李宗夷

Pan-Disease Classification Using Microbiome Co-occurrence Network-Based Multi-Channel Graph Attention Networks

生物資訊及系統生物研究所

腸道菌群、共現網路、圖注意力網路、泛疾病分類、可解釋人工智慧、Gut microbiome、Co-occurrence network、Graph Attention Network、Pan-disease classification、Explainable AI

KinPhosT5E: Leveraging T5 Protein Language Model Representations and Multi-scale Soft Ensemble Learning for Kinase-Specific Phosphorylation Site Prediction

數據科學與工程研究所

磷酸化位點預測、激酶特異性磷酸化、轉譯後修飾、遷移學習、T5 編碼器、蛋白質語言模型、同源性控制、Phosphorylation Site Prediction、Kinase-Specific Phosphorylation、Post-translational Modification、Transfer Learning、T5 Encoder、Protein Language Model、Homology Control

Pan-Cancer Spatial Transcriptomics Study Reveals Tumor Microenvironment Signatures Associated with Immunotherapy Response

生物資訊及系統生物研究所

空間轉錄體學、免疫檢查點抑制劑、腫瘤微環境、跨癌症分析、配體–受體相互作用、免疫治療抗藥性、spatial transcriptomics、immune checkpoint inhibitor、tumor microenvironment、pan-cancer、ligand–receptor interaction、ICI resistance

DeepFusion-DTI: Structure-Aware Cross-Attention Fusion of Drug and Protein Representations for Drug-Target Interaction Prediction

數據科學與工程研究所

藥物-標靶交互作用預測、結構感知模型、殘基層級接觸圖、結合位點資訊、交叉注意力融合、drug-target interaction prediction、structure-aware model、residue-level contact graph、binding-site information、cross-attention fusion

Integrative Multi-Omics Modeling Reveals Biomarkers of Drug Response in Acute Myeloid Leukemia

生物資訊及系統生物研究所

急性骨髓性白血病、藥物反應預測、磷酸化蛋白體學、多體學整合、生物標誌物探索、Acute Myeloid Leukemia、Drug Response Prediction、Phosphoproteomics、Multi-omics Integration、Biomarker Discovery

A Microbiome Bioinformatics Framework for Corticosteroid Response and Prognostic Assessment in Severe Community-Acquired Pneumonia

生物資訊及系統生物研究所

重症社區型肺炎、肺部菌相、腸肺軸、類固醇治療反應、死亡風險、臨床決策支持、severe community-acquired pneumonia、lung microbiome、gut–lung axis、corticosteroid response、mortality risk、clinical decision support

Homology-guided discovery of antimicrobial peptides from the human gut microbiome

數據科學與工程研究所

抗生素抗藥性、抗菌胜肽、基因體探勘、同源性導向發現、小型開放閱讀框、抗菌活性預測、ADMET 預測、Antimicrobial resistance、Antimicrobial peptides、Genome mining、Homology-guided discovery、smORF、Antimicrobial activity prediction、ADMET prediction

Unraveling B Cell Dynamics and Gene Regulatory Networks Across Lung Adenocarcinoma Stages

生物資訊及系統生物研究所

肺腺癌、單細胞分析、B淋巴細胞、基因表達、軌跡分析、基因調控網路、Lung adenocarcinoma、Single-cell analysis、B lymphocytes、Gene expression、Trajectory analysis、Gene regulatory network、Transcription factors、Cancer progression

Phosphoproteome-derived Pan-cancer Kinase Activity Profiling and Drug Response Association Study

生物資訊及系統生物研究所

磷酸化蛋白質體學、激酶活性、磷酸化位點、泛癌分析、激酶與底物網絡、生物標記物、腫瘤藥物探索、Phosphoproteomics、Kinase activity、Phosphorylation sites、Pan- cancer analysis、Kinase-substrate network、Biomarker discovery、Cancer drug discovery

An Explainable Learning Approach to Predict MicroRNA Expression Levels in Breast Cancer

生物資訊及系統生物研究所

小分子核糖核酸、轉錄因子、輕量級梯度提升框架、單細胞小分 子核糖核酸、轉錄因子-小分子核糖核酸-標靶基因調控網路、miRNA、transcription factors、LightGBM、single-cell miRNA、TF miRNA-target regulatory network

A Multi-modal Hierarchical Graph Neural Network for Diagnosis and Prognosis in Lung Adenocarcinoma using Multi-omics Data

生物資訊及系統生物研究所

肺腺癌、多體學、圖神經網路、自注意力機制、深度學習、Lung adenocarcinoma、Multi-omics、Graph Neural Network、Self-attention、Deep learning

PathGENOS: An Interpretable Deep Learning Framework Combining Gene and Pathway Expression Patterns for Drug Response Prediction

生物資訊及系統生物研究所

藥物敏感性預測、基因表達、GDSC 資料庫、深度學習、生物通路、通路導向建模、精準腫瘤醫學、基因通路關聯、生物解釋性、Drug response prediction、Gene expression、GDSC、Deep learning、Biological pathway、Pathway-informed modeling、Precision oncology、Gene-pathway association、Biological interpretability

Application of machine learning methods on identifying ubiquitination sites and E3-substrate interactions

生物資訊及系統生物研究所

轉譯後修飾、泛素化、機器學習、蛋白質序列、E3-底物交互作用、Post-translational modification、Ubiquitination、Machine learning、Protein sequences、E3-substrate interactions