elegans . In this paper we first describe WISTdb, a database designed to store the interaction data generated in Marc Vidal's laboratory. We then describe InterDB, a multi-organism prediction-oriented database of protein-protein interactions. We finally discuss our current approaches, based on ...
elegans. In this paper we first describe WISTdb, a database designed to store the interaction data generated in Marc Vidal’s laboratory. We then describe InterDB, a multi-organism prediction-oriented database of protein-protein interactions. We finally discuss our current approaches, based...
GitHub - masashitsubaki/CPI_prediction: This is a code for compound-protein interaction (CPI) prediction based on a graph neural network (GNN) for compounds and a convolutional neural network (CNN) for proteins. DUD-E数据集: DUD-E: A Database of Useful (Docking) Decoys — Enhanced ...
Proteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein–protein interaction)
MDTips: a multimodal-data-based drug-target interaction prediction system fusing knowledge, gene expression profile, and structural data 2023, Bioinformatics Transfer learning for drug-target interaction prediction 2023, Bioinformatics Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial...
Structural insight of the protein–protein interaction (PPI) interface can provide knowledge about the kinetics, thermodynamics and molecular functions of the complex while elucidating its role in diseases and further enabling it as a potential therapeut
18is a SCL database of bacterial andarchaeaproteins that provides certain clues for drug research and development. PSORTdb is the latest version of Gram-negative bacteria protein SCL that supports subcellular location prediction simultaneously. Notably, the database that was no longer accessible is ...
protein interaction prediction based on a majority voting method. The model uses four well-established machine learning methods: support vector machines, random forests, decision trees, and naive Bayes. In the cross-validation experiment, the ensemble learning method achieved over 80% sensitivity and ...
Lensink, M. F. et al. Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment.Proteins87, 1200–1221 (2019). ArticleCASPubMedPubMed CentralGoogle Scholar Vreven, T. et al. Updates to the integrated protein-protein interaction benchmarks: docking benchmark version...
Protein-protein interaction has proven to be a valuable biological knowledge and starting point for understanding how the cell internally works. In this study we propose a method for PPI prediction using only the primary structure information of protein sequence. The method was developed based on a...