Babatunde Ogunnaike | University of Delaware (original) (raw)

Papers by Babatunde Ogunnaike

Genome biology, 2006

Identifying the gene regulatory networks governing physiological signal integration remains an im... more Identifying the gene regulatory networks governing physiological signal integration remains an important challenge in circadian biology. Epidermal growth factor receptor (EGFR) has been implicated in circadian function and is expressed in the suprachiasmatic nuclei (SCN), the core circadian pacemaker. The transcription networks downstream of EGFR in the SCN are unknown but, by analogy to other SCN inputs, we expect the response to EGFR activation to depend on circadian timing. We have undertaken a systems-level analysis of EGFR circadian time-dependent signaling in the SCN. We collected gene-expression profiles to study how the SCN response to EGFR activation depends on circadian timing. Mixed-model analysis of variance (ANOVA) was employed to identify genes with circadian time-dependent EGFR regulation. The expression data were integrated with transcription-factor binding predictions through gene group enrichment analyses to generate robust hypotheses about transcription-factors re...

Biophysical Journal, 2006

Increasing evidence suggests an important role for VPAC 2 -activated signal transduction pathways... more Increasing evidence suggests an important role for VPAC 2 -activated signal transduction pathways in maintaining a synchronized biological clock in the suprachiasmatic nucleus (SCN). Activation of the VPAC 2 signaling pathway induces per1 gene expression in the SCN and phase-shifts the circadian clock. Mice without the VPAC 2 receptor lack an overt, coherent circadian rhythm in clock gene expression, SCN neuron firing rate, and locomotor behavior. Using a systems approach, we have developed a kinetic model integrating VPAC 2 signaling mediated by the cyclic AMP (cAMP)/protein kinase A (PKA) pathway and leading to induced circadian clock gene expression. We fit the model to experimental data from the literature for cAMP accumulation, PKA activation, cAMP-response element binding protein phosphorylation, and per1 induction. By linking the VPAC 2 model to a published circadian clock model, we also simulated clock phase shifts induced by vasoactive intestinal polypeptide (VIP) and matched experimental data for the VIP response. The simulated phase response curve resembled the hamster response to a related neuropeptide, GRP 1-27 , and light. Simulations using pulses of VIP revealed that the system response is extraordinarily robust to input signal duration, a result with physiologically relevant consequences. Lastly, simulations using varied receptor levels matched literature experimental data from animals overexpressing VPAC 2 receptors.

Industrial & Engineering Chemistry Research, 1994

Many industrial chemical processes are difficult to control effectively using existing techniques... more Many industrial chemical processes are difficult to control effectively using existing techniques because they are complex, interconnected, nonlinear systems which lack reliable on-line measurements of key process variables. Due to increasingly stringent demands on product quality, energy utilization, and environmental responsibility, more effective control strategies are needed for these processes. By contrast, extremely complex biological systems routinely operate under more stringent requirements on "product quality" and "failure tolerance" as a result of the robust, high performance computation and control functions provided by the brain. Thus, studying and understanding these biological control systems, and ultimately "reverse engineering" their functions, should provide ample alternative techniques for developing effective control systems for chemical processes. The objective of this paper is to present one such biological control system-the baroreceptor reflex, which provides short-term regulation of arterial blood pressure-and identify potential applications in chemical process control. Novel process monitoring, modeling, and control strategies which are currently being developed by "reverse engineering" the architectural and computational properties of this reflex are discussed. Preliminary results on techniques for sensor fusion based control, nonlinear modeling, and control of multiple-input, single-output systems which have been abstracted from the reflex are also presented.

Chemical Engineering Science, 1996

A parallel control strategy is developed for process applications by "reverse engineering" the fu... more A parallel control strategy is developed for process applications by "reverse engineering" the functions of the baroreceptor reflex--the biological control system that regulates arterial blood pressure. The specific control architecture and algorithm employed by the reflex are analyzed from a process control perspective. A parallel control structure for process applications is then developed by reparameterizing the controllers in the biologically derived architecture. The resulting structure allows independent design of the parallel controllers via Hz-optimal control theory. The parallel control technique is applicable to singleinput processes for which two types of output measurements are available: (i) a primary measurement of the controlled output whose dynamic response to input changes is unfavorable (e.g. delayed); and (ii) a secondary measurement of a different output whose dynamic response is more favorable (e.g. undelayed). The parallel control system uses the primary and secondary outputs in a coordinated fashion in order to provide high performance disturbance rejection. Compared to conventional cascade control, the parallel control strategy provides improved stability and robustness characteristics. Two simulation examples demonstrate the superior performance and failure tolerance that can be achieved with the parallel control strategy compared to cascade control and single-input, single-output control techniques.

