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Hi-C data Enhancement and Forecasting using Deep Learning

  1. Mondal, Proloy K.  Oluwadare, O. (2026) HiC-SuperNet: Multi-Scale Attention-Based Deep Learning for High-Resolution Chromatin Contact Map Enhancement. ACM-BCB 2026: 94:1-94:6. Accepted for BCB’26 conference proceedings Rende (CS) Italy
  1. Olowofila, S., and Oluwadare, O (2025). DiCARN-DNase: Enhancing Cell-to-Cell Hi-C Resolution Using Dilated Cascading ResNet with Self-Attention and DNase-seq Chromatin Accessibility Data. Bioinformatics. 
  1. Chandrashekar M. K. B., Menon,  R., Olowofila, S., and Oluwadare, O. (2025). Unicorn: Enhancing Single-Cell Hi-C Data with Blind Super-Resolution for 3D Genome Structure Reconstruction. Bioinformatics. Accepted for ISMB/ECCB 2025 Proceedings. (Acceptance rate: ~17.5%)   
  1. Menon, R., Chowdhury, H. M., & Oluwadare, O. (2025). ScHiCAtt: Enhancing Single-Cell Hi-C Data Resolution Using Attention-Based Models. Computational and Structural Biotechnology Journal.
  1. Pinchuk, D., Chowdhury, H. M. A. M., Pandeya, A., & Oluwadare, O. (2025). HiCForecast: dynamic network optical flow estimation algorithm for spatiotemporal Hi-C data forecasting. Bioinformatics.
  1. Hicks, P., & Oluwadare, O. (2022). HiCARN:Resolution Enhancement of Hi-C Data Using Cascading Residual Network. Bioinformatics. [Won 2nd Place at 2022 President’s Academic Showcase at Concordia University Irvine]
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