Tools

• iPhDNet (integrated Phosphoprotein Histone Drug Network)
  S. A. Mollah and S. Subramaniam, “Histone Signatures Predict Therapeutic Efficacy in Breast Cancer”. 2020, IEEE Open Journal of Engineering in Medicine and Biology, vol. 1, pp. 74-82.  (doi.org/10.1109/OJEMB.2020.2967105)

• Gen3DNet ( Generic 3D Network derived from iPhDNet, coming soon… )
   
• HOCMO (Higher-Order Correlation Model)
  Min Shi, Rintsen Sherpa, Liubou Klindziuk, Stefanie Kriel, Shamim Mollah. “A Non-Negative Tensor Factorization Approach to Deconvolute Epigenetic Microenvironment in Breast Cancer”. 2020. (doi.org/10.1101/2020.12.01.406249)

• NeTOIF (Network-based Approach for Time-Series Omics Data Imputation and Forecasting) 
  Min Shi and Shamim Mollah. “NeTOIF: A Network-based Approach for Time-Series Omics Data Imputation and Forecasting.”. 2021. (doi.org/10.1101/2021.06.05.447209)
  

• PBHSCM (Peripheral Blood Hematopoietic Stem Cell Mobilization score)
  Xiang J, Shi M, Fiala MA, Gao F, Rettig MP, Uy GL, Schroeder MA, Weilbaecher KN, Stockerl-Goldstein K, Mollah S, DiPersio JF. Machine learning-based scoring models to predict hematopoietic stem cell mobilization in allogeneic donors. Blood Adv. 2021 Sep 23:bloodadvances.2021005149. (doi:10.1182/bloodadvances.2021005149) PMID: 34555850.  

• CREWdb (Chromatin  Reader Eraser Writer Database)
  Maya Natesan, Mitchelle Kong, Min Shi, Reetika Ghaag, Shamim Mollah. “CREWdb 1.0: Optimizing Chromatin Readers, Erasers, and Writers Database using Machine Learning-Based Approach”. 2022. (doi.org/10.1101/2022.06.02.494594)