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Chen V†, Yang M†, Cui W, Kim JS, Talwalkar A*, and Ma J*.
Applying interpretable machine learning in computational biology - pitfalls, recommendations and opportunities for new developments.
Nature Methods, 21(8):1454-1461, 2024.
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Deng Y†, Zhang R†, Xu P, Ma J*, and Gu Q*.
Pre-trained hypergraph convolutional neural networks with self-supervised learning.
Transactions on Machine Learning Research, 2835-8856, 2024.
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Chidester B†, Zhou T†, Alam S, and Ma J.
SPICEMIX enables integrative single-cell spatial modeling of cell identity.
Nature Genetics, 55(1):78-88, 2023. [Cover Article]
RECOMB, 2021.
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Yang Y, Wang Y, Zhang Y, and Ma J.
CONCERT: Genome-wide prediction of sequence elements that modulate DNA replication timing.
bioRxiv, doi: https://doi.org/10.1101/2022.04.21.488684
RECOMB, 2022.
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Zhang R†, Zhou T†, and Ma J.
Ultrafast and interpretable single-cell 3D genome analysis with Fast-Higashi.
Cell Systems, 13(10):P798-807.E6, 2022. [Cover Article]
RECOMB, 2022.
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Zhang R, Zhou T, and Ma J.
Multiscale and integrative single-cell Hi-C analysis with Higashi.
Nature Biotechnology, https://doi.org/10.1038/s41587-021-01034-y, 2021.
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Zhang R, Ma JZ*, and Ma J*.
DANGO: Predicting higher-order genetic interactions.
bioRxiv, doi: https://doi.org/10.1101/2020.11.26.400739
RECOMB, 2021.
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Zhang R, Zou Y, and Ma J.
Hyper-SAGNN: a self-attention based graph neural network for hypergraphs.
ICLR, 2020.
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Chidester B, Zhou T, Do MN, and Ma J.
Rotation equivariant and invariant neural networks for microscopy image analysis.
ISMB, 2019.
Bioinformatics, 35(14):i530-i537, 2019.
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Yang Y, Zhang Y, Ren B, Dixon J, and Ma J.
Comparing 3D genome organization in multiple species using Phylo-HMRF.
Cell Systems, 8(6):494-505.e14, 2019.
RECOMB, 2019.
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Yang Y, Gu Q, Zhang Y, Sasaki T, Crivello J, O'Neill R, Gilbert DM, and Ma J.
Continuous-trait probabilistic model for comparing multi-species functional genomic data.
Cell Systems, 7(2):208-218.e11, 2018.
RECOMB, 2018.
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Singh S, Poczos B, and Ma J.
Minimax reconstruction risk of convolutional sparse dictionary learning.
AISTATS, 2018.
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Chen J, Xu P, Wang L, Ma J, and Gu Q.
Covariate adjusted precision matrix estimation via nonconvex optimization.
ICML, 2018.
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Xu P, Ma J, and Gu Q.
Speeding up latent variable Gaussian graphical model estimation via nonconvex optimizations.
NIPS, 2017.
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Tian D, Gu Q*, and Ma J*.
Identifying gene regulatory network rewiring using latent differential graphical models.
Nucleic Acids Research, 44(17):e140, 2016.