MOTIVATION: Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound identification. However, not all ligands have experimentally determined activities. In particular, many G...
The complex system of gene expression is regulated by the cell type-specific binding of transcription factors (TFs) to regulatory elements. Identifying variants that disrupt TF binding and lead to human diseases remains a great challenge. To address ...
MOTIVATION: Protein O-GlcNAcylation (O-GlcNAc) is an important post-translational modification of serine (S)/threonine (T) residues that involves multiple molecular and cellular processes. Recent studies have suggested that abnormal O-G1cNAcylation c...
A major ambition of artificial intelligence lies in translating patient data to successful therapies. Machine learning models face particular challenges in biomedicine, however, including handling of extreme data heterogeneity and lack of mechanistic...
IEEE transactions on neural networks and learning systems
Jun 1, 2018
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine ...
MOTIVATION: Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontol...
While tens of thousands of pathogenic variants are used to inform the many clinical applications of genomics, there remains limited information on quantitative disease risk for the majority of variants used in clinical practice. At the same time, ris...
MOTIVATION: Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally r...
MOTIVATION: Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networ...
MOTIVATION: While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a tim...
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