Bioinformatics Research and Applications

.- Feddaw: Dual Adaptive Weighted Federated Learning for Non-IID Medical Data.

.- LoopNetica: predicting chromatin loops using convolutional neural networks and attention mechanisms.

.- Probabilistic and Machine Learning Models for the Protein Scaffold Gap Filling Problem.

.- Patient Anticancer Drug Response Prediction based on Single-Cell Deconvolution.

.- A Data Set of Paired Structural Segments between Protein Data Bank and AlphaFold DB for Medium-Resolution Cryo-EM Density Maps: A Gap in Overall Structural Quality.

.- PmmNDD: Predicting the Pathogenicity of Missense Mutations in Neurodegenerative Diseases via Ensemble Learning.

.- Improved Inapproximability Gap and Approximation Algorithm for Scaffold Filling to Maximize Increased Duo-preservations.

.- Residual Spatio-Temporal Attention based Prototypical Network for Rare Arrhythmia Classification.

.- SEMQuant: Extending Sipros-Ensemble with Match-Between-Runs for comprehensive quantitative metaproteomics.

.- PrSMBooster Improving the Accuracy of Top-down Proteoform Characterization using Deep Learning Rescoring Models.

.- FCMEDriver: identifing cancer driver gene by combining mutual exclusivity of embedded features and optimized mutation frequency score.