Cranos Williams

Biography

Research Interests: I am currently the director of the EnBiSys Research Laboratory. The EnBiSys Lab is a highly collaborative, multidisciplinary research laboratory, focused on the development of targeted computational and analytical solutions for modeling and controlling biological systems. The solutions we develop are used to build and strengthen the transition from large-scale high-throughput –omics data to highly connected kinetic models in the post-genomic era; models that can be used to attain the depth, understanding, and comprehension needed to manipulate and control biological systems for a defined purpose.

Specific interests in this field include:

- Nonlinear Systems Analysis

- System Identification

- Uncertainty Analysis

- Optimal Experimental Design

- Biological Signal and Data Processing

Patents: S. Chen, L. Ray, N. Cahill, M. Goodgame, and C. Williams, “Method of Image Registration using Mutual Information,” U.S. Patent 7,263,243, Aug. 28, 2007.

Education

• Ph.D. 2008
  Electrical Engineering
  North Carolina State University, Raleigh
• Master's 2002
  Electrical Engineering
  North Carolina State University, Raleigh
• Bachelor's 2001
  Electrical Engineering
  NC A&T State University, Greensboro

Awards & Honors

Recent Publications

• Computer vision approach to characterize size and shape phenotypes of horticultural crops using high-throughput imagery (2021)
• Internal defect scanning of sweetpotatoes using interactance spectroscopy (2021)
• BioVision Tracker: A semi-automated image analysis software for spatiotemporal gene expression tracking in Arabidopsis thaliana (2020)
• Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling (2020)
• MAGIC: Live imaging of cellular division in plant seedlings using lightsheet microscopy (2020)
• Computational prediction of gene regulatory networks in plant growth and development (2019)
• Directions for research and training in plant omics: Big Questions and Big Data (2019)
• Flux modeling for monolignol biosynthesis (2019)
• Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks (2019)
• Assessing the impact of the 4CL enzyme complex on the robustness of monolignol biosynthesis using metabolic pathway analysis (2018)