Reliable computation of equilibrium states and bifurcations in food chain models. - C. Ryan Gwaltney; Mark P. Styczynski; Mark A. Stadtherr (Comput. Chem. Eng., 2004)

Overview of computational methods for the inference of gene regulatory networks. - Mark P. Styczynski; Gregory Stephanopoulos (Comput. Chem. Eng., 2005)

A generic motif discovery algorithm for sequential data. - Kyle L. Jensen; Mark P. Styczynski; Isidore Rigoutsos; Gregory Stephanopoulos (Bioinform., 2006)

Pathline: A Tool For Comparative Functional Genomics. - Miriah D. Meyer; Bang Wong; Mark P. Styczynski; Tamara Munzner; Hanspeter Pfister (Comput. Graph. Forum, 2010)

Distinct metabolic responses of an ovarian cancer stem cell line. - Kathleen A. Vermeersch; Lijuan Wang; John F. McDonald 002; Mark P. Styczynski (BMC Syst. Biol., 2014)

Live demonstration: A multi-modality CMOS sensor array for cell-based assay and drug screening. - Jong Seok Park 001; Taiyun Chi; Amy Su; Chengjie Zhu; Jessica Butts; Tracy Hookway; Todd C. McDevitt; Mark P. Styczynski; Hua Wang 006 (BioCAS, 2015)

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems. - Weiwei Yin; Swetha Garimalla; Alberto Moreno; Mary R. Galinski; Mark P. Styczynski (BMC Syst. Biol., 2015)

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening. - Taiyun Chi; Jong Seok Park 001; Jessica C. Butts; Tracy A. Hookway; Amy Su; Chengjie Zhu; Mark P. Styczynski; Todd C. McDevitt; Hua Wang 006 (IEEE Trans. Biomed. Circuits Syst., 2015)

Live demonstration: A 1024-pixel CMOS multi-modality sensing array for cell-based assays. - Jong Seok Park 001; Moez Karim Aziz; Taiyun Chi; Amy Su; Andrew Zhao; Hee Cheol Cho; Mark P. Styczynski; Hua Wang 006 (IEEE SENSORS, 2016)

A high-density CMOS multi-modality joint sensor/stimulator array with 1024 pixels for holistic real-time cellular characterization. - Jong Seok Park 001; Taiyun Chi; Amy Su; Chengjie Zhu; Jung Hoon Sung; Hee Cheol Cho; Mark P. Styczynski; Hua Wang 006 (VLSI Circuits, 2016)

LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism. - Robert A. Dromms; Justin Y. Lee; Mark P. Styczynski (BMC Bioinform., 2020)

SCOUR: a stepwise machine learning framework for predicting metabolite-dependent regulatory interactions. - Justin Y. Lee; Britney Nguyen; Carlos Orosco; Mark P. Styczynski (BMC Bioinform., 2021)