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Selected Publications ▮ complete list

  • Chen V, Yang M, Cui W, Kim JS, Talwalkar A*, and Ma J*.
    On the pitfalls of applying interpretable machine learning in computational biology.
    Nature Methods, accepted in principle
  • Zhou T, Zhang R, Jia D, Doty RT, Munday AD, Gao D, Xin L, Abkowitz JL, Duan Z*, and Ma J*.
    GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells.
    Nature Genetics,, 2024.
  • Xiong K, Zhang R, and Ma J.
    scGHOST: Identifying single-cell 3D genome subcompartments.
    Nature Methods, 21(5):814-822, 2024.
  • Deng Y, Zhang R, Xu P, Ma J*, and Gu Q*.
    PhyGCN: Pre-trained gypergraph convolutional neural networks with self-supervised learning.
    bioRxiv, doi:
  • Zhang Y, Boninsegna L, Yang M, Misteli T*, Alber F*, and Ma J*.
    Computational methods for analysing multiscale 3D genome organization.
    Nature Reviews Genetics, 25(2):123-141, 2024.
  • Yang M and Ma J.
    UNADON: Transformer-based model to predict genome-wide chromosome spatial position.
    ISMB, 2023.
    Bioinformatics, 39(39 Suppl 1):i553-i562, 2023.
  • 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.
  • Zhu X, Zhang Y, Wang Y, Tian D, Belmont AS, Swedlow JR, and Ma J.
    Nucleome Browser: An integrative and multimodal data navigation platform for 4D Nucleome.
    Nature Methods, 19(8):911-913, 2022.
  • Yang Y, Wang Y, Zhang Y, and Ma J.
    CONCERT: Genome-wide prediction of sequence elements that modulate DNA replication timing.
    bioRxiv, doi:
    RECOMB, 2022.
  • 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.
  • Zhang R, Zhou T, and Ma J.
    Multiscale and integrative single-cell Hi-C analysis with Higashi.
    Nature Biotechnology, 40:254–261, 2022.
  • Zhang R, Ma JZ*, and Ma J*.
    DANGO: Predicting higher-order genetic interactions.
    bioRxiv, doi:
    RECOMB, 2021.
  • Wang Y, Zhang Y, Zhang R, van Schaik T, Zhang L, Sasaki T, Peric-Hupkes D, Chen Y, Gilbert DM, van Steensel B, Belmont AS, and Ma J.
    SPIN reveals genome-wide landscape of nuclear compartmentalization.
    Genome Biology, 22:36, 2021.
  • Zhang L, Zhang Y, Chen Y, Gholamalamdari O, Wang Y, Ma J, and Belmont AS.
    TSA-seq reveals a largely conserved genome organization relative to nuclear speckles with small position changes tightly correlated with gene expression changes.
    Genome Research, 31(2):251-264, 2021.
  • Tao Y, Rajaraman A, Cui X, Cui Z, Eaton J, Kim H, Ma J*, and Schwartz R*.
    Assessing the contribution of tumor mutational phenotypes to cancer progression risk.
    PLOS Computational Biology, 17(3):e1008777, 2021.
  • Zhang Y, Xiao Y, Yang M, and Ma J.
    Cancer mutational signatures representation by large-scale context embedding.
    ISMB, 2020.
    Bioinformatics, 36(Supplement_1):i309-i316, 2020.
  • Zhang R and Ma J.
    MATCHA: Probing multi-way chromatin interaction with hypergraph representation learning.
    Cell Systems, 10(5):397-407.E5, 2020.
    RECOMB, 2020.
  • Tian D, Zhang R, Zhang Y, Zhu X, and Ma J.
    MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome.
    Genome Research, 30(2):227-238, 2020. [Cover Article]
  • Lazzarotto CR, Malinin NL, Li Y, Zhang R, Yang Y, Lee G, Cowley E, He Y, Lan X, Jividen K, Katta V, Kolmakova NG, Petersen CT, Qi Q, Strelcov E, Maragh S, Krenciute G, Ma J, Cheng Y, and Tsai SQ.
    CHANGE-seq reveals genetic and epigenetic effects on CRISPR–Cas9 genome-wide activity.
    Nature Biotechnology, 38(11):1317-1327, 2020.
  • Zhang R, Zou Y, and Ma J.
    Hyper-SAGNN: a self-attention based graph neural network for hypergraphs.
    ICLR, 2020.
  • Xiong K and Ma J.
    Revealing Hi-C subcompartments by imputing inter-chromosomal chromatin interactions.
    Nature Communications, 10, 5069, 2019.
  • 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.
  • Ma J and Duan Z.
    Replication timing becomes intertwined with 3D genome organization.
    Cell, 176(4):681-684, 2019 (Preview).
  • 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.
  • Singh S, Poczos B, and Ma J.
    Minimax reconstruction risk of convolutional sparse dictionary learning.
    AISTATS, 2018.
  • 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.
  • Chen Y, Zhang Y, Wang Y, Zhang L, Brinkman EK, Adam SA, Goldman R, van Steensel B, Ma J, and Belmont AS.
    Mapping 3D genome organization relative to nuclear compartments using TSA-Seq as a cytological ruler.
    Journal of Cell Biology, 217(11):4025-4048, 2018.
  • Chen J, Xu P, Wang L, Ma J, and Gu Q.
    Covariate adjusted precision matrix estimation via nonconvex optimization.
    ICML, 2018.
