DINIES specifications

Unique identifier:
Web user interface
Input data:
For search: a drug name (e.g., Cathine), a drug ID (e.g., D07627), a protein name (e.g., GABRA), a protein ID (e.g., hsa:4988); For prediction: the data files for drugs or target proteins in the format of either "profile" matrix or "kernel" similarity matrix. Input format: KEGG, MOL, STRING, TXT
Computer skills:
Drug-target Interaction Network Inference Engine based on Supervised Analysis
Restrictions to use:
Output data:
A weighted bipartite graph with drugs and proteins as nodes and prediction scores for drug– protein pairs as edges. The prediction results are provided in the following ways: Inferred list, BRITE mapping, Pathway mapping and Downloadable text files.

DINIES support


  • Susumu Goto <>

Additional information



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Division of System Cohort, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Japan; Institute for Advanced Study, Kyushu University, Higashi-ku, Fukuoka, Japan; Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan; Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan

Funding source(s)

Supported by Ministry of Education, Culture, Sports, Science and Technology of Japan; the Japan Science and Technology Agency and the Japan Society for the Promotion of Science, JSPS KAKENHI grant [25700029], Program to Disseminate Tenure Tracking System, MEXT, Japan and Kyushu University Interdisciplinary Programs in Education and Projects in Research Development.

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