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Disambiguation of "Li, Li-Ping"

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Precise Prediction of Pathogenic Microorganisms Using 16S rRNA Gene Sequences.

, , , , , , and . ICIC (2), volume 11644 of Lecture Notes in Computer Science, page 138-150. Springer, (2019)

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Ping Li

Ping Li

Ping Li

Ping Li

Ping-Lu Li

 

Other publications of authors with the same name

The LAMOST Survey of Background Quasars in the Vicinity of the Andromeda and Triangulum Galaxies -- II. Results from the Commissioning Observations and the Pilot Surveys, , , , , , , , , and 61 other author(s). (2013)cite arxiv:1304.3174Comment: 26 pages, 6 figures, AJ accepted.BCMCMI: A Fusion Model for Predicting circRNA-miRNA Interactions Combining Semantic and Meta-path., , , , and . J. Chem. Inf. Model., 63 (16): 5384-5394 (August 2023)A feature extraction method based on noise reduction for circRNA-miRNA interaction prediction combining multi-structure features in the association networks., , , , , , , and . Briefings Bioinform., (May 2023)Combining High Speed ELM with a CNN Feature Encoding to Predict LncRNA-Disease Associations., , , , and . ICIC (2), volume 11644 of Lecture Notes in Computer Science, page 406-417. Springer, (2019)Inferring Drug-miRNA Associations by Integrating Drug SMILES and MiRNA Sequence Information., , , , , and . ICIC (2), volume 12464 of Lecture Notes in Computer Science, page 279-289. Springer, (2020)WGMFDDA: A Novel Weighted-Based Graph Regularized Matrix Factorization for Predicting Drug-Disease Associations., , , , and . ICIC (3), volume 12465 of Lecture Notes in Computer Science, page 542-551. Springer, (2020)Precise Prediction of Pathogenic Microorganisms Using 16S rRNA Gene Sequences., , , , , , and . ICIC (2), volume 11644 of Lecture Notes in Computer Science, page 138-150. Springer, (2019)Predicting Protein-Protein Interactions from Protein Sequence Information Using Dual-Tree Complex Wavelet Transform., , , , and . ICIC (2), volume 12464 of Lecture Notes in Computer Science, page 132-142. Springer, (2020)A computational approach for predicting drug-target interactions from protein sequence and drug substructure fingerprint information., , , , , and . Int. J. Intell. Syst., 36 (1): 593-609 (2021)Predicting circRNA-disease associations using deep generative adversarial network based on multi-source fusion information., , , , and . BIBM, page 145-152. IEEE, (2019)