Preprints and Manuscripts
Chen, Q., Liang, Z., Jin Z., Xu M. Decoupling extrudability and shape fidelity: A quantitative, computer-vision framework for printability of soybean meal-xanthan inks in extrusion-based 3D food printing.
Published papers
Fernandez, E.C., Tu, G., Dai, W., Yang, S., Liu, Z., Grzybowski, M. and Liang, Z.#, 2026. Spatial Coordination between Leaf Gradient and Temperature Response in Barley. bioRxiv, pp.2025-06 (Accepted at The Plant Journal).
Shao, Y., Tran, Q., Feng, Y., Kolekar, P., Liu, Y., Liang, Z., Fan, L., McBride, A., Jones, T., Cameron, A. and Mulder, H., 2026. Analysis of error profiles of indels and structural variants in deep-sequencing data. Cell Genomics, 6(2).
Khan, H., Manan, F., Acharya, N., Pothula, H., Basyal, S., Salsman, E., Hegstad, J., Liang, Z., Liu, Z. and Li, X., 2026. Phenotypic evaluation and genome-wide association mapping for bacterial leaf streak resistance in a worldwide cultivated emmer wheat collection. Phytopathology®, 116(1), pp.129-136.
Chen, Q., Liang, Z., Islam, S., Rao, J. and Xu, M., 2025. Integrating fiber modification and computer-vision evaluation to improve soybean meal for 3D food printing. Food Research International, p.118131.
Liu, H., Ma, X., Jiang, S., Li, Z., Dai, W., Liang, Z#., Springer, N.M#. and Zhang, M#., 2025. Conservation and variability of long-range interactions in structurally diverse maize genomes. Nature Communications, 16(1), p.10105.
Ma, X., Feng, Y., Li, H., Shao, Y., Mulder, H., Kolekar, P., Liu, Y., Tran, Q., Liang, Z., Fan, L. and Foy, S., 2025. Diverse mechanisms of therapy resistance in relapsed childhood B-cell acute lymphoblastic leukemia (B-ALL): a report from the Children’s Oncology Group. Cancer Research, 85(8_Supplement_1), pp.1205-1205.
Wang, X., Ma, X., Yan, G., Hua, L., Liu, H., Huang, W., Liang, Z., Chao, Q., Hibberd, J.M., Jiao, Y. and Zhang, M., 2023. Gene duplications facilitate C4-CAM compatibility in common purslane. Plant Physiology, 193(4), pp.2622-2639.
Barnes, A.C., Myers, J.L., Surber, S.M., Liang, Z., Mower, J.P., Schnable, J.C. and Roston, R.L., 2023. Oligogalactolipid production during cold challenge is conserved in early diverging lineages. Journal of Experimental Botany, 74(17), pp.5405-5417.
Liang, Z., Meng, X. and Schnable, J.C., 2023. A Transferable Machine Learning Framework for Predicting Transcriptional Responses of Genes Across Species. In Plant Gene Regulatory Networks: Methods and Protocols (pp. 361-379). New York, NY: Springer US.