MOTIVATION: DNA methylation plays an important role in epigenetic modification, the occurrence, and the development of diseases. Therefore, identification of DNA methylation sites is critical for better understanding and revealing their functional me...
MOTIVATION: Predicting entity relationship can greatly benefit important biomedical problems. Recently, a large amount of biomedical heterogeneous networks (BioHNs) are generated and offer opportunities for developing network-based learning approache...
MOTIVATION: In silico drug-target interaction (DTI) prediction is important for drug discovery and drug repurposing. Approaches to predict DTIs can proceed indirectly, top-down, using phenotypic effects of drugs to identify potential drug targets, or...
SUMMARY: The ability to unveil binding patterns in peptide sets has important applications in several biomedical areas, including the development of vaccines. We present an open-source tool, CNN-PepPred, that uses convolutional neural networks to dis...
How can an agency like the U.S. Food & Drug Administration ("FDA") effectively regulate software that is constantly learning and adapting to real-world data? Continuously learning algorithms pose significant public health risks if a medical device ca...
We describe the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the "human" category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is ent...
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Nov 30, 2021
A software platform for AI-ECG algorithm research is designed and implemented to better serve the research of ECG artificial intelligence classification algorithm and to solve the problem of subjects data information management. Matlab R2019b and MyS...
While glycans are crucial for biological processes, existing analysis modalities make it difficult for researchers with limited computational background to include these diverse carbohydrates into workflows. Here, we present glycowork, an open-source...
MOTIVATION: Traditional regression models are limited in outcome prediction due to their parametric nature. Current deep learning methods allow for various effects and interactions and have shown improved performance, but they typically need to be tr...
MOTIVATION: Digital pathology supports analysis of histopathological images using deep learning methods at a large-scale. However, applications of deep learning in this area have been limited by the complexities of configuration of the computational ...
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