6 papers
Geometric Relevance Is Not Sufficient: Evaluating Focused Post-Training Supervision in Diffusion Docking
Michael Brown, Maryam Rahimimovassagh, Mehdi Yazdani-Jahromi +2
Diffusion-based molecular docking requires learning a corrective score field across a broad corruption distribution, yet individual pose errors can differ substantially in their st…
One Mistake, Three Layers: Persistence Rules Under Depth Correlation
Maryam Rahimimovassagh, Michael Brown, Sanjeda Sara Jennifer +1
Probing frozen representations layer by layer is now standard practice, but reporting when a signal first becomes decodable requires a rule for reading a depth curve, and the obvio…
ORBIT-FMIB: Tracking Order-Resolved Epistatic Information Through ESM-2
Maryam Rahimimovassagh, Ivan Garibay, Waldemar Karwowski +1
Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological interaction information rema…
Beyond Tokens: Probing Higher-Order Epistasis in Learned Protein Representations
Maryam Rahimimovassagh, Ivan Garibay, Niloofar Yousefi
Protein fitness landscapes contain nonlinear interactions in which mutation effects depend on other residues. We introduce ORBIT, an Order-Resolved Benchmarking of Interaction Tran…
BRIDGE: Bottleneck-Aware Regulator-Set Inference and Diagnosis for Cooperative Gene Regulatory Recovery
Maryam Rahimimovassagh, Clayton Thomas Barham, Ivan Garibay +1
Cooperative gene regulation often depends on groups of regulators acting jointly, but most gene regulatory network (GRN) inference methods output pairwise regulator-target rankings…
Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics
Maryam Rahimimovassagh, Md Elias Hossain, Ivan Garibay +1
Electroencephalographic (EEG) abnormalities arise from dynamic changes in neural synchrony across spatial and temporal scales, yet many computational approaches reduce these dynami…