M. Kohandel

Conditional Sequence-Structure Integration: A Novel Approach for Precision Antibody Engineering and Affinity Optimization

This paper introduces a method to design antibodies by integrating antigen structure and sequence using a protein structural encoder and antibody language model, achieving better performance than existing methods.

Controlled tumor heterogeneity in a co-culture system by 3D bio-printed tumor-on-chip model

This paper develops a 3D bioprinted tumor-on-chip model to study tumor heterogeneity and cell migration in breast cancer.

Deep Learning Characterization of Brain Tumours With Diffusion Weighted Imaging

This paper develops a deep learning model to estimate GBM tumour parameters and predict progression using MRI data.

Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy

This study uses reinforcement learning to create more robust chemotherapy schedules that outperform classical methods, even when using the same bone marrow measurements.

A mean-field approach for modeling the propagation of perturbations in biochemical reaction networks

The paper develops a mean-field model to predict the temporal behavior of protein expression in response to perturbations in biochemical networks, validated against RNA sequencing data.

Combining Hypoxia-Activated Prodrugs and Radiotherapy in silico: Impact of Treatment Scheduling and the Intra-Tumoural Oxygen Landscape

This paper uses in silico models to show how hypoxia-activated prodrugs and radiotherapy interact, with treatment outcomes depending on scheduling and tumour oxygen levels.