  • Zhang R, Wang Y, Yang Y, Zhang Y, and Ma J.
    Predicting CTCF-mediated chromatin loops using CTCF-MP.
    ISMB, 2018.
    Bioinformatics, 34(13):i133–i141, 2018.
  • Yang Y, Zhang R, Singh S, and Ma J.
    Exploiting sequence-based features for predicting enhancer-promoter interactions.
    ISMB, 2017.
    Bioinformatics, 33(14): i252-i260, 2017.
  • Kim J, Farre MB, Auvil L, Capitanu B, Larkin D*, Ma J*, and Lewin HA*.
    Reconstruction and evolutionary history of eutherian chromosomes.
    PNAS, 114(27) E5379-E5388, 2017.
  • Rajaraman A and Ma J.
    Towards recovering allele-specific cancer genome graphs.
    RECOMB, 2017.
  • Xu P, Ma J, and Gu Q.
    Speeding up latent variable Gaussian graphical model estimation via nonconvex optimizations.
    NIPS, 2017.
  • Tian D, Gu Q*, and Ma J*.
    Identifying gene regulatory network rewiring using latent differential graphical models.
    Nucleic Acids Research, 44(17):e140, 2016.
  • Li Y, Zhou S, Schwartz DC, and Ma J.
    Allele-specific quantification of structural variations in cancer genomes.
    Cell Systems, 3(1):21-34, 2016.
    RECOMB, 2016.
  • Hou JP, Emad A, Puleo GJ, Ma J*, and Milenkovic O*.
    A new correlation clustering method for cancer mutation analysis.
    Bioinformatics, 32(24):3717-28, 2016.
  • Kim Y-C, Byun S, Zhang Y, Seok S, Kemper BW, Ma J*, and Kemper JK*.
    Liver ChIP-seq analysis in FGF19-treated mice reveals SHP as a global transcriptional partner of SREBP-2.
    Genome Biology, 16:268, 2015.
  • Seok S, Fu T, Choi SE, Li Y, Zhu R, Kumar S, Sun X, Yoon G, Kang Y, Zhong W, Ma J, Kemper B, and Kemper JK.
    Transcriptional regulation of autophagy by an FXR-CREB axis.
    Nature, 516(7529):108-11, 2014.
  • Yokoyama KD, Zhang Y, and Ma J.
    Tracing the evolution of lineage-specific transcription factor binding sites in a birth-death framework.
    PLOS Computational Biology, 10(8): e1003771, 2014.
  • Hou JP and Ma J.
    DawnRank: Discovering personalized driver genes in cancer.
    Genome Medicine, 6:56, 2014.
  • Liu Y, Gu Q, Hou JP, Han J, and Ma J.
    A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression.
    BMC Bioinformatics, 15:37, 2014.
  • Kim J and Ma J.
    PSAR-Align: improving multiple sequence alignment using probabilistic sampling.
    Bioinformatics, 30(7):1010-2, 2014.
  • Heo Y, Wu X-L, Chen D, Ma J, and Hwu W-M.
    BLESS: Bloom filter-based error correction solution for high-throughput sequencing reads.
    Bioinformatics, 30(10):1354-62, 2014.
  • Kim J, Larkin DM, Cai Q, Asan, Zhang Y, Ge RL, Auvil L, Capitanu B, Zhang G, Lewin HA*, and Ma J*.
    Reference-assisted chromosome assembly.
    PNAS, 110(5):1785-90, 2013.
  • Li-Byarlay H, Li Y, Stroud H, Feng S, Newman TC, Kaneda M, Hou KK, Worley KA, Elsik C, Wickline SA, Jacobsen SE, Ma J, and Robinson GE.
    RNA interference knockdown of DNA methyl-transferase 3 affects gene alternative splicing in the honey bee.
    PNAS, 110(31):12750-5, 2013.
  • Li Y, Li-Byarlay H, Burns P, Borodovsky M, Robinson GE, and Ma J.
    TrueSight: a new algorithm for splice junction detection using RNA-seq.
    Nucleic Acids Research, 41(4):e51, 2013.
    RECOMB, 2012.
  • Kim J and Ma J.
    PSAR: Measuring multiple sequence alignment reliability by probabilistic sampling.
    Nucleic Acids Research, 39(15):6359-68, 2011.
    RECOMB, 2011.
  • Li Y, Chien J, Smith DI, and Ma J.
    FusionHunter: identifying fusion transcripts in cancer using paired-end RNA-seq.
    Bioinformatics, 27(12):1708-10, 2011.
  • Orangutan Genome Sequencing and Analysis Consortium.
    Comparative and demographic analysis of orangutan genomes.
    Nature, 469(7331):529-33, 2011.
  • Ma J, Ratan A, Raney BJ, Suh BB, Miller W, and Haussler D.
    The infinite sites model of genome evolution.
    PNAS, 105(38):14254-14261, 2008.
  • Ma J, Ratan A, Raney BJ, Suh BB, Zhang L, Miller W, and Haussler D.
    DUPCAR: Reconstructing contiguous ancestral regions with duplications.
    Journal of Computational Biology, 15(8):1007-1027, Oct 2008.
  • Ma J, Zhang L, Suh BB, Raney BJ, Burhans RC, Kent WJ, Blanchette M, Haussler D, and Miller W.
    Reconstructing contiguous regions of an ancestral genome.
    Genome Research, 16(12):1557-1565, 2006.