Fatemeh Afrasiabi

University of Massachusetts Boston

Papers

3

Total Citations

13

H-Index

2

About

Fatemeh Afrasiabi is a computational biologist and structural bioinformatics researcher whose work focuses on the challenging problem of exploring protein conformational spaces — the complex, high-dimensional landscapes that govern how proteins move and function at the cellular level. Her research centers on developing and refining algorithmic approaches to simulate and analyze large-scale conformational changes in proteins, work that is critical for understanding biological mechanisms and informing drug discovery efforts. Afrasiabi's most notable contribution is her application of the Rapidly-exploring Random Tree Star (RRT*) algorithm combined with Monte Carlo (MC) methods to efficiently navigate protein conformational pathways — a significant methodological advance in a notoriously difficult computational problem. Her 2020 paper on this approach has garnered 7 citations, establishing her as an emerging voice in the field. Building on this foundation, she subsequently integrated rigidity analysis into the same framework, adding a sophisticated layer of structural constraint modeling that improves both accuracy and computational efficiency, work recognized with additional citations across multiple publications. Afrasiabi's research bridges robotics-inspired motion planning and structural biology, representing an innovative interdisciplinary approach that holds strong promise for deepening our understanding of protein dynamics and intermediate conformational states.

Research Focus

Key Achievements

2
H-Index
3
Papers
13
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Efficient Exploration of Protein Conformational Pathways using RRT* and MC
7 citations · 2020
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: University of Massachusetts Boston

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago