A5045462352- Gene Regulatory Network Analysis
- Advanced Control Systems Optimization
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
- Control Systems and Identification
- Stability and Control of Uncertain Systems
- Adaptive Control of Nonlinear Systems
- Advanced Control Systems Design
- Fault Detection and Control Systems
- Computational Drug Discovery Methods
- Extremum Seeking Control Systems
- Gene expression and cancer classification
- Iterative Learning Control Systems
- Hydrology and Drought Analysis
- Genomics and Phylogenetic Studies
- Receptor Mechanisms and Signaling
- Evolution and Genetic Dynamics
- RNA and protein synthesis mechanisms
- Mathematical Biology Tumor Growth
- Sensor Technology and Measurement Systems
- Single-cell and spatial transcriptomics
- Bacterial Genetics and Biotechnology
- Microbial Natural Products and Biosynthesis
- Target Tracking and Data Fusion in Sensor Networks
- Advanced Adaptive Filtering Techniques
Texas A&M University
2015-2024
Arizona State University
2024
Savitribai Phule Pune University
2021
ORCID
2021
Texas A&M University System
2017-2020
Mitchell Institute
1995-2014
Texas A&M University at Qatar
2012-2014
Qatar University
2012
Translational Genomics Research Institute
2009-2010
Jadavpur University
2010
An issue in microfabrication of the fluidic channels glass/poly (dimethyl siloxane) (PDMS) is absence a well-defined study bonding strength between surfaces making up these channels. Although most research papers mention use oxygen plasma for developing chemical (siloxane) bonds participating surfaces, yet they only define certain set parameters, tailored to specific setup. important requirement all microfluidics/biosensors industry development general regime, which defines systematic method...
This paper considers the problem of stabilizing a first-order plant with dead time using proportional-integral-derivative (PID) controller. Using version Hermite-Biehler theorem that is applicable to quasi-polynomials, complete set PID parameters determined for both open-loop stable and unstable plants. The range admissible proportional gains first in closed form. For each gain this range, space integral derivative shown be either trapezoid, triangle or quadrilateral. case an plant,...
Abstract Motivation: Intervention in a gene regulatory network is used to help it avoid undesirable states, such as those associated with disease. Several types of intervention have been studied the framework probabilistic Boolean (PBN), which essentially finite collection networks at any discrete time point state vector transitions according rules one constituent networks. For an instantaneously random PBN, governing randomly chosen each point. context-sensitive remains fixed for interval...
A complete tutorial review of the entire field is presented, beginning with simple instability examples to identify causes nonrobust behavior in adaptive control. Some mathematical groundwork and theory for design analysis laws developed. Commonly used controller structures are discussed, highlighting their particular robustness properties. Particular attention paid model reference, pole placement, linear quadratic structures. Designs analyses controllers, based on combining corresponding...
External control of a genetic regulatory network is used for the purpose avoiding undesirable states, such as those associated with disease. Heretofore, intervention has focused on finite-horizon control, i.e., over small number stages. This paper considers design optimal infinite-horizon context-sensitive probabilistic Boolean networks (PBNs). It can also be applied to instantaneously random PBNs. The stationary policy obtained independent time and dependent current state. We concentrate...
Abstract Probabilistic Boolean Networks, which form a subclass of Markovian Genetic Regulatory have been recently introduced as rule-based paradigm for modeling gene regulatory networks. In an earlier paper, we external control into More precisely, given genetic network whose state transition probabilities depend on (control) variable, Dynamic Programming-based procedure was developed by one could choose the sequence actions that minimized performance index over finite number steps. The...
Motivation: Dynamical modeling of gene regulation via network models constitutes a key problem for genomics. The long-run characteristics dynamical system are critical and their determination is primary aspect analysis. In the other direction, synthesis involves constructing possessing given set properties. This inverse problem. Generally, ill-posed, meaning there will be many networks, or perhaps none, desired Relative to behavior, we may wish construct networks desirable steady-state...
The purpose of this paper is to address the issue performance by using two additional criteria assess in ideal and nonideal situations. They are mean square tracking error criterion L/sub /spl infin// bound criterion. We use these examine a standard model reference adaptive controller motivate design modified scheme that can have an arbitrarily improved nominal case presence bounded input disturbances. It shown for cases provide zero-state transient arbitrary reduction size possible bursts...
The YJBK parametrization characterizes all stabilizing controllers. In industry, most controllers are PID and there is no solution to the problem: can a plant P(s) be stabilized by controller? this paper, we provide an answer question. Besides settling question of existence, computationally constructive characterization that stabilize given plant. Thus result essentially extension restricted PIDs opens up possibility optimal design using PIDs.
This paper presents a general theoretical framework for generating Boolean networks whose state transitions realize set of given biological pathways or minor variations thereof. ill-posed inverse problem, which is crucial importance across practically all areas biology, solved by using Karnaugh maps are classical tools digital system design. It shown that the incorporation prior knowledge, presented in form pathways, can bring about dramatic reduction cardinality network search space....
Abstract Background Oxidative stress is a consequence of normal and abnormal cellular metabolism linked to the development human diseases. The effective functioning pathway responding oxidative protects DNA against damage; conversely failure response mechanism can induce aberrant behavior leading diseases such as neurodegenerative disorders cancer. Thus, understanding signaling present in pathways determining possible alterations disease could provide us with useful pointers for therapeutic...
The fabrication and testing of Teflon AF-coated channels on silicon bonding the same to a similarly coated glass wafer are described. With water or aqueous solutions in such channels, exhibit much better light conduction ability than similar uncoated channels. Although loss is greater extruded AF tubes, throughput far superior described literature consisting [110] planes with 45° sidewalls. Absorbance noise levels under actual flow conditions using an LED source, inexpensive photodiode...
Abstract Motivation: Cancer encompasses various diseases associated with loss of cell cycle control, leading to uncontrolled proliferation and/or reduced apoptosis. is usually caused by malfunction(s) in the cellular signaling pathways. Malfunctions occur different ways and at locations a pathway. Consequently, therapy design should first identify location type malfunction arrive suitable drug combination. Results: We consider growth factor (GF) pathways, widely studied context cancer....
This paper summarizes the discussions held during First IEEE Life Sciences Grand Challenges Conference, on October 4-5, 2012, at National Academy of Sciences, Washington, DC, and grand challenges identified by conference participants. Despite tremendous efforts to develop knowledge ability that are essential in addressing biomedical health problems using engineering methodologies, optimization this approach toward life sciences healthcare remains a challenge. The was aimed high-level...
This article presents a tutorial survey of some the recent results on intervention in context probabilistic gene regulatory networks, which, owing to their original binary formulation and usual application using ternary gene-expression quantization, are generically called Boolean networks (PBNs). These essentially generalizations standard introduced by Kauffman that allow incorporation uncertainty into intergene relationships. Given PBN, transition from one state next takes place accordance...
The control of probabilistic Boolean networks as a model genetic regulatory is formulated an optimal stochastic problem and has been solved using dynamic programming; however, the proposed methods fail when number genes in network goes beyond small number. There are two dimensionality problems. First, complexity exponentially increases with genes. Second, estimating probability distributions specifying We propose approximate method based on reinforcement learning that mitigates curses...
Probabilistic Boolean networks (PBNs) have been recently introduced as a paradigm for modeling genetic regulatory networks. One of the objectives PBN is to use network design and analysis intervention strategies aimed at moving out undesirable states, such those associated with disease, into desirable ones. To date, number proposed in context PBNs. However, all these techniques assume perfect knowledge transition probability matrix PBN. Such an assumption cannot be satisfied practice since...
In recent years, there has been an increasing interest in the field of big data analytics. It established that exist large amounts energy industry <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . However, is a need to develop methods combining domain knowledge transform this into meaningful information return business intelligence. The existing literature on analytics focuses applications various fields such as healthcare, aviation...