Automatica, Sep 1, 1996

Abstract-Two formulations of a nonlinear model predictive control scheme based on the second-orde... more Abstract-Two formulations of a nonlinear model predictive control scheme based on the second-order Volterra series model are presented. The lirst formulation determines the control action using successive substitution, and the second method directly solves a fourth-order nonlinear programming problem on-line. One case study is presented for the SISO control of an isothermal reactor which utilizes the fist controller formulation. A second case study is presented for the multivariable control of a large reactor, and uses the nonlinear programming formulation for the controller. The model coefficients for both examples are obtained by discretizing the bilinear Taylor series approximation of the fundamental model and calculating Markov parameters. The relationships between discrete and continuoustime bilinear model matrices using an explicit fourth-order Runge-Kutta method are also included. The responses to setpoint changes of both reactors controlled with a linear model predictive control scheme and the second-order Volterra model predictive control scheme are compared to desired, linear reference trajectories. In the majority of the cases examined, the responses obtained by the Volterra controller followed the reference trajectories more closely. Practical issues, including the reduction of the number of model parameters, are addressed in both case studies.

Http Dx Doi Org 10 1080 00986448508911284, Apr 3, 2007

The Journal of Clinical Endocrinology and Metabolism, Apr 14, 2014

Context: A control engineering perspective provides a framework for representing important mechan... more Context: A control engineering perspective provides a framework for representing important mechanistic details of the calcium (Ca) regulatory system efficiently. The resulting model facilitates the testing of hypotheses about mechanisms underlying the emergence of known Ca-related pathologies.

Biotechnology Progress, 2016

Glycan distribution has been identified as a "critical quality attribute" for m... more Glycan distribution has been identified as a "critical quality attribute" for many biopharmaceutical products, including monoclonal antibodies. Consequently, determining quantitatively how process variables affect glycan distribution is important during process development in order to control antibody glycosylation. In this work, we assess the effect of six bioreactor process variables on the glycan distribution of an IgG1 produced in CHO cells. Our analysis established that glucose and glutamine media concentration, temperature, pH, agitation rate, and dissolved oxygen (DO) had small but significant effects on the relative percentage of various glycans. In addition, we assessed glycosylation enzyme transcript levels and intracellular sugar nucleotide concentrations within the CHO cells to provide a biological explanation for the observed effects on glycan distributions. From these results we identified a robust operating region, or design space, in which the IgG1 could be produced with a consistent glycan distribution. Since our results indicate that perturbations to bioreactor process variables will cause only small (even if significant) changes to the relative percentage of various glycans (<±1.5%) - changes that are too small to affect the bioactivity and efficacy of this IgG1 significantly - it follows that the glycan distribution obtained will be consistent even with relatively large variations in bioreactor process variables. However, for therapeutic proteins where bioactivity and efficacy are affected by small changes to the relative percentage of glycans, the same analysis would identify the manipulated variables capable of changing glycan distribution, and hence can be used to implement a glycosylation control strategy. This article is protected by copyright. All rights reserved.

IFAC Proceedings Volumes, 2008

ABSTRACT Neurons in the nucleus tractus solitarius (NTS) communicate through chemical messengers ... more ABSTRACT Neurons in the nucleus tractus solitarius (NTS) communicate through chemical messengers to play a major role in blood pressure regulation, and aberrant communications within this brain nucleus cause serious diseases such as hypertension. To fulfill their role in blood pressure regulation, NTS neurons must receive chemical messengers and process these signals through biochemical networks comprising a large number of interacting proteins and genes; but because the population of NTS neurons is heterogeneous, there is significant variability in the abundance and activity of these network components. The effect of this neuron-to-neuron variability on blood pressure regulation is not well-understood and an improvement in understanding is necessary for developing effective treatments of hypertension. Our overall objective, therefore, is to understand how NTS neurons function in the presence of biological variability. In this work, we investigate the effect of biological variability on a critical mechanism for the central regulation of blood pressure: angiotensin II type 1 receptor (AT1R) activation of tyrosine hydroxylase in the brain. Using the regulatory mechanisms established in the literature (Veerasingham and Raizada, 2003), we construct a mechanistic, ordinary differential equation model for the induction of tyrosine hydroxylase gene expression modulated by the gene regulatory network activated by AT1R. This model allows us to explore the effect of biological variability on neuron function by performing model simulations with variations in reaction rate constants and species initial concentrations, and then comparing the predicted response of tyrosine hydroxylase from AT1R gene networks with variations in model parameters. We present simulation results showing AT1R activation induces tyrosine hydroxylase robustly in the presence of biological variability, and discuss properties of the AT1R gene regulatory network that ensure this robust performance. By finding this critical mechanism for the central regulation of blood pressure to be robust to neuron-to-neuron variability, our results may lead to the development of improved treatments of hypertension. Reference Veerasingham S.J. & Raizada M.K. (2003) Brain reninangiotensin system dysfunction in hypertension: recent advances and perspectives. Br. J. Pharmacol. 139(2):191-202.

