Artificial Intelligence for Bone: Theory, Methods, and Applications
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
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Integrating scRNA-seq and machine learning identifies MNAT1 as a therapeutic target in OSCC. [PDF]
Gao H +6 more
europepmc +1 more source
Correction: Mast cell marker gene signature: prognosis and immunotherapy response prediction in lung adenocarcinoma through integrated scRNA-seq and bulk RNA-seq. [PDF]
Zhang P +6 more
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Correction to: Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy. [PDF]
He S +7 more
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Identify Diagnostic Biomarkers Related to Taurine Metabolism in Diabetic Foot Ulcers Using Bulk RNA-seq and ScRNA-seq Analysis. [PDF]
He M, Chen J.
europepmc +1 more source
Multiomic, Histologic, and scRNA-seq Profiling of Pleural Mesothelioma Reveals Negative Prognosis Associated With a Novel Uncommitted Molecular Phenotype. [PDF]
Severson DT +23 more
europepmc +1 more source
ScRNA-Seq and BCR Analysis of Murine Immune Responses to Inactivated DHAV-1 as a Model Antigen
Yaru Fan +8 more
openalex +1 more source
Integration of scRNA-Seq and scATAC-Seq Reveals Malignant Characteristics of Sarcomatoid Clear Cell Renal Cell Carcinoma. [PDF]
Lu W +10 more
europepmc +1 more source
Correction to 'Immunopipe: a comprehensive and flexible scRNA-seq and scTCR-seq data analysis pipeline'. [PDF]
europepmc +1 more source

