A5015375342- Engineering Education and Curriculum Development
- Intermetallics and Advanced Alloy Properties
- Gene Regulatory Network Analysis
- Engineering Education and Pedagogy
- Nanotechnology research and applications
- Fungal and yeast genetics research
- Microtubule and mitosis dynamics
- Career Development and Diversity
- Advanced materials and composites
- Metal and Thin Film Mechanics
- Experimental Learning in Engineering
- Titanium Alloys Microstructure and Properties
- Microbial Metabolic Engineering and Bioproduction
- Biomedical and Engineering Education
- Higher Education Research Studies
- Evaluation of Teaching Practices
- Advanced ceramic materials synthesis
- Teaching and Learning Programming
- Bioinformatics and Genomic Networks
- Shape Memory Alloy Transformations
- Learning Styles and Cognitive Differences
- High Entropy Alloys Studies
- Diverse Education and Engineering Focus
- Innovative Teaching and Learning Methods
- Gender Diversity and Inequality
Worcester Polytechnic Institute
2018-2024
Michigan State University
2015-2024
California Polytechnic State University
2008-2024
William P. Wharton Trust
2023-2024
University of Massachusetts Dartmouth
2024
Cal Poly Corporation
2018-2024
National Chengchi University
2023
Chung Shan Medical University Hospital
2023
Stanford University
2020-2021
Cuesta College
2020
The adaptive responses of a living cell to internal and external signals are controlled by networks proteins whose interactions so complex that the functional integration network cannot be comprehended intuitive reasoning alone. Mathematical modeling, based on biochemical rate equations, provides rigorous reliable tool for unraveling complexities molecular regulatory networks. budding yeast cycle is challenging test case this approach, because control system known in exquisite detail its...
Cells progressing through the cell cycle must commit irreversibly to mitosis without slipping back interphase before properly segregating their chromosomes. A mathematical model of cell-cycle progression in cell-free egg extracts from frog predicts that irreversible transitions into and out are driven by hysteresis molecular control system. Hysteresis refers toggle-like switching behavior a dynamical In model, toggle switch is created positive feedback phosphorylation reactions controlling...
The molecular machinery of cell cycle control is known in more detail for budding yeast, Saccharomyces cerevisiae, than any other eukaryotic organism. In recent years, many elegant experiments on yeast have dissected the roles cyclin molecules (Cln1–3 and Clb1–6) coordinating events DNA synthesis, bud emergence, spindle formation, nuclear division, separation. These experimental clues suggest a mechanism principal interactions controlling synthesis degradation. Using standard techniques...
In the cell division cycle of budding yeast, START refers to a set tightly linked events that prepare for and DNA replication, FINISH denotes interrelated by which exits from mitosis divides into mother daughter cells. On basis recent progress made molecular biologists in characterizing genes proteins control FINISH, we crafted new mathematical model progression yeast. Our exploits natural separation time scales network construct system differential-algebraic equations protein synthesis...
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Abstract Background Parameter estimation from experimental data is critical for mathematical modeling of protein regulatory networks. For realistic networks with dozens species and reactions, parameter an especially challenging task. In this study, we present approach that effective in fitting a model the budding yeast cell cycle (comprising 26 nonlinear ordinary differential equations containing 126 rate constants) to experimentally observed phenotypes (viable or inviable) 119 genetic...
The cell cycle is composed of bistable molecular switches that govern the transitions between gap phases (G1 and G2) in which DNA replicated (S) partitioned daughter cells (M). Many details budding yeast G1-S transition (Start) have been elucidated recent years, especially with regard to its switch-like behavior due positive feedback mechanisms. These results led us reevaluate expand a previous mathematical model cycle. new incorporates Whi3 inhibition Cln3 activity, Whi5 SBF MBF...
To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths weaknesses. In this paper, we propose "standard component" strategy combines advantageous features networks, simulations framework acknowledges typical sorts reactions found protein regulatory networks....
Regulation of cyclin abundance is central to eukaryotic cell cycle control. Strong overexpression mitotic cyclins known lock the system in mitosis, but quantitative behavior control as this threshold approached has only been characterized vitro Xenopus extract system. Here, we quantitate for block budding yeast caused by constitutive Clb2. Near threshold, displays marked loss robustness, that or even heterozygosity some regulators becomes deleterious lethal, though complete these tolerated...
Progression through the cell division cycle is orchestrated by a complex network of interacting genes and proteins. Some these proteins are known to fluctuate periodically during cycle, but systematic study fluctuations broad sample cell-cycle has not been made until now. Using time-lapse fluorescence microscopy, we profiled 16 strains budding yeast, each containing GFP fused single gene involved in regulation. The dynamics protein abundance localization were characterized extracting...
Abstract Engineering departments across the country are striving to diversify their student bodies, making it increasingly important attract and support first-generation students. First-generation students—students whose parents do not have four-year degrees—bring ethnic, cultural, socioeconomic diversity university campuses. They also often face additional academic social challenges during transition college when compared peers with who graduated from (Engle, Bermeo, O’Brien, 2006). It is...
Unlike many mutants that are completely viable or inviable, the CLB2-dbΔ clb5Δ mutant of Saccharomyces cerevisiae is inviable in glucose but partially on slower growth media such as raffinose. On raffinose, cells can bud and divide each cycle there a chance cell will fail to (telophase arrest), causing it exit cycle. This effect gives rise stochastic phenotype cannot be explained by deterministic model. We measure inter-bud times wild type growing raffinose compute statistics distributions...