, Qifan Kuang, et al.
Biomed Research International|September 10, 2020
Improving Model Performance on the Stratification of Breast Cancer Patients by Integrating Multiscale Genomic FeaturesYingyi Hao, Li He, Yifan Zhou, et al.
Biomarkers in Medicine|October 27, 2015
Comparative analysis of oncogenes identified by microarray and RNA-sequencing as biomarkers for clinical prognosisYuan Liu, Runyu Jing, Junmei Xu, et al.
BMC Bioinformatics|December 18, 2009
In silico method for systematic analysis of feature importance in microRNA-mRNA interactionsJiamin Xiao, Yizhou Li, Kelong Wang, et al.
Neurological Sciences : Official Journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology|January 19, 2023
A pilot study on identifying gene signatures as markers for predicting patient response to antiseizure medicationsYifei Duan, Liyuan Kang, Yujie He, et al.
Frontiers in Pharmacology|March 14, 2022
Structure-Activity Relationship (SAR) Model for Predicting Teratogenic Risk of Antiseizure Medications in Pregnancy by Using Support Vector MachineLiyuan Kang, Yifei Duan, Cheng Chen, et al.
International Journal of Genomics|August 24, 2017
A New Network-Based Strategy for Predicting the Potential miRNA-mRNA Interactions in TumorigenesisJiwei Xue, Fanfan Xie, Junmei Xu, et al.
Computational Biology and Chemistry|January 23, 2017
Bipartite network analysis reveals metabolic gene expression profiles that are highly associated with the clinical outcomes of acute myeloid leukemiaFanfan Xie, Mingxiong He, Li He, et al.
International Journal of Molecular Sciences|May 14, 2025
A Transfer Learning Framework for Predicting and Interpreting Drug Responses via Single-Cell RNA-Seq DataYujie He, Shenghao Li, Hao Lan, et al.
Pageof 6