Cranos Williams

Haque, S., Lobaton, E., Nelson, N., Yencho, G. C., Pecota, K. V., Mierop, R., … Williams, C. M. (2021). Computer vision approach to characterize size and shape phenotypes of horticultural crops using high-throughput imagery. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 182. https://doi.org/10.1016/j.compag.2021.106011

Kudenov, M. W., Scarboro, C. G., Altaqui, A., Boyette, M., Yencho, G. C., & Williams, C. M. (2021). Internal defect scanning of sweetpotatoes using interactance spectroscopy. PLOS ONE, 16(2). https://doi.org/10.1371/journal.pone.0246872

Buckner, E., Madison, I., Melvin, C., Long, T., Sozzani, R., & Williams, C. (2020). BioVision Tracker: A semi-automated image analysis software for spatiotemporal gene expression tracking in Arabidopsis thaliana. PLANT CELL BIOLOGY, pp. 419–436. https://doi.org/10.1016/bs.mcb.2020.04.017

Broeck, L., Gordon, M., Inze, D., Williams, C., & Sozzani, R. (2020). [Review of Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling]. FRONTIERS IN GENETICS, 11. https://doi.org/10.3389/fgene.2020.00457

Madison, I., Melvin, C., Buckner, E., Williams, C., Sozzani, R., & Long, T. (2020). MAGIC: Live imaging of cellular division in plant seedlings using lightsheet microscopy. PLANT CELL BIOLOGY, pp. 405–418. https://doi.org/10.1016/bs.mcb.2020.04.004

Haque, S., Ahmad, J. S., Clark, N. M., Williams, C. M., & Sozzani, R. (2019). Computational prediction of gene regulatory networks in plant growth and development. Current Opinion in Plant Biology, 47, 96–105. https://doi.org/10.1016/J.PBI.2018.10.005

Argueso, C. T., Assmann, S. M., Birnbaum, K. D., Chen, S., Dinneny, J. R., Doherty, C. J., … Williams, C. M. (2019). Directions for research and training in plant omics: Big Questions and Big Data. Plant Direct, 3(4), e00133. https://doi.org/10.1002/PLD3.133

Wang, J. P., Matthews, M. L., Naik, P. P., Williams, C. M., Ducoste, J. J., Sederoff, R. R., & Chiang, V. L. (2019). Flux modeling for monolignol biosynthesis. Current Opinion in Biotechnology, 56, 187–192. https://doi.org/10.1016/J.COPBIO.2018.12.003

Clark, N. M., Buckner, E., Fisher, A. P., Nelson, E. C., Nguyen, T. T., Simmons, A. R., … Sozzani, R. (2019). Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks. NATURE COMMUNICATIONS, 10. https://doi.org/10.1038/s41467-019-13132-2

Naik, P., Wang, J. P., Sederoff, R., Chiang, V., Williams, C., & Ducoste, J. J. (2018). Assessing the impact of the 4CL enzyme complex on the robustness of monolignol biosynthesis using metabolic pathway analysis. PLoS One, 13(3). https://doi.org/10.1371/journal.pone.0193896

Wang, J. P., Matthews, M. L., Williams, C. M., Shi, R., Yang, C. M., Tunlaya-Anukit, S., … Shuford, C. M. (2018). Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis. Nature Communications, 9. https://doi.org/10.1038/s41467-018-03863-z

Alexander, W. E., & Williams, C. M. (2017). Design of digital filters. Digital Signal Processing: Principles, Algorithms and System Design, 205–275.

Alexander, W. E., & Williams, C. M. (2017). Digital signal processing systems design. Digital Signal Processing: Principles, Algorithms and System Design, 455–517.

Alexander, W. E., & Williams, C. M. (2017). Digital signal processing: principles, algorithms and system design preface. Digital Signal Processing: Principles, Algorithms and System Design, XXVII-.

Alexander, W. E., & Williams, C. M. (2017). Finite word length effects. Digital Signal Processing: Principles, Algorithms and System Design, 351–388. https://doi.org/10.1016/b978-0-12-804547-3.00006-1

Alexander, W. E., & Williams, C. M. (2017). Frequency domain analysis. Digital Signal Processing: Principles, Algorithms and System Design, 159–204.

Alexander, W. E., & Williams, C. M. (2017). Fundamental DSP concepts. Digital Signal Processing: Principles, Algorithms and System Design, 19–157.

Alexander, W. E., & Williams, C. M. (2017). Hardware implementation. Digital Signal Processing: Principles, Algorithms and System Design, 519–561.

Alexander, W. E., & Williams, C. M. (2017). Implementation of discrete time systems. Digital Signal Processing: Principles, Algorithms and System Design, 277–350.

