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At least 757 records · Page 42Linked to original sources
PubMed2006

Spatio-temporal statistical models for river monitoring networks.

When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.

Data Collection↗
PubMed2004

Tuning organogels and mesophases with phenanthroline ligands and their copper complexes by inter- to intramolecular hydrogen bonds.

A novel family of highly functionalized molecules consisting of a central 4-methyl-3,5-diacylaminobenzene platform linked in close