<ul><li>Designing biological sequences with multiple functional and biophysical criteria is a challenging task in biomolecule engineering.</li><li>A new approach called Multi-Objective-Guided Discrete Flow Matching (MOG-DFM) has been introduced to address this challenge.</li><li>MOG-DFM steers discrete-time flow matching generators towards Pareto-efficient trade-offs across multiple objectives by computing hybrid rank-directional scores.</li><li>This framework has been demonstrated to effectively generate peptide binders optimized across five properties and design DNA sequences with specific enhancer classes and shapes.</li></ul>

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design

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