• genomic
  • Many genome-scale data are available in soybean including genomic sequence, transcriptomics (microarray, RNA-seq), proteomics and metabolomics datasets, together with growing knowledge of soybean in gene, microRNAs, pathways, and phenotypes. (missouri.edu)
  • Reported DEGs can be used as genomic resource for future discovery of candidate genes associated with herbicide tolerance. (frontiersin.org)
  • 1997. The hardwiring of development: organization and function of genomic regulatory systems. (wikipedia.org)
  • The RegCreative jamboree was stimulated by a community initiative to curate in perpetuity the genomic sequences which have been experimentally determined to control gene expression. (wikipedia.org)
  • dynamical
  • Once a domain mostly reserved for experts, dynamical modelling of gene regulatory and reaction networks has been an area of growth over the last decade. (royalsocietypublishing.org)
  • Ruet, P., Thieffry, D.: Graphic requirements for multistability and attractive cycles in a boolean dynamical framework. (springer.com)
  • A Boolean network is a particular kind of sequential dynamical system, where time and states are discrete, i.e. both the set of variables and the set of states in the time series each have a bijection onto an integer series. (wikipedia.org)
  • Since a Boolean network has only 2N possible states, a trajectory will sooner or later reach a previously visited state, and thus, since the dynamics are deterministic, the trajectory will fall into a steady state or cycle called an attractor (though in the broader field of dynamical systems a cycle is only an attractor if perturbations from it lead back to it). (wikipedia.org)
  • In dynamical systems theory, the structure and length of the attractors of a network corresponds to the dynamic phase of the network. (wikipedia.org)
  • organism
  • For example, learning when nutrients are going to be present in the environment allows the organism to selectively express genes that will take up the food source, thus allowing the organism to harvest energy. (wikipedia.org)
  • algorithms
  • The framework of the models, which provides algorithms for discovering and analyzing structure in complex distributions to describe them succinctly and extract the unstructured information, allows them to be constructed and utilized effectively. (wikipedia.org)
  • The target sequences and the regulated genes can be listed for each TF, which can be used as benchmark for TFBS recognition tools or as training sets for new TFBS recognition algorithms. (wikipedia.org)
  • Boolean
  • Methods of robustness analysis for Boolean models of gene control networks. (springer.com)
  • A Boolean network consists of a discrete set of Boolean variables each of which has a Boolean function (possibly different for each variable) assigned to it which takes inputs from a subset of those variables and output that determines the state of the variable it is assigned to. (wikipedia.org)
  • Boolean networks have been used in biology to model regulatory networks. (wikipedia.org)
  • Boolean networks are related to cellular automata. (wikipedia.org)
  • clarification needed] A random Boolean network (RBN) is one that is randomly selected from the set of all possible boolean networks of a particular size, N. One then can study statistically, how the expected properties of such networks depend on various statistical properties of the ensemble of all possible networks. (wikipedia.org)
  • The stability of Boolean networks depends on the connections of their nodes. (wikipedia.org)
  • A Boolean network can exhibit stable, critical or chaotic behavior. (wikipedia.org)
  • model
  • The Process Hitting (PH) is a recently introduced framework to model concurrent processes. (springer.com)
  • PH is suitable to model Biological Regulatory Networks (BRNs) with complete or partial knowledge of cooperations between regulators by defining the most permissive dynamics with respect to these constraints. (springer.com)
  • The simulation based on this model, though currently limited in scope in terms of the biology it represents, supports the utility of the Halley and Winkler branching process model in describing the behaviour of stem cell gene regulatory networks. (york.ac.uk)
  • We wanted a quick and easy way to visualize the weight parameters from the model which represent the direction and magnitude of the influence of a transcription factor on its target gene, so we created GRNsight. (peerj.com)
  • If the network structure of the model is a directed acyclic graph, the model represents a factorization of the joint probability of all random variables. (wikipedia.org)
  • This type of graphical model is known as a directed graphical model, Bayesian network, or belief network. (wikipedia.org)
  • A Markov random field, also known as a Markov network, is a model over an undirected graph. (wikipedia.org)
  • This suggests a potential model for module evolution whereby modules form from a system's tendency to resist maximizing connections to create more efficient and compartmentalized network topologies. (wikipedia.org)
  • EVE is a simulation framework that is able to model predictive internal models around of complex environments. (wikipedia.org)
  • Graph
  • GRNsight automatically lays out either an unweighted or weighted network graph based on an Excel spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows, a Simple Interaction Format (SIF) text file, or a GraphML XML file. (peerj.com)
  • When a user uploads an input file specifying an unweighted network, GRNsight automatically lays out the graph using black lines and pointed arrowheads. (peerj.com)
  • Degree (or connectivity, a distinct usage from that used in graph theory) is the number of edges that connect a node, while betweenness is a measure of how central a node is in a network. (wikipedia.org)
  • evolutionary
  • A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network. (wikipedia.org)
  • Against such strong positive selection, other evolutionary forces acting on the network must exist, with gaps of relaxed selection, to allow focused reorganization to occur. (wikipedia.org)
  • Recent studies have indicated conservation of molecular networks through deep evolutionary time. (wikipedia.org)
  • This objective is of fundamental importance to evolutionary analysis and translational research as regulatory mechanisms are widely implicated in species-specific adaptation and the etiology of disease. (wikipedia.org)
  • annotations
  • It has many useful tools including Affymetrix probeID search, gene family search, multiple gene/metabolite analysis, motif prediction tool, protein 3D structure viewer and download/upload capacity for experimental data and annotations. (missouri.edu)
  • discrete
  • The paper sets up the validation framework, provides examples of distance functions, and applies them to some discrete Markov network models. (eurekaselect.com)
  • Modularity refers to the ability of a system to organize discrete, individual units that can overall increase the efficiency of network activity and, in a biological sense, facilitates selective forces upon the network. (wikipedia.org)
  • Usually, the dynamics of the system is taken as a discrete time series where the state of the entire network at time t+1 is determined by evaluating each variable's function on the state of the network at time t. (wikipedia.org)
  • promoters
  • They are major regulatory units and around 50% of CpG islands are located in gene promoter regions, while another 25% lie in gene bodies, often serving as alternative promoters. (wikipedia.org)
  • nodes
  • Nodes are rectangular and support gene labels of up to 12 characters. (peerj.com)
  • GRNsight is best-suited for visualizing networks of fewer than 35 nodes and 70 edges, although it accepts networks of up to 75 nodes or 150 edges. (peerj.com)
  • Nodes and edges are the basic components of a network. (wikipedia.org)
  • In social networks, nodes with high degree or high betweenness may play important roles in the overall composition of a network. (wikipedia.org)
  • This set of functions in effect determines a topology (connectivity) on the set of variables, which then become nodes in a network. (wikipedia.org)
  • In this, with "initially close states" one means that the Hamming distance is small compared with the number of nodes ( N {\displaystyle N} ) in the network. (wikipedia.org)
  • Cognitive
  • His inventions include the design of the first random access fibre-optics local area network, a patented admission control technique for ATM networks, a neural network based anomaly detector for brain magnetic resonance scans, and the cognitive packet network routing protocol to offer quality of service to users. (wikipedia.org)
  • Markov
  • Both directed acyclic graphs and undirected graphs are special cases of chain graphs, which can therefore provide a way of unifying and generalizing Bayesian and Markov networks. (wikipedia.org)
  • data
  • EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos. (amedeo.com)
  • It also considers approximate validation methods based on data for which the generating network is not known, the kind of situation one faces when using real data. (eurekaselect.com)
  • They gathered the measurement data of medical laboratory tests (e.g. hemoglobin level ) for a number of patients and they calculated the Pearson correlation between the results for each pair of tests and the pairs of tests which showed a correlation higher than a certain level were connected in the network (e.g. insulin level with blood sugar). (wikipedia.org)
  • Gelenbe has contributed pioneering research concerning the performance of multiprogramming computer systems, virtual memory management, data base reliability optimisation, distributed systems and network protocols. (wikipedia.org)
  • models
  • In this work we review the strategies, tools, current advances, and recent models of mammalian cells, focusing mainly on metabolism, but discussing the methodology applied to other types of networks as well. (springerprofessional.de)
  • The first part of this thesis is about the Web application GEne Network GEnerator (GeNGe) which I have developed as a framework for automatic generation of gene regulatory network models. (hu-berlin.de)
  • created a series of models that compared the efficiency of various evolved network topologies in an environment where performance, their only metric for selection, was taken into account, and another treatment where performance as well as the connectivity cost were factored together. (wikipedia.org)
  • Volume 2 contains a variety of neural network models that investigate how these representations change during learning (including models from Randy O'Reilly, Matthew Schlesinger and Yuko Munakata). (wikipedia.org)
  • signals
  • Signals are transduced within cells or in between cells and thus form complex signaling networks. (wikipedia.org)
  • Also, the inductive signals and the genes involved are different from those that control animal development. (wikipedia.org)
  • topology
  • Such theoretical studies have revealed that biological networks share many features with other networks such as the Internet or social networks, e.g. their network topology. (wikipedia.org)
  • The conditions of stability are the same in the case of networks with scale-free topology where the in-and out-degree distribution is a power-law distribution: P ( K ) ∝ K − γ {\displaystyle P(K)\propto K^{-\gamma }} , and ⟨ K i n ⟩ = ⟨ K o u t ⟩ {\displaystyle \langle K^{in}\rangle =\langle K^{out}\rangle } , since every out-link from a node is an in-link to another. (wikipedia.org)
  • cell fate
  • However, because of the complexity of both the core pluripotency network and the process of cell fate computation it is not yet possible to control the fate of stem cells. (york.ac.uk)