Modern biomedical research generates knowledge far faster than scientists can organize, evaluate, and translate it into predictive models. BOHEME addresses this challenge through a unified ecosystem of explainable AI tools that bridge the gap between scientific literature and executable biological models. Its modular workflow automatically extracts biological knowledge, identifies experimental context, verifies evidence across public databases, reconciles new findings with existing knowledge, assembles executable mechanistic models, and simulates their behavior to generate new hypotheses. By integrating symbolic reasoning, graph algorithms, mechanistic modeling, and large language models, BOHEME accelerates the transition from biological data to scientific understanding.

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