Jian Peng
Affiliations: | 2007-2013 | Computer Science | Toyota Technological Institute |
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| Su Y, Luo Y, Zhao X, et al. (2019) Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction. Plos Computational Biology. 15: e1007283 |
| Cai Y, Guan K, Lobell D, et al. (2019) Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches Agricultural and Forest Meteorology. 274: 144-159 |
| Shang J, Jiang M, Tong W, et al. (2018) DPPred: An Effective Prediction Framework with Concise Discriminative Patterns. Ieee Transactions On Knowledge and Data Engineering. 30: 1226-1239 |
| Liu Y, Ye Q, Wang L, et al. (2018) Learning structural motif representations for efficient protein structure search. Bioinformatics (Oxford, England). 34: i773-i780 |
| Liu Y, Palmedo P, Ye Q, et al. (2017) Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks. Cell Systems |
| Luo Y, Zhao X, Zhou J, et al. (2017) A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information. Nature Communications. 8: 573 |
| Ma X, Zhou G, Shang J, et al. (2017) Detection of Complexes in Biological Networks Through Diversified Dense Subgraph Mining. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology |
| Cho H, Berger B, Peng J. (2016) Compact Integration of Multi-Network Topology for Functional Analysis of Genes. Cell Systems |
| Wang S, Peng J, Ma J, et al. (2016) Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields. Scientific Reports. 6: 18962 |
| Simmons S, Peng J, Bienkowska J, et al. (2015) Discovering What Dimensionality Reduction Really Tells Us About RNA-Seq Data. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 22: 715-28 |