The Faseb Journal, Mar 1, 2008

Automatica a Journal of Ifac the International Federation of Automatic Control, Feb 1, 2007

Sheet and film processes include polymer film extrusion, coating processes of many types, paper m... more Sheet and film processes include polymer film extrusion, coating processes of many types, paper manufacturing, sheet metal rolling, and plate glass manufacture. Identification, estimation, monitoring, and control of sheet and film processes are of substantial industrial interest since effective control means reduced usage of raw materials, increased production rates, improved product quality, elimination of product rejects, and reduced energy consumption. This paper reviews recent developments in sheet and film process control with particular attention to the effectiveness of existing techniques at addressing the critical aspects of sheet and film processes. ᭧

Lecture Notes in Control and Information Sciences, May 9, 2010

Although TGF-β is widely known to appear to function paradoxically as a tumor suppressor in norma... more Although TGF-β is widely known to appear to function paradoxically as a tumor suppressor in normal cells, and as a tumor promoter in cancer cells, the underlying mechanisms by which a single cytokine plays such a dual—and diametrically opposed—role are unknown. In particular, it remains a mystery why the level of TGF-β is unusually high in the primary cancer tissue and blood samples of cancer patients with the poorest prognosis, given that this cytokine is primarily a tumor suppressor. To provide a quantitative explanation of these paradoxical observations, we have developed, from a control theory perspective, a mechanistic model of TGF-β-driven regulation of cell homeostasis. Analysis of the overall system model yields quantitative insight into how the cell population is regulated, enabling us to propose a plausible explanation for the paradox: with the tumor suppressor role of TGF-β unchanged from normal to cancer cells, we demonstrate that the observed increased level of TGF-β is an effect of cancer cell characteristics (specifically, acquired TGF-β resistance), not the cause. We are thus able to explain precisely why the clinically observed correlation between elevated TGF-β levels and poor prognosis is in fact consistent with TGF-β’s original (and unchanged) role as a tumor suppressor.

Application of Neural Networks and Other Learning Technologies in Process Engineering, 2001

Methods developed for radial basis function network (RBFN) identification are applied to a comple... more Methods developed for radial basis function network (RBFN) identification are applied to a complex multiple-input, multiple-output (MIMO) simulation of a solution copolymerization reactor. For RBFN identification, k-means clustering and stepwise regression analysis are used. The practicality of applying these methods to large industrial identification problems is discussed, considering the restrictions of industrially practical input sequence design. The RBFN model has three inputs and two outputs, and the dimensionality of the identification problem poses some difficulties for nonlinear empirical model identification; specifically, the large amount of data required is a problem for plant testing and may cause computational difficulties for identification algorithms as well.

Industrial Engineering Chemistry Research, May 19, 2010

Reactive extrusion processes are typically multivariable, display highly nonlinear characteristic... more Reactive extrusion processes are typically multivariable, display highly nonlinear characteristics, and often have significant time delays associated with the (offline) measurements of key product properties. Achieving desired product characteristics in industrial practice has therefore been based primarily on the control of a single critical variable such as viscosity. However, increasingly stringent customer demand on product quality has rendered such strategies no longer viable and has necessitated the development of more comprehensive schemes that focus explicitly on controlling product quality characteristics. This paper reports on an experimentally validated inference-based control scheme for controlling product quality and end-use properties in reactive extrusion processes. The scheme employs inference models to predict infrequently measured properties at a much faster ratespredictions that are then used to take necessary control action in between samples, within a cascadelike structure involving separate and distinct multivariable controllers. The control scheme is evaluated first in simulation and then implemented experimentally via a Labview-Matlab interface on an actual pilot-scale reactive extrusion process, where product viscosity, tensile strength, and toughness are controlled simultaneously. Some representative results are presented to highlight the advantages and limitations of the scheme.