Alexander, W. E., & Williams, C. M. (2017). Introduction to digital signal processing. Digital Signal Processing: Principles, Algorithms and System Design, 1–17.

Muhammad, D., Schmittling, S., Williams, C., & Long, T. A. (2017). [Review of More than meets the eye: emergent properties of transcription factors networks in arabidopsis]. Biochimica et Biophysica Acta. Gene Regulatory Mechanisms, 1860(1), 64–74. https://doi.org/10.1016/j.bbagrm.2016.07.017

Alexander, W. E., & Williams, C. M. (2017). Multirate digital signal processing. Digital Signal Processing: Principles, Algorithms and System Design, 389–454.

Balaguer, M. A. D., Fisher, A. P., Clark, N. M., Fernandez-Espinosa, M. G., Moller, B. K., Weijers, D., … Sozzani, R. (2017). Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells. Proceedings of the National Academy of Sciences of the United States of America, 114(36), E7632–7640. https://doi.org/10.1073/pnas.1707566114

Lin, C. Y., Wang, J. P., Li, Q. Z., Chen, H. C., Liu, J., Loziuk, P., … Chiang, V. L. (2015). 4-coumaroyl and caffeoyl shikimic acids inhibit 4-coumaric acid: Coenzyme a ligases and modulate metabolic flux for 3-hydroxylation in monolignol biosynthesis of Populus trichocarpa. Molecular Plant, 8(1), 176–187. https://doi.org/10.1016/j.molp.2014.12.003

Koryachko, A., Matthiadis, A., Muhammad, D., Foret, J., Brady, S. M., Ducoste, J. J., … Williams, C. (2015). Clustering and differential alignment algorithm: Identification of early stage regulators in the Arabidopsis thaliana iron deficiency response. PLoS One, 10(8). https://doi.org/10.1371/journal.pone.0136591

Koryachko, A., Matthiadis, A., Ducoste, J. J., Tuck, J., Long, T. A., & Williams, C. (2015). Computational approaches to identify regulators of plant stress response using high-throughput gene expression data. Current Plant Biology, 3-4, 20–29. https://doi.org/10.1016/J.CPB.2015.04.001

Balaguer, M. A. D., & Williams, C. M. (2014). Hierarchical modularization of biochemical pathways using fuzzy-C means clustering. IEEE Transactions on Cybernetics, 44(8), 1473–1484. https://doi.org/10.1109/tcyb.2013.2286679

Chen, H. C., Song, J., Wang, J. P., Lin, Y. C., Ducoste, J., Shuford, C. M., … Chiang, V. L. (2014). Systems biology of lignin biosynthesis in Populus trichocarpa: Heteromeric 4-Coumaric zcid: Coenzyme A ligase protein complex formation, regulation, and numerical modeling. Plant Cell, 26(3), 876–893. https://doi.org/10.1105/tpc.113.119685

Chen, H. C., Song, J. N., Williams, C. M., Shuford, C. M., Liu, J., Wang, J. P., … Chiang, V. L. (2013). Monolignol pathway 4-coumaric acid: Coenzyme a ligases in Populus trichocarpa: Novel specificity, metabolic regulation, and simulation of coenzyme a ligation fluxes. Plant Physiology, 161(3), 1501–1516. https://doi.org/10.1104/pp.112.210971

Nabavi, S., & Williams, C. M. (2012). A novel cost function for parameters estimation in oscillatory biochemical systems. 2012 Proceedings of IEEE Southeastcon. https://doi.org/10.1109/secon.2012.6196978

Wang, J. P., Shuford, C. M., Li, Q. Z., Song, J. N., Lin, Y. C., Sun, Y. H., … Chiang, V. L. (2012). Functional redundancy of the two 5-hydroxylases in monolignol biosynthesis of Populus trichocarpa: LC-MS/MS based protein quantification and metabolic flux analysis. Planta, 236(3), 795–808. https://doi.org/10.1007/s00425-012-1663-5

Matthews, M. L., & Williams, C. M. (2012). Region of attraction estimation of biological continuous Boolean models. Ieee international conference on systems man and cybernetics conference, 1700–1705. https://doi.org/10.1109/icsmc.2012.6377982

Marvel, S. W., & Williams, C. M. (2012). Set membership experimental design for biological systems. BMC Systems Biology, 6. https://doi.org/10.1186/1752-0509-6-21

Marvel, S. W., & Williams, C. M. (2012). Set membership state and parameter estimation for nonlinear differential equations with sparse discrete measurements. Ieee international conference on systems man and cybernetics conference, 72–77. https://doi.org/10.1109/icsmc.2012.6377679