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Jiesi Luo

Macrophage cell membrane-based nanoparticles: a new promising biomimetic platform for targeted delivery and treatment
2022 · Yuesong Wu, Shengli Wan, et al. · Journal of Nanobiotechnology · 302
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SecretP: Identifying bacterial secreted proteins by fusing new features into Chou’s pseudo-amino acid composition
2010 · Lezheng Yu, Yanzhi Guo, et al. · Journal of Theoretical Biology · 121
Prediction of CRISPR sgRNA Activity Using a Deep Convolutional Neural Network
2018 · Li Xue, Bin Tang, et al. · Journal of Chemical Information and Modeling · 110
DeepACP: A Novel Computational Approach for Accurate Identification of Anticancer Peptides by Deep Learning Algorithm
2020 · Lezheng Yu, Runyu Jing, et al. · Molecular Therapy — Nucleic Acids · 90
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Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision
2017 · Yungang Xu, Yongcui Wang, et al. · Nucleic Acids Research · 69
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Prediction of activity and specificity of CRISPR-Cpf1 using convolutional deep learning neural networks
2019 · Jiesi Luo, Wei Chen, et al. · BMC Bioinformatics · 51
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DeepT3: deep convolutional neural networks accurately identify Gram-negative bacterial type III secreted effectors using the N-terminal sequence
2018 · Li Xue, Bin Tang, et al. · Bioinformatics · 51
The applications of deep learning algorithms on in silico druggable proteins identification
2022 · Lezheng Yu, Li Xue, et al. · Journal of Advanced Research · 49
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A structural dissection of large protein-protein crystal packing contacts
2015 · Jiesi Luo, Zhongyu Liu, et al. · Scientific Reports · 49
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autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences
2020 · Runyu Jing, Yizhou Li, et al. · Journal of Chemical Information and Modeling · 35
RPI-Bind: a structure-based method for accurate identification of RNA-protein binding sites
2017 · Jiesi Luo, Liang Liu, et al. · Scientific Reports · 32
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Effective Identification of Gram-Negative Bacterial Type III Secreted Effectors Using Position-Specific Residue Conservation Profiles
2013 · Xiaojiao Yang, Yanzhi Guo, et al. · PLoS ONE · 32
Toll-like Receptors and Thrombopoiesis
2023 · Xiaoqin Tang, Qian Xu, et al. · International Journal of Molecular Sciences · 29
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Discovery of a novel megakaryopoiesis enhancer, ingenol, promoting thrombopoiesis through PI3K-Akt signaling independent of thrombopoietin
2022 · Long Wang, Ting Zhang, et al. · Pharmacological Research · 29
Prediction of hot spots residues in protein–protein interface using network feature and microenvironment feature
2013 · Ling Ye, Qifan Kuang, et al. · Chemometrics and Intelligent Laboratory Systems · 25
A functional feature analysis on diverse protein–protein interactions: application for the prediction of binding affinity
2014 · Jiesi Luo, Yanzhi Guo, et al. · Journal of Computer-Aided Molecular Design · 24
Functional classification of secreted proteins by position specific scoring matrix and auto covariance
2011 · Jiesi Luo, Lezheng Yu, et al. · Chemometrics and Intelligent Laboratory Systems · 22
Targeting a thrombopoietin-independent strategy in the discovery of a novel inducer of megakaryocytopoiesis, DMAG, for the treatment of thrombocytopenia
2022 · Long Wang, Sha Liu, et al. · Haematologica · 20
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Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder
2015 · Yuanyuan Fu, Yanzhi Guo, et al. · Computational Biology and Chemistry · 19
DeepT3 2.0: improving type III secreted effector predictions by an integrative deep learning framework
2021 · Runyu Jing, Tingke Wen, et al. · NAR Genomics and Bioinformatics · 18
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DeepT3_4: A Hybrid Deep Neural Network Model for the Distinction Between Bacterial Type III and IV Secreted Effectors
2021 · Lezheng Yu, Fengjuan Liu, et al. · Frontiers in Microbiology · 18
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Genistin: A Novel Estrogen Analogue Targeting ERβ to Alleviate Thrombocytopenia
2024 · Xiaoqin Tang, Rui Liao, et al. · International Journal of Biological Sciences · 17
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layerUMAP: A tool for visualizing and understanding deep learning models in biological sequence classification using UMAP
2022 · Runyu Jing, Li Xue, et al. · iScience · 17
Machine learning to guide the use of plasma technology for antibiotic degradation
2024 · Li Xue, Runyu Jing, et al. · Journal of Hazardous Materials · 15
The combination of machine learning and transcriptomics reveals a novel megakaryopoiesis inducer, MO-A, that promotes thrombopoiesis by activating FGF1/FGFR1/PI3K/Akt/NF-κB signaling
2023 · Ting Zhang, Qi Mo, et al. · European Journal of Pharmacology · 15
Works count: 84
Citation count: 1,486
H-index: 19
I10-index: 36
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