Constructing regulatory gene set networks to reveal novel insights into biological systems. - Chayaporn Suphavilai; Liugen Zhu; Jake Y. Chen (ICCABS, 2014)

PAGER: constructing PAGs and new PAG-PAG relationships for network biology. - Zongliang Yue; Madhura M. Kshirsagar; Thanh Nguyen 005; Chayaporn Suphavilai; Michael T. Neylon; Liugen Zhu; Timothy Ratliff; Jake Yue Chen (Bioinform., 2015)

Predicting Cancer Drug Response using a Recommender System. - Chayaporn Suphavilai; Denis Bertrand; Niranjan Nagarajan (Bioinform., 2018)

Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning. - Rafael Peres da Silva; Chayaporn Suphavilai; Niranjan Nagarajan (CoRR, 2020)

Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning (Student Abstract). - Rafael Peres da Silva; Chayaporn Suphavilai; Niranjan Nagarajan (AAAI, 2021)

TUGDA: task uncertainty guided domain adaptation for robust generalization of cancer drug response prediction from in vitro to in vivo settings. - Rafael Peres da Silva; Chayaporn Suphavilai; Niranjan Nagarajan (Bioinform., 2021)

CREAMMIST: an integrative probabilistic database for cancer drug response prediction. - Hatairat Yingtaweesittikul; Jiaxi Wu; Aanchal Mongia; Rafael Peres; Karrie Ko; Niranjan Nagarajan; Chayaporn Suphavilai (Nucleic Acids Res., 2023)

MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes. - Rafael Peres da Silva; Chayaporn Suphavilai; Niranjan Nagarajan (BMC Bioinform., 2024)