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Lab members are underlined.

denotes equal contribution   * denotes co-corresponding authors.

use Xin Maizie Zhou (X. M. Zhou) for publications since 2023.

Preprints/under review

Parallel signatures of cognitive maturation in primate antisaccade performance and prefrontal activity.

J. Zhu, X. M. ZhouC. Constantinidis, E. Salinas, T. R. Stanford.



A speed-performance tradeoff in alignment and assembly-based methods for structural variant detection with long-read sequencing data.

Y. H. LiuC. Luo†, S. G. Golding, J. B. Ioffe, X. M. Zhou.

Preprint (2022)


Peer-reviewed Publications


ADEPT: autoencoder with differentially expressed genes and imputation for robust spatial transcriptomics clustering.

Y. Hu, Y. Zhao, C. T. Schunk, Y. Ma, T. Derr*, X. M. Zhou*.

RECOMB-Seq 2023, iScience  (2023) 26(6), 106792. 


Haplotyping-assisted diploid assembly and variant detection with linked-reads. 

Y. Hu, C. Yang, L. Zhang*, X. Zhou*.

Methods Mol Biol (2023) 2590:161-182. doi: 10.1007/978-1-0716-2819-5_1. PMID: 36335499.



Haplotype-phasing of long-read HiFi data to enhance structural variant detection through a Skip-Gram model.

C. Luo, P. A. Datar, Y. H. Liu, X. Zhou.

IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 2022, pp. 2326-2333, doi: 10.1109/BIBM55620.2022.9995293.


A comprehensive investigation of statistical and machine learning approaches for predicting complex human diseases on genomic variants.

C. Wang, J. Zhang, X. Zhou, L. Zhang.

Briefings in Bioinformatics (2022) bbac552.


Automated filtering of genome-wide large deletions through an ensemble deep learning framework. 

Y. Hu, S. Mangal, L. Zhang, X. Zhou.

Methods (2022) 206, 77-86.


Graphing cell relations in spatial transcriptomics.

X. Zhou.

Nature Computational Science (2022) 2, 354-355.


Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA reveals novel spatial biology.

W. Zhang, I. Li, N. E. Reticker-Flynn, Z. Good, S. Chang, N. Samusik, S. Saumyaa, Y. Li, X. Zhou, et al.

Nature Methods (2022) 9, 759–769.


Strong gamma frequency oscillations in the adolescent prefrontal cortex.

Z. Wang, B. Singh, X. Zhou*, C. Constantinidis*.   (* co-corresponding and co-senior authors)

Journal of Neuroscience (2022) 42 (14) 2917-2929.


Benchmarking challenging small variants with linked and long reads. 

J. Wagner, N. D. Olson…, X. Zhou,…, J. Zook.

Cell Genomics (2022) 2(5), 100128.


Neural mechanisms of working memory accuracy revealed by recurrent neural networks.

Y. Xie, Y. H. Liu, C. Constantinidis, X. Zhou.

Front. Syst. Neurosci. (2022) 16:760864.


A Bayesian factorization method to recover single-cell RNA sequencing data.

Z.-H. Wen, J. L. Langsam, L. Zhang, W. Shen*, X. Zhou*.

Cell Reports Methods (2022) 2, 100133.



An ensemble deep learning framework to refine large deletions in linked-reads.

Y. Hu, S. V. Mangal, L. Zhang, X. Zhou.

IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2021), pp. 288-295, doi: 10.1109/BIBM52615.2021.9669571.  (acceptance rate: 19.3%)


The epithelial and stromal immune microenvironment in gastric cancer: a comprehensive analysis reveals prognostic factors with digital cytometry.

W. Shen, G. Wang, G. R. Cooper, Y. Jiang, X. Zhou.

Cancers (Basel) (2021) 13(21):5382.


Emergence of prefrontal neuron maturation properties by training recurrent neural networks in cognitive tasks.

Y. H. Liu, J. Zhu, C. Constantinidis, X. Zhou.

iScience (2021) 24(10):103178.


Structural variant detection in region-based phased diploid assemblies from linked-reads.

C. Luo and X. Zhou.

The International Symposium on Bioinformatics Research and Applications (ISBRA) (2021) (acceptance rate: 17.6%) [PDF][SI]


Editorial: predicting high-risk individuals for common diseases using multi-omics and epidemiological data.

D. Chowdhury, X. Zhou, B. Li, Y. Zhang, W. K. Cheung, A. Lyu, L. Zhang.

Front. Genet. (2021) 12:737598.


DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-Seq Data.

J. Chen, C. Cheong, L. Lan, X. Zhou, J. Liu, A. Lyu, W. K. Cheung, L. Zhang.

Briefings in Bioinformatics (2021), 22(6):bbab325.


Text mining of gene-phenotype associations reveals new phenotypic profiles of autism-associated genes.

S. Li, Z. Guo, J. B. Ioffe, Y. Hu, Y. Zhen*, X. Zhou*.       ( equal contribution)

Scientific Reports (2021) 11(1):15269.


Aquila_stLFR: diploid genome assembly based structural variant calling package for stLFR linked-reads.

Y.H. Liu, G. L. Grubbs, L. Zhang, X. Fang, D. L. Dill, A. Sidow, X. Zhou.

Bioinformatics Advances (2021) 1, vbab007.


Aquila enables reference-assisted diploid personal genome assembly and comprehensive variant detection based on linked-reads. 

X. Zhou*, L. Zhang,  Z. Weng, D. L. Dill, A. Sidow*.   (* co-corresponding authors)

Nature Communications (2021) 12:1077.


2020 and earlier

A comprehensive investigation of metagenome assembly by linked-read sequencing.

L. Zhang, X. Fang, H. Liao, Z. Zhang, X. Zhou, L. Han, Y. Chen, Q. Qiu, S. C. Li.

Microbiome (2020) 8(1), 1-11.


A diploid assembly-based benchmark for variants in the major histocompatibility complex. 

C. Chin, J. Wagner,…, X. Zhou,…, J. Zook.

Nature Communications (2020) 11:4794.


De novo diploid genome assembly for genome-wide structural variant detection. 

L. ZhangX. Zhou, Z. Weng, A. Sidow.       ( equal contribution)

NAR Genomics and Bioinformatics (2020) 2(1)1-10.


Plasticity of persistent activity and its constraints.

S. Li, X. Zhou, C. Constantinidis, X.-L. Qi.

Frontiers in Neural Circuits (2020) 14: 15.


Assessment of human diploid genome assembly with 10x Linked-Reads data.

L. ZhangX. Zhou, Z. Weng, A. Sidow.     ( equal contribution)

GigaScience (2019) 8:1-11. 


Assessment of network module identification across complex diseases. 

S. Choobdar et al.

Nature Methods (2019) 16:843-852.


HAPDeNovo: a haplotype-based approach for filtering and phasing de novo mutations in linked read sequencing data. 

X. Zhou, S. Batzoglou, A. Sidow, L. Zhang.

BMC genomics (2018) 19 (1), 467.


Anterior-posterior gradient of plasticity in primate prefrontal cortex. 

M. Riley, X.-L. Qi, X. Zhou, C. Constantinidis.

Nature Communications (2018) 9(1):3790.


Fixation target representation in prefrontal cortex during the anti-saccade task. 

X. Zhou, C. Constantinidis.

J. Neurophysiology (2017)  117:2152-2162.


Neural correlates of working memeory development in adolescent primates. 

X. Zhou, D. Zhu, X.-L. Qi, S. H. Li, S.G. King, E. Salinas, T. R. Stanford, C. Constantinidis.

Nature Communications (2016) 7:13423.


Behavioral response inhibition and maturation of goal representation in prefrontal cortex after puberty. 

X. Zhou, D. Zhu, S. G. King, C. J. Lees, A. J. Bennett, E. Salinas, T. R. Stanford, C. Constantinidis.

Proc. Natl. Acad. Sci. USA (2016) 113(12):3353-8.


Distinct roles of the prefrontal and posterior parietal cortices in response inhibition. 

X. Zhou, X.-L. Qi, C. Constantinidis.

Cell Reports (201614(12):2765-73.


An evolutionary strategy for resilient cyber defense. 

E. W. Fulp, H. D. Gage, D. J. John, M. McNiece, W. H. Turkett, and X. Zhou [alphabetical].

In Proceedings of the IEEE Global Communications Conference (GLOBECOM) (2015).


Age-dependent changes in prefrontal intrinsic connectivity. 

X. ZhouD. Zhu, F. Katsuki, X.-L. Qi, C. J. Lees, A. J. Bennett, E. Salinas, T. R. Stanford, C. Constantinidis.

Proc. Natl. Acad. Sci. USA (2014) 111(10):3853-3858.


Working memory performance and neural activity in the prefrontal cortex of peri-pubertal monkeys. 

X. Zhou, D. Zhu, X.-L. Qi, C. J. Lees, A. J. Bennett, E. Salinas, T. R. Stanford, C. Constantinidis.

J. Neurophysiology (2013) 110:2648-2660.


Neurons with inverted tuning during the delay periods of working memory tasks in the dorsal prefrontal and posterior parietal cortex. 

X. Zhou, F. Katsuki, X.-L. Qi, and C. Constantinidis.

J. Neurophysiology (2012) 108:31-38.


Cholinergic modulation of working memory activity in primate prefrontal cortex. 

X. Zhou, X.-L. Qi, K. Douglas, K. Palaninathan, H. S. Kang, J. J. Buccafusco, D. T. Blake, C. Constantinidis.

J. Neurophysiology (2011) 106:2180:8.


Comparison of neural activity related to working memory in primate dorsolateral prefrontal and posterior parietal cortex. 

X.-L. Qi, F. Katsuki, T. Meyer, J. B. Rawley, X. Zhou, K. Douglas, C. Constantinidis.

Front. Syst. Neurosci. (2010) 4:12.


Book Chapters

X. Zhou, E. Salinas, T. R. Stanford, C. Constantinidis. Dynamic interactions in prefrontal functional connectivity during adolescence. In: Advances in Cognitive Neurodynamics (V) (2016) R. Wang and X. Pan, Editors. Springer. pp. 193-197


X.-L. Qi, X. Zhou, C. Constantinidis. Neurophysiological mechanisms of working memory: cortical specialization & plasticity. In: Attention and Performance XXV (2015). Jolicoeur P., Lefebvre C. and Martinez-Trujillo J., Editors. Academic Press. pp. 171-186