Computational analysis of scientific and molecular knowledge to identify relationships that may support drug repositioning research.
Work can combine literature mining, knowledge graphs, evidence aggregation, drug-target relationships, disease associations, and network analysis.
The resulting systems can support hypothesis generation, evidence exploration, candidate prioritization, and research knowledge discovery.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.