All Stories

  1. Attenuation of antigen-specific T helper 1 immunity by Neolitsea hiiranensis and its derived terpenoids
  2. ChemDIS: a chemical–disease inference system based on chemical–protein interactions
  3. Developing a QSAR model for hepatotoxicity screening of the active compounds in traditional Chinese medicines
  4. Public Databases of Plant Natural Products for Computational Drug Discovery
  5. Interpretable prediction of non-genotoxic hepatocarcinogenic chemicals
  6. An in silico toxicogenomics approach for inferring potential diseases associated with maleic acid
  7. A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the ‘rule-of-two’ model
  8. Databases for T-Cell Epitopes
  9. Acquiring Decision Rules for Predicting Ames-Negative Hepatocarcinogens Using Chemical-Chemical Interactions
  10. Prediction of pupylation sites using the composition of k-spaced amino acid pairs
  11. Prediction and Analysis of Antibody Amyloidogenesis from Sequences
  12. Prediction of Non-genotoxic Hepatocarcinogenicity Using Chemical-Protein Interactions
  13. PupDB: a database of pupylated proteins
  14. POPISK: T-cell reactivity prediction using support vector machines and string kernels
  15. Predicting protein subnuclear localization using GO-amino-acid composition features
  16. ProLoc-rGO: Using rule-based knowledge with Gene Ontology terms for prediction of protein subnuclear localization
  17. Computational identification of ubiquitylation sites from protein sequences
  18. ProLoc: Prediction of protein subnuclear localization using SVM with automatic selection from physicochemical composition features
  19. POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties