ARTEMIS integrates autoencoders and schrödinger bridges to predict continuous dynamics of gene expression, cell population and perturbation from time-series single-cell data. Sayali Anil Alatkar & Daifeng Wang, Bioinformatics, ECCB 2025 link code

Personalized Single-cell Transcriptomics Reveals Molecular Diversity in Alzheimer’s Disease. Pramod Bharadwaj Chandrashekar*, Sayali Anil Alatkar*, Noah Cohen Kalafut*, Ting Jin*, Chirag Gupta, Ryan Burzak, Xiang Huang, Shuang Liu, Athan Z. Li, PsychAD Consortium, Kiran Girdhar, Georgios Voloudakis, Gabriel E. Hoffman, Jaroslav Bendl, John F. Fullard, Donghoon Lee, Panos Roussos#, Daifeng Wang#, in revision, 2025 link code

NeuroTD: A Time-Frequency Based Multimodal Learning Approach to Analyze Time Delays in Neural Activities. Xiang Huang, Noah Cohen Kalafut, Sayali Alatkar, Athan Z. Li, Qiping Dong, Qiang Chang, Daifeng Wang, (submitted), 2024 link code

CMOT: Cross-Modality Optimal Transport for multimodal inference. Sayali Anil Alatkar & Daifeng Wang, Genome Biology, 2023 link code

DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype–phenotype prediction Pramod Bharadwaj Chandrashekar, Sayali Alatkar, Jiebiao Wang, Gabriel E. Hoffman, Chenfeng He, Ting Jin, Saniya Khullar, Jaroslav Bendl, John F. Fullard, Panos Roussos & Daifeng Wang, Genome Medicine, 2023 link code

Single-cell network biology characterizes cell type gene regulation for drug repurposing and phenotype prediction in Alzheimer’s disease Chirag Gupta, Jielin Xu, Ting Jin, Saniya Khullar, Xiaoyu Liu, Sayali Alatkar, Feixiong Cheng, Daifeng Wang, PLoS Computational Biology, 2022 link

CMOT: Cross-Modality Optimal Transport for multi-modal inference [poster] Sayali Anil Alatkar & Daifeng Wang, RECOMB, 2022 link