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2. Generic protein–ligand interaction scoring by integrating physical prior knowledge and data augmentation modelling

7. Identify compound-protein interaction with knowledge graph embedding of perturbation transcriptomics

9. In silico off-target profiling for enhanced drug safety assessment

11. Targeting JMJD1C to selectively disrupt tumor Treg cell fitness enhances antitumor immunity

12. Fine-tuning Large Language Models for Chemical Text Mining

14. Fine-tuning Large Language Models for Chemical Text Mining

16. KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling

19. LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP

20. PBCNet:Computing Relative Binding Affinity of Ligands to a Receptor Based on a Pairwise Binding Comparison Network for Lead Optimization

21. MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules

22. Structural Optimization of Fibroblast Growth Factor Receptor Inhibitors for Treating Solid Tumors

25. Author Correction: Engineered bioorthogonal POLY-PROTAC nanoparticles for tumour-specific protein degradation and precise cancer therapy

33. Targeted creation of new mutants with compact plant architecture using CRISPR/Cas9 genome editing by an optimized genetic transformation procedure in cucurbit plants

37. Discovery of Pyrazolo[3,4-d]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation

38. Active Learning for Drug Design: A Case Study on the Plasma Exposure of Orally Administered Drugs

39. Drug target inference by mining transcriptional data using a novel graph convolutional network framework

42. Generative Models for De Novo Drug Design

45. Cytoplasmic DNA sensing by KU complex in aged CD4+ T cell potentiates T cell activation and aging-related autoimmune inflammation

47. Single Calibration Technique of Autocorrelator Based on a Flat Crystal

49. Automated design and optimization of multitarget schizophrenia drug candidates by deep learning

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