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Xuehai Hu

Showing results (1-10 of 19) with videos related to

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BMC Bioinformatics|December 4, 2015
Accurate prediction of nuclear receptors with conjoint triad featureHongchu Wang, Xuehai Hu
Current Opinion in Biotechnology|January 14, 2023
Deep learning in regulatory genomics: from identification to designXuehai Hu, Alisdair R Fernie, Jianbing Yan
Plant Biotechnology Journal|April 6, 2019
A directed learning strategy integrating multiple omic data improves genomic predictionXuehai Hu, Weibo Xie, Chengchao Wu, et al.
International Journal of Molecular Sciences|April 10, 2019
Improved Prediction of Regulatory Element Using Hybrid Abelian Complexity Features with DNA SequencesChengchao Wu, Jin Chen, Yunxia Liu, et al.
Bioinformatics (Oxford, England)|January 8, 2021
TSPTFBS: a Docker image for trans-species prediction of transcription factor binding sites in plantsLifen Liu, Ge Zhang, Shoupeng He, et al.
Briefings in Bioinformatics|May 12, 2020
A statistical framework for predicting critical regions of p53-dependent enhancersXiaohui Niu, Kaixuan Deng, Lifen Liu, et al.
International Journal of Molecular Sciences|February 18, 2017
Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in HumanChengchao Wu, Shixin Yao, Xinghao Li, et al.
Frontiers in Genetics|January 24, 2020
A Pretraining-Retraining Strategy of Deep Learning Improves Cell-Specific Enhancer PredictionsXiaohui Niu, Kun Yang, Ge Zhang, et al.
Bio-Medical Materials and Engineering|September 26, 2015
A novel fractal approach for predicting G-protein-coupled receptors and their subfamilies with support vector machinesGuoping Nie, Yong Li, Feichi Wang, et al.
Frontiers in Plant Science|May 25, 2023
TSPTFBS 2.0: trans-species prediction of transcription factor binding sites and identification of their core motifs in plantsHuiling Cheng, Lifen Liu, Yuying Zhou, et al.
Pageof 2

Showing results (1-10 of 19) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|December 4, 2015
Accurate prediction of nuclear receptors with conjoint triad featureHongchu Wang, Xuehai Hu
Current Opinion in Biotechnology|January 14, 2023
Deep learning in regulatory genomics: from identification to designXuehai Hu, Alisdair R Fernie, Jianbing Yan
Plant Biotechnology Journal|April 6, 2019
A directed learning strategy integrating multiple omic data improves genomic predictionXuehai Hu, Weibo Xie, Chengchao Wu, et al.
International Journal of Molecular Sciences|April 10, 2019
Improved Prediction of Regulatory Element Using Hybrid Abelian Complexity Features with DNA SequencesChengchao Wu, Jin Chen, Yunxia Liu, et al.
Bioinformatics (Oxford, England)|January 8, 2021
TSPTFBS: a Docker image for trans-species prediction of transcription factor binding sites in plantsLifen Liu, Ge Zhang, Shoupeng He, et al.
Briefings in Bioinformatics|May 12, 2020
A statistical framework for predicting critical regions of p53-dependent enhancersXiaohui Niu, Kaixuan Deng, Lifen Liu, et al.
International Journal of Molecular Sciences|February 18, 2017
Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in HumanChengchao Wu, Shixin Yao, Xinghao Li, et al.
Frontiers in Genetics|January 24, 2020
A Pretraining-Retraining Strategy of Deep Learning Improves Cell-Specific Enhancer PredictionsXiaohui Niu, Kun Yang, Ge Zhang, et al.
Bio-Medical Materials and Engineering|September 26, 2015
A novel fractal approach for predicting G-protein-coupled receptors and their subfamilies with support vector machinesGuoping Nie, Yong Li, Feichi Wang, et al.
Frontiers in Plant Science|May 25, 2023
TSPTFBS 2.0: trans-species prediction of transcription factor binding sites and identification of their core motifs in plantsHuiling Cheng, Lifen Liu, Yuying Zhou, et al.
Pageof 2