Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Network graphs”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36Linked to original sources
PubMed2003

A structural representation of migraine diagnostic criteria: the experts' view.

OBJECTIVE: To generate an empirically derived structural representation of migraine diagnostic criteria in a group of international headache experts using the Pathfinder network scaling algorithm in order to evaluate the validity of the migraine criteria used in the International Headache Society (IHS) classification system. BACKGROUND: Because it is a disease entity that lacks objective defining markers, developing valid diagnostic criteria for migraine is a challenge. The IHS committee relied on expert consensus to develop their classification system in 1988. Expert consensus also was used to evaluate the validity of the IHS classification system, but further studies employing alternative methods still are needed. METHODS: Headache experts representing the Executive Committee of the IHS and the Board of Directors of the American Headache Society analyzed 14 criteria (7 IHS and 7 non-IHS) considered relevant in diagnosing migraine. Their ratings were submitted to the Pathfinder algorithm to generate a network structure reflecting the experts' conceptualization of migraine diagnostic criteria. RESULTS: The expert network had 3 groupings: headache characteristics (eg, phonophobia, unilateral pain, throbbing pain), biological contributing factors (eg, family history, hormonal relationship, relief with sleep), and triggering factors (eg, worse with stress, food triggers). The IHS criteria were clustered together in the center portion of the network. A t test showed that each IHS criterion was closer conceptually to other IHS criteria than to non-IHS criteria. Graph theory indices revealed that the most central criteria were unilateral pain, moderate/severe intensity, and nausea/vomiting. CONCLUSION: The structural representation of migraine diagnostic criteria from these international headache experts is consistent with the migraine diagnostic criteria set forth in the IHS classification system and thus provides further support for the validity of migraine criteria in the IHS system.

Algorithms↗
PubMed2005

Error threshold in optimal coding, numerical criteria, and classes of universalities for complexity.

The free energy of the random energy model at the transition point between the ferromagnetic and spin glass phases is calculated. At this point, equivalent to the decoding error threshold in optimal codes, the free energy has finite size corrections proportional to the square root of the number of degrees. The response of the magnetization to an external ferromagnetic phase is maximal at values of magnetization equal to one-half. We give several criteria of complexity and define different universality classes. According to our classification, at the lowest class of complexity are random graphs, Markov models, and hidden Markov models. At the next level is the Sherrington-Kirkpatrick spin glass, connected to neuron-network models. On a higher level are critical theories, the spin glass phase of the random energy model, percolation, and self-organized criticality. The top level class involves highly optimized tolerance design, error thresholds in optimal coding, language, and, maybe, financial markets. Living systems are also related to the last class. The concept of antiresonance is suggested for complex systems.

Journal Article↗
PubMed2000

Graphical tool for navigation within the semantic network of the UMLS metathesaurus on a locally installed database.

Knowledge in the environment of information technologies is bound to structured vocabularies. Medical data dictionaries are necessary for uniquely describing findings like diagnoses, procedures or functions. Therefore we decided to locally install a version of the Unified Medical Language System (UMLS) of the U.S. National Library of Medicine as a repository for defining entries of a medical multimedia database. Because of the requirement to extend the vocabulary in concepts and relations between existing concepts a graphical tool for appending new items to the database has been developed: Although the database is an instance of a semantic network the focus on single entries offers the opportunity of reducing the net to a tree within this detail. Based on the graph theorem, there are definitions of nodes of concepts and nodes of knowledge. The UMLS additionally offers the specification of sub-relations, which can be represented, too. Using this view it is possible to manage these 1:n-Relations in a simple tree view. On this background an explorer like graphical user interface has been realised to add new concepts and define new relationships between those and existing entries for adapting the UMLS for specific purposes such as describing medical multimedia objects.

Computer Graphics↗
PubMed2004

A hopfield network learning method for bipartite subgraph problem.

In this paper, we present a gradient ascent learning method of the Hopfield neural network for bipartite subgraph problem. The method is intended to provide a near-optimum parallel algorithm for solving the bipartite subgraph problem. To do this we use the Hopfield neural network to get a near-maximum bipartite subgraph, and increase the energy by modifying weights in a gradient ascent direction of the energy to help the network escape from the state of the near-maximum bipartite subgraph to the state of the maximum bipartite subgraph or better one. A large number of instances are simulated to verify the proposed method with the simulation results showing that the solution quality is superior to that of best existing parallel algorithm. We also test the learning method on total coloring problem. The simulation results show that our method finds optimal solution in every test graph.

Algorithms↗
PubMed2001

Symbolic dynamics and computation in model gene networks.

We analyze a class of ordinary differential equations representing a simplified model of a genetic network. In this network, the model genes control the production rates of other genes by a logical function. The dynamics in these equations are represented by a directed graph on an n-dimensional hypercube (n-cube) in which each edge is directed in a unique orientation. The vertices of the n-cube correspond to orthants of state space, and the edges correspond to boundaries between adjacent orthants. The dynamics in these equations can be represented symbolically. Starting from a point on the boundary between neighboring orthants, the equation is integrated until the boundary is crossed for a second time. Each different cycle, corresponding to a different sequence of orthants that are traversed during the integration of the equation always starting on a boundary and ending the first time that same boundary is reached, generates a different letter of the alphabet. A word consists of a sequence of letters corresponding to a possible sequence of orthants that arise from integration of the equation starting and ending on the same boundary. The union of the words defines the language. Letters and words correspond to analytically computable Poincare maps of the equation. This formalism allows us to define bifurcations of chaotic dynamics of the differential equation that correspond to changes in the associated language. Qualitative knowledge about the dynamics found by integrating the equation can be used to help solve the inverse problem of determining the underlying network generating the dynamics. This work places the study of dynamics in genetic networks in a context comprising both nonlinear dynamics and the theory of computation. (c) 2001 American Institute of Physics.

Journal Article↗
PubMed2006

Algorithmic and complexity results for decompositions of biological networks into monotone subsystems.

A useful approach to the mathematical analysis of large-scale biological networks is based upon their decompositions into monotone dynamical systems. This paper deals with two computational problems associated to finding decompositions which are optimal in an appropriate sense. In graph-theoretic language, the problems can be recast in terms of maximal sign-consistent subgraphs. The theoretical results include polynomial-time approximation algorithms as well as constant-ratio inapproximability results. One of the algorithms, which has a worst-case guarantee of 87.9% from optimality, is based on the semidefinite programming relaxation approach of Goemans-Williamson [Goemans, M., Williamson, D., 1995. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. J. ACM 42 (6), 1115-1145]. The algorithm was implemented and tested on a Drosophila segmentation network and an Epidermal Growth Factor Receptor pathway model, and it was found to perform close to optimally.

Algorithms↗
PubMed1995

The acquisition of the English past tense in children and multilayered connectionist networks.

The apparent very close similarity between the learning of the past tense by Adam and the Plunkett and Marchman model is exaggerated by several misleading comparisons--including arbitrary, unexplained changes in how graphs were plotted. The model's development differs from Adam's in three important ways: Children show a U-shaped sequence of development which does not depend on abrupt changes in input; U-shaped development in the simulation occurs only after an abrupt change in training regimen. Children overregularize vowel-change verbs more than no-change verbs; the simulation overregularizes vowel-change verbs less often than no-change verbs. Children, including Adam, overregularize more than they irregularize; the simulation overregularized less than it irregularized. Interestingly, the RM model--widely criticized as being inadequate--does somewhat better, correctly overregularizing vowel-change verbs more often than no-change verbs, and overregularizing more often than it irregularizes. Although Plunkett and Marchman's (1993) state of the art model incorporated hidden layers and back-propagation, used a more realistic phonological coding scheme, and explored a broader range of parameters than Rumelhart and McClelland's model, their results are farther from psychological reality. It is unknown whether any connectionist model can mimic a child's performance without resorting to unrealistic exogenous changes in the training or input, but it is clear that adding a hidden-layer and back-propagation does not ensure a solution.

Child Language↗
PubMed1995

Computer-assisted assignment of peptides with non-standard amino acids.

A comprehensive peptide assignment program and its application to a cyclic peptide, cyclosporin A, are presented in this paper. A group of graph theoretical algorithms using fuzzy logic are discussed with the aid of examples from cyclosporin A. The algorithms deal with heavily overlapped peaks, recover disjointed and distorted spin coupling networks, and include strategies for sequence-specific assignment. A procedure to extend the Protein Knowledge Base for automatically assigning non-standard amino acid residues is also presented. The program is capable of completely automated assignment for small peptides (approximately 20 residues). For such molecules, it is insensitive to whether the peptide chain is cyclic or acyclic, and to whether amide protons are present or absent. For larger peptides/proteins, more user interaction is required and the sequence-specific assignment step usually must proceed through fragments smaller than the full length to avoid problems due to occurrence of a combinatorial explosion. The program can be applied as a rigorous tool to check manual assignments. The fuzzy graph theoretical concepts built in the program are illustrated with 2D proton spectra of a peptide, but may be extended to higher-dimensional spectra, other biopolymers, natural products and other organic structures.

Algorithms↗
PubMed1999

3D reconstruction of the cerebral arterial network from stereotactic DSA.

The authors present an automatic algorithm for 3D reconstruction of cerebral blood vessels by digital subtracted angiography. The patient is localized by a stereotactic method. The reconstruction algorithm includes two steps: first vessel extraction then 2D matching and reconstruction. Accurate vessel skeletons are generated by a combination of mathematical morphological algorithms and adaptive filters. The 3D reconstruction algorithm is based on the reconstruction of vessels center lines. For that purpose, three different projections of the vascular network are used. Reconstruction is computed segment by segment (a curved line between two nodes). For each segment point, the algorithm defines all epipolar solutions on the other views. These epipolar solutions are sorted and pooled by 2D continuity and 3D proximity criteria resulting in a 3D graph. Optimal 3D segment is defined by a recursive algorithm that looks up the better path in the 3D graph. The algorithms have been implemented on a Compatible-PC computer in C language. More than 95% of static copper phantom was reconstructed in 5 min and with 1 mm 3D accuracy. 70% of arteries (from carotid to the seventh node) of a true patient arterial network were reconstructed is less than 30 min.

Algorithms↗
PubMed2005

A query language for biological networks.

MOTIVATION: Many areas of modern biology are concerned with the management, storage, visualization, comparison and analysis of networks, but no appropriate query language for such complex data structures yet exists. RESULTS: We have designed and implemented the pathway query language (PQL) for querying large protein interaction or pathway databases. PQL is based on a simple graph data model with extensions reflecting properties of biological objects. Queries match subgraphs in the database based on node properties and paths between nodes. The syntax is easy to learn for anybody familiar with SQL. As an important feature, a query may require a certain structure in the database to exist but return a different subgraph. We have tested PQL queries on networks of up to 16,000 nodes and found it to scale very well. AVAILABILITY: The code is available on request from the author.

Computational Biology↗
PubMed2006

Gene networks as a tool to understand transcriptional regulation.

Gene regulatory networks, or simply gene networks (GNs), have shown to be a promising approach that the bioinformatics community has been developing for studying regulatory mechanisms in biological systems. GNs are built from the genome-wide high-throughput gene expression data that are often available from DNA microarray experiments. Conceptually, GNs are (un)directed graphs, where the nodes correspond to the genes and a link between a pair of genes denotes a regulatory interaction that occurs at transcriptional level. In the present study, we had two objectives: 1) to develop a framework for GN reconstruction based on a Bayesian network model that captures direct interactions between genes through nonparametric regression with B-splines, and 2) to demonstrate the potential of GNs in the analysis of expression data of a real biological system, the yeast pheromone response pathway. Our framework also included a number of search schemes to learn the network. We present an intuitive notion of GN theory as well as the detailed mathematical foundations of the model. A comprehensive analysis of the consistency of the model when tested with biological data was done through the analysis of the GNs inferred for the yeast pheromone pathway. Our results agree fairly well with what was expected based on the literature, and we developed some hypotheses about this system. Using this analysis, we intended to provide a guide on how GNs can be effectively used to study transcriptional regulation. We also discussed the limitations of GNs and the future direction of network analysis for genomic data. The software is available upon request.

Bayes Theorem↗
PubMed2004

Proteomic traces of speciation.

Recent work has shown that the network of structural similarity between protein domains exhibits a power-law distribution of edges per node. The scale-free nature of this graph, termed the protein domain universe graph or PDUG, may be reproduced via a divergent model of structural evolution. The performance of this model, however, does not preclude the existence of a successful convergent model. To further resolve the issue of protein structural evolution, we explore the predictions of both convergent and divergent models directly. We show that when nodes from the PDUG are partitioned into subgraphs on the basis of their occurrence in the proteomes of particular organisms, these subgraphs exhibit a scale-free nature as well. We explore a simple convergent model of structural evolution and find that the implications of this model are inconsistent with features of these organismal subgraphs. Importantly, we find that biased convergent models are inconsistent with our data. We find that when speciation mechanisms are added to a simple divergent model, subgraphs similar to the organismal subgraphs are produced, demonstrating that dynamic models can easily explain the distributions of structural similarity that exist within proteomes. We show that speciation events must be included in a divergent model of structural evolution to account for the non-random overlap of structural proteomes. These findings have implications for the long-standing debate over convergent and divergent models of protein structural evolution, and for the study of the evolution of organisms as a whole.

Bacterial Proteins↗
PubMed2005

Phase transition in the link weight structure of networks.

When transport in networks follows the shortest paths, the link weights are shown to play a crucial role. If the underlying topology with nodes N is not changed and if the link weights are independent from each other, then we show that, by tuning the link weights, a phase transition occurs around a critical extreme value index alphac of the link weight distribution alpha<alphac. If the extreme value index of the link weight distribution , transport in the network traverses many links whereas for , all transport flows over a critical backbone consisting of N-1 links. For connected Erdös-Rényi random graphs Gp(N) and square lattices, we have characterised the phase transition and found that alphac approximately =bN(-beta) with betaGp(N) and betalattice approximately = 0.62.

Journal Article↗
PubMed2004

Graph-based iterative Group Analysis enhances microarray interpretation.

BACKGROUND: One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically important associations between the differentially expressed genes. A large part of the relevant functional evidence can be represented in the form of graphs, e.g. metabolic and signaling pathways, protein interaction maps, shared GeneOntology annotations, or literature co-citation relations. Such graphs are easily constructed from available genome annotation data. The problem of biological interpretation can then be described as identifying the subgraphs showing the most significant patterns of gene expression. We applied a graph-based extension of our iterative Group Analysis (iGA) approach to obtain a statistically rigorous identification of the subgraphs of interest in any evidence graph. RESULTS: We validated the Graph-based iterative Group Analysis (GiGA) by applying it to the classic yeast diauxic shift experiment of DeRisi et al., using GeneOntology and metabolic network information. GiGA reliably identified and summarized all the biological processes discussed in the original publication. Visualization of the detected subgraphs allowed the convenient exploration of the results. The method also identified several processes that were not presented in the original paper but are of obvious relevance to the yeast starvation response. CONCLUSIONS: GiGA provides a fast and flexible delimitation of the most interesting areas in a microarray experiment, and leads to a considerable speed-up and improvement of the interpretation process.

Algorithms↗
PubMed2006

A novel functional module detection algorithm for protein-protein interaction networks.

BACKGROUND: The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically evaluate a novel clustering technique for clustering and detecting functional modules in protein-protein interaction networks, termed STM. RESULTS: STM selects representative proteins for each cluster and iteratively refines clusters based on a combination of the signal transduced and graph topology. STM is found to be effective at detecting clusters with a diverse range of interaction structures that are significant on measures of biological relevance. The STM approach is compared to six competing approaches including the maximum clique, quasi-clique, minimum cut, betweeness cut and Markov Clustering (MCL) algorithms. The clusters obtained by each technique are compared for enrichment of biological function. STM generates larger clusters and the clusters identified have p-values that are approximately 125-fold better than the other methods on biological function. An important strength of STM is that the percentage of proteins that are discarded to create clusters is much lower than the other approaches. CONCLUSION: STM outperforms competing approaches and is capable of effectively detecting both densely and sparsely connected, biologically relevant functional modules with fewer discards.

Journal Article↗
PubMed1996

Quality assurance for abdominal CT: a rapid, computer-assisted technique.

OBJECTIVE: Maintaining high standards in a large CT imaging department with multiple scanners, a large technical and clerical staff, and a rotating staff of radiologists is an ongoing challenge. We undertook a project to design and implement a simple, rapidly performed computer-assisted system of quality assurance (QA) for use in abdominal CT. In our project, we also analyzed the results of that QA system. MATERIALS AND METHODS: We graded 1810 abdominal CT studies done in a 50-week period, using a three-point scale to indicate the quality of the following five parameters of technical quality: IV contrast enhancement, oral contrast opacification, window settings and artifacts, conformity to radiologists' protocol, and completeness and accuracy of header and scout data. In addition, a parameter reflecting performance of the film library and clerical staff was similarly graded. To provide a measure of peer review for radiologists, any disagreements with prior CT study reports were recorded when comparison studies were reviewed in the process of CT interpretation. A commercially available spreadsheet and database software program was tailored to allow rapid, easily performed data entry and analysis. Tables and graphs showing performance of technologists and film library and clerical staff were generated. This customized program was made available on the radiology department computer network. Results generated by the program were further analyzed with linear regression models. RESULTS: Our QA system was successfully integrated into the routine operation of the abdominal CT division. During the first 11.5 months of operation, the system reflected improvement in each of the technical parameters with a statistically significant improvement in the combined average technical score (from 1.15 to 1.68 on a scale of 0-2; p < .0001). The "Throughout Speed/Old Exams" parameter for performance of the film library and clerical staff, which was analyzed separately from the technical parameters, also improved significantly (from 1.3 to 1.8; p < .02). Improvements were statistically significant, even when we controlled for potential variations in quality among different CT scanners and variations among the radiologists who rated the quality of the examination. Thirty-eight disagreements with previous scan interpretations (5% of all scan comparisons) were recorded for evaluation at peer review conferences. CONCLUSION: The ability to monitor performance continuously using a rapid, computer-assisted system has effected measurable improvement in our CT service. Technologist and film library and clerical staff performance improved for all parameters studied. Deficiencies were revealed and trends demonstrated. The QA system allowed us to identify disagreements in interpretation of CT examinations for subsequent peer review by radiologists. Our QA software program has been made available on the Internet as freeware to licensed Excel users via anonymous file transfer protocol at Internet Protocol 134.192.6.110.

Administration, Oral↗
PubMed1996

A top-down approach to whole genome visualization.

The investigation of large DNA contigs like complete chromosomes or genomes requires novel methods of data visualization. The complex information contained in a genome, particularly the relation of its individual genetic elements, needs to be accessible in a comprehensive, intelligent and intelligible manner. The yeast genome is expected to contain more than 6,000 Open Reading Frames (ORFs). As yet, the function of many of these ORFs has not been characterized satisfactorily. Also, many ORFs are found to have redundant copies elsewhere in the genome that originated from common ancestors. Other genetic elements (e.g. Tss, delta-elements, t-RNAs) are present in multiple copies. To visualize these relationships, a top-down "genome browser" is introduced that enables inspection of genomic data at different levels of abstraction (e.g. chromosomes, coding/non-coding regions, high/low levels of similarity). This novel tool is a key component for the integrated services approach to biological sequence data management (Heumann et al. 1995) and is accessible through the world wide web (WWW). This work demonstrates how the genome browser visualizes the results of an all-against-all comparison of the elements in the yeast genome as a graph. Interactive navigational queries across yeast chromosomes along the lines of sequence similarity open versatile options for the detailed investigation of genome properties. For sequence comparison the hashed position tree HPT (Mewes & Heumann 1995) is applied. Sequence similarity relationships are represented using the genome similarity graph (GSG) (Heumann & Mewes 1996c).

Chromosomes, Fungal↗
PubMed2006

Qualitative analysis of the relation between DNA microarray data and behavioral models of regulation networks.

We introduce a mathematical framework that allows to test the compatibility between differential data and knowledge on genetic and metabolic interactions. Within this framework, a behavioral model is represented by a labeled oriented interaction graph; its predictions can be compared to experimental data. The comparison is qualitative and relies on a system of linear qualitative equations derived from the interaction graph. We show how to partially solve the qualitative system, how to identify incompatibilities between the model and the data, and how to detect competitions in the biological processes that are modeled. This approach can be used for the analysis of transcriptomic, metabolic or proteomic data.

Fatty Acids↗