Sayali Alatkar

* denotes equal contribution

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
ISMB/ECCB 2025
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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 (Nature Medicine) 2025
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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
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CMOT: Cross-Modality Optimal Transport for multimodal inference.
Sayali Anil Alatkar & Daifeng Wang
Genome Biology 2023
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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
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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
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CMOT: Cross-Modality Optimal Transport for multi-modal inference (poster)
Sayali Anil Alatkar & Daifeng Wang
RECOMB 2022
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