Papers
11
Total Citations
173
H-Index
8
About
Kevin Molloy is a computational scientist whose research sits at the intersection of robotics-inspired algorithms, protein biophysics, and motion planning. His work primarily addresses fundamental challenges in protein structure prediction and conformational dynamics, developing innovative computational methods to navigate the notoriously complex energy landscapes of biomolecular systems. Among his most influential contributions is the application of probabilistic search strategies to ab initio protein structure prediction, where his biased decoy sampling framework significantly improves the identification of near-native conformations — work that has garnered nearly 40 citations. Equally notable is his development of robotics-inspired roadmap algorithms for characterizing protein transition pathways between functionally relevant states, reflecting a creative cross-disciplinary approach that has shaped how researchers model protein dynamics. His 2015 work on peptide energy landscapes further demonstrates his breadth, addressing the structural flexibility that underpins peptide biological function. With cumulative citations exceeding 170 across his top publications, Molloy has established a meaningful presence in structural bioinformatics. His more recent explorations into simultaneous system design and path planning suggest an expanding research vision with implications beyond biology, positioning him as a versatile and inventive computational researcher.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5A General, Adaptive, Roadmap-Based Algorithm for Protein Motion Computation15 citations · 2016
- 6Simultaneous system design and path planning: A sampling-based algorithm11 citations · 2018
- 7
- 8Interleaving Global and Local Search for Protein Motion Computation10 citations · 2015
- 9
- 10