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1.
In this paper, the problem of the uniform stability for a class of fuzzy fractional-order genetic regulatory networks with random discrete delays, distributed delays, and parameter uncertainties is studied. Although there is a portion of literature on using fixed point theorems to study the stability of fractional neural networks, most of them required the fractional order to be in 1 2 , 1 . However, the case of the fractional-order belonging to ( 0 , 1 2 ) has not been discussed. To solve it, this work proposes a novel idea of using fixed point theory to study the stability of fuzzy (0,1) order neural networks, the problem of the uniqueness of the solution of the considered genetic regulatory networks is resolved, and a novel sufficient condition to guarantee the uniform stability of above genetic regulatory networks is also derived. Eventually, an example is given to demonstrate that the obtained result is effective.  相似文献   
2.
This Letter is concerned with the robust state estimation problem for uncertain time-delay Markovian jumping genetic regulatory networks (GRNs) with SUM logic, where the uncertainties enter into both the network parameters and the mode transition rate. The nonlinear functions describing the feedback regulation are assumed to satisfy the sector-like conditions. The main purpose of the problem addressed is to design a linear estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. By resorting to the Lyapunov functional method and some stochastic analysis tools, it is shown that if a set of linear matrix inequalities (LMIs) is feasible, the desired state estimator, that can ensure the estimation error dynamics to be globally robustly asymptotically stable in the mean square, exists. The obtained LMI conditions are dependent on both the lower and the upper bounds of the delays. An illustrative example is presented to demonstrate the feasibility of the proposed estimation schemes.  相似文献   
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Integrated information theory (IIT) provides a mathematical framework to characterize the cause-effect structure of a physical system and its amount of integrated information (Φ). An accompanying Python software package (“PyPhi”) was recently introduced to implement this framework for the causal analysis of discrete dynamical systems of binary elements. Here, we present an update to PyPhi that extends its applicability to systems constituted of discrete, but multi-valued elements. This allows us to analyze and compare general causal properties of random networks made up of binary, ternary, quaternary, and mixed nodes. Moreover, we apply the developed tools for causal analysis to a simple non-binary regulatory network model (p53-Mdm2) and discuss commonly used binarization methods in light of their capacity to preserve the causal structure of the original system with multi-valued elements.  相似文献   
6.
郑亚楠  王丹 《化学进展》2019,31(10):1372-1383
金属调控蛋白是微生物体内通过转录抑制或激活机制严格控制金属离子摄入、外排和储存的特异性金属离子结合蛋白,对维持体内适宜的金属离子浓度和平衡起着举足轻重的作用。本文综述了目前主要的七大家族金属调控蛋白的调控机制和拓扑结构,详细介绍了金属离子结合区域的结构特征和金属-配体的配位构型。基于金属-配体的配位构型,重点讨论了每类金属调控蛋白对目标金属离子特异性选择的机理。此外,本文还介绍了金属调控蛋白在重金属离子检测和吸附方面的应用,拓展了金属调控蛋白的研究和应用领域,同时为生物无机化学的研究方向开辟了新的思路。  相似文献   
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Reverse engineering of biochemical networks remains an important open challenge in computational systems biology. The goal of model inference is to, based on time-series gene expression data, obtain the sparse topological structure and parameters that quantitatively understand and reproduce the dynamics of biological systems. In this paper, we propose a multi-objective approach for the inference of S-System structures for Gene Regulatory Networks (GRNs) based on Pareto dominance and Pareto optimality theoretical concepts instead of the conventional single-objective evaluation of Mean Squared Error (MSE). Our motivation is that, using a multi-objective formulation for the GRN, it is possible to optimize the sparse topology of a given GRN as well as the kinetic order and rate constant parameters in a decoupled S-System, yet avoiding the use of additional penalty weights. A flexible and robust Multi-Objective Cellular Evolutionary Algorithm is adapted to perform the tasks of parameter learning and network topology inference for the proposed approach. The resulting software, called MONET, is evaluated on real-based academic and synthetic time-series of gene expression taken from the DREAM3 challenge and the IRMA in vivo datasets. The ability to reproduce biological behavior and robustness to noise is assessed and compared. The results obtained are competitive and indicate that the proposed approach offers advantages over previously used methods. In addition, MONET is able to provide experts with a set of trade-off solutions involving GRNs with different typologies and MSEs.  相似文献   
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Glucokinase (GK) plays a critical role in maintaining glucose homeostasis in the human liver and pancreas. In the liver, the activity of GK is modulated by the glucokinase regulatory protein (GKRP) which functions as a competitive inhibitor of glucose to bind to GK. Moreover, the inhibitory intensity of GKRP–GK is suppressed by fructose 1-phosphate (F1P), and reinforced by fructose 6-phosphate (F6P). Here, we employed a series of computational techniques to explore the interactions of fructose phosphates with GKRP. Calculation results reveal that F1P and F6P can bind to the same active site of GKRP with different binding modes, and electrostatic interaction provides a major driving force for the ligand binding. The presence of fructose phosphate severely influences the motions of protein and the conformational space, and the structural change of sugar phosphate influences its interactions with GKRP, leading to a large conformational rearrangement of loop2 in the SIS2 domain. In particular, the binding of F6P to GKRP facilitates the protruding loop2 contacting with GK to form the stable GK–GKRP complex. The conserved residues 179–184 of GKRP play a major role in the binding of phosphate group and maintaining the stability of GKRP. These results may provide deep insight into the regulatory mechanism of GKRP to the activity of GK.  相似文献   
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Abstract

Interferon regulatory factor-7 (IRF-7) is involved in pulmonary infection and pneumonia. Here, a synthetic strategy that combined quantitative structure–activity relationship (QSAR)-based virtual screening and in vitro binding assay was described to identify new and potent mediator ligands of IRF-7 from natural products. In the procedure, a QSAR scoring function was developed and validated using Gaussian process (GP) regression and a structure-based set of protein–ligand affinity data. By integrating hotspot pocket prediction, pharmacokinetics profile analysis and molecular docking calculations, the scoring function was successfully applied to virtual screening against a large library of structurally diverse, drug-like natural products. With the method we were able to identify a number of potential hits, from which several compounds were found to have moderate or high affinity to IRF-7 using fluorescence binding assays, with dissociation constants Kd at micromolar level. We have also examined the structural basis and noncovalent interactions of computationally modelled IRF-7 complex with its potent ligands. It is revealed that hydrophobic forces and van der Waals contacts play a central role in stabilization of the complex architecture, while few hydrogen bonds confer additional specificity for the protein–ligand recognition.  相似文献   
10.
In this paper, we investigate the stability and robust stability criteria for genetic regulatory networks with interval time-varying delays and Markovian jumping parameters. The genetic regulatory networks have a finite number of modes, which may jump from one mode to another according to the Markov process. By using Lyapunov–Krasovskii functional, some sufficient conditions are derived in terms of linear matrix inequalities to achieve the global asymptotic stability in the mean square of the considered genetic regulatory networks. Two numerical examples are provided to illustrate the usefulness of the obtained theoretical results.  相似文献   
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