Author

C. Miao

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Plant Biology· 6 Cancer Biology· 2 Cell Biology· 1

Signature Assays, Organisms & Methods

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Organism:plant (other)· 6 Assay:imaging· 5 Research Focus:cell type annotation· 4 Approach:statistical model· 4 Approach:deep learning· 3 Approach:experimental assay· 3 Research Focus:gene regulatory network inference· 3 Organism:human· 3

Frequent Co-Authors

J. C. Schnable· 5 shared A. S. Kibel· 2 shared B. Benes· 2 shared J. Yang· 2 shared K. W. Mouw· 2 shared L. Jia· 2 shared M. Gaillard· 2 shared P. S. Schnable· 2 shared

Activity by Year

2019-2022 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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5 shared papersPlant Biology

J. C. Schnable

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Author profile →

9 papers

Recent·Most cited

CRISPR screens reveal genetic determinants of PARP inhibitor sensitivity and resistance in prostate cancer

T. Tsujino, T. Takai, K. Hinohara, F. Gui, T. Tsutsumi, X. Bai, C. Miao, C. Feng, B. Gui, S. Sztupinszki, A. Simoneau, N. Xie, L. Fazli, X. Dong, H. Azuma, , L. Jia

This study uses CRISPR screens to identify genetic factors affecting PARP inhibitor sensitivity and resistance in prostate cancer, revealing novel targets and mechanisms.

bioRxiv · Apr 13, 2022 · PreprintCancer Biology

RB1 loss overrides PARP inhibitor sensitivity driven by RNASEH2B loss in prostate cancer

c. Miao, T. Tsujino, T. Takai, G. Fu, T. Tsutsumi, Z. Sztupinszki, Z. Szallasi, K. W. Mouw, A. S. Kibel, L. Jia

The paper shows that loss of RNASEH2B makes prostate cancer cells sensitive to PARP inhibitors, but co-deletion with RB1 reduces this sensitivity through BRCA2 upregulation, and ATR inhibition can restore sensitivity.

bioRxiv · Nov 8, 2021Cancer Biology

MicroRNA-27a-5p inhibits proliferation, migration and invasion and promotes apoptosis of Wilms tumor cell by targeting PBOV1

z. guo, q. yv, c. miao, w. ge, p. li

This study shows miR-27a-5p suppresses Wilms tumor by inducing apoptosis and inhibiting proliferation, migration, and invasion through targeting PBOV1.

bioRxiv · Aug 25, 2021Cell Biology

3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves

M. C. Tross, M. Gaillard, M. Zwiener, C. Miao, R. J. Grove, B. Li, B. Benes, J. C. Schnable

This paper uses 3D reconstruction to measure leaf angles in sorghum and identifies genetic loci associated with leaf angle variation.

bioRxiv · Jun 15, 2021Plant Biology

Automation of Leaf Counting in Maize and Sorghum Using Deep Learning

C. Miao, A. Guo, A. M. Thompson, J. Yang, Y. Ge, J. C. Schnable

This paper develops and evaluates deep learning models for automated leaf counting in maize and sorghum, achieving performance close to human annotators.

bioRxiv · Dec 19, 2020Plant Biology

Meta-Analysis Identifies Pleiotropic Loci Controlling Phenotypic Trade-offs in Sorghum

R. V. Mural, M. Grzybowski, C. Miao, A. Damke, S. Sapkota, R. E. Boyles, M. G. Salas Fernandez, P. S. Schnable, B. Sigmon, S. Kresovich, J. C. Schnable

The paper uses existing trait datasets from a sorghum population to identify pleiotropic loci through multivariate analysis, revealing new insights into phenotypic trade-offs.

bioRxiv · Oct 27, 2020Plant Biology

Voxel Carving Based 3D Reconstruction of Sorghum Identifies Genetic Determinants of Radiation Interception Efficiency

M. Gaillard, C. Miao, J. Schnable, B. Benes

This paper develops a voxel carving method to reconstruct 3D sorghum canopies from RGB images, identifying genetic loci affecting light interception efficiency.

bioRxiv · Apr 6, 2020Plant Biology

Functional principal component based time-series genome-wide association in sorghum

C. Miao, Y. Xu, S. Liu, P. S. Schnable, J. C. Schnable

This study uses functional principal component analysis to identify genetic loci regulating phenotypic change over time in sorghum, successfully detecting known genes not found in single-time-point analyses.

bioRxiv · Feb 16, 2020 · PreprintPlant Biology

Simulated Plant Images Improve Maize Leaf Counting Accuracy

C. Miao, T. P. Hoban, A. Pages, Z. Xu, E. Rodene, J. Ubbens, I. Stavness, J. Yang, J. C. Schnable

The paper shows synthetic maize leaf images improve leaf counting accuracy when real-world data are limited, outperforming real data in some cases.

bioRxiv · Jul 18, 2019 · PreprintPlant Biology