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    SynthLens is a visual analytics system that helps researchers design synthetic routes for novel molecules. It aids in exploring multiple reaction possibilities and evaluating them based on various criteria for efficient molecule synthesis.

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    Area of Science:

    • Chemistry
    • Computer Science
    • Data Visualization

    Background:

    • Designing synthetic routes for novel molecules is crucial in medicine and chemistry.
    • Researchers face challenges in selecting optimal reactions and considering their impact on the overall route.

    Purpose of the Study:

    • To introduce SynthLens, a visual analytics system designed to aid researchers in the iterative design of synthetic routes.
    • To facilitate the exploration and evaluation of multiple synthetic reaction possibilities at each step.

    Main Methods:

    • Developed SynthLens, a visual analytics system incorporating a tree-form visualization.
    • The system allows comparison and evaluation of synthetic routes based on multiple criteria (e.g., yield, duration, step count).

    Main Results:

    • SynthLens empowers researchers to comprehensively analyze their construction process.
    • The system guides users toward promising exploration directions for completing synthetic routes.
    • Usability and effectiveness were validated through quantitative evaluation and expert interviews.

    Conclusions:

    • SynthLens effectively facilitates the design process of synthetic routes.
    • The system's insights can inspire visual analytics applications in other multi-criteria decision-making scenarios.