CurvEdgeNet Predicts CircRNA-Disease Links Using Network Geometry
A new computational framework called CurvEdgeNet uses Ollivier-Ricci curvature to predict circRNA-disease associations with high accuracy on three benchmark datasets.
A new computational framework called CurvEdgeNet uses Ollivier-Ricci curvature to predict circRNA-disease associations with high accuracy on three benchmark datasets.
A review in Cell Division evaluates AI and machine learning models for pancreatic cancer diagnosis, highlighting their high reliability in ...
Researchers have developed GallMine, a unified repository integrating multi-omics datasets and published literature to advance computational analysis and therapeutic discovery ...
A literature review finds that machine learning and bioinformatics have improved AML classification and risk stratification, but clinical implementation remains ...
A nested case-control study associated distinct serum protein trajectories with rapid SARS-CoV-2 IgG waning after breakthrough infection in older vaccinated ...
A reversed-phase LC/MS/MS workflow resolved diverse N-glycan isomers in pooled healthy-person urine and created a reference dataset to support future ...
A public-data reanalysis identified broad tumor-normal gene-expression changes in sinonasal squamous cell carcinoma and nominated four preliminary candidate biomarkers supported ...
A retrospective analysis of 1,101 serum samples used explainable artificial intelligence to prioritize circulating microRNAs that distinguished pancreatic cancer from ...
Network analysis and B16F0 cell experiments linked carboplatin with CDKN1A, BRCA1, PTEN and AKT1 in melanoma, without establishing clinical benefit.
Singapore's A*STAR has signed a Memorandum of Understanding with AI digital pathology firm HistoIndex to quantitatively evaluate preclinical therapeutic candidates ...
A new open-source Python package called ROOFS benchmarks multiple feature selection methods on a researcher's own data, evaluating predictive performance ...
In the realm of clinical proteomics, innovative tools are crucial for harnessing the vast amounts of proteomic data generated in ...
In a groundbreaking study that could change our understanding of gynecological health, researchers have delved into the genomic landscape of ...
In a groundbreaking study, researchers have conducted a comprehensive multi-omic profiling of small-cell lung cancer (SCLC), revealing crucial insights into ...
The intersection of artificial intelligence (AI) and extracellular vesicle (EV) biomarker discovery represents an exciting frontier in biomedical research, promising ...
In the ever-evolving field of proteomics, researchers are continuously seeking innovative methodologies to enhance biomarker discovery. Recent advancements have spotlighted ...
In a groundbreaking longitudinal study set to transform our understanding of neurodevelopmental disorders, researchers have meticulously charted the metabolomic landscape ...
In a groundbreaking advancement for cancer diagnostics, researchers have unveiled a plasma protein profiling technique capable of predicting cancer in ...
In a groundbreaking study that promises to reshape our understanding of diabetic retinopathy, researchers have unveiled an unprecedented proteome atlas ...
In the rapidly evolving field of proteomics, researchers are continuously seeking innovative techniques to enhance sensitivity and efficiency in biomarker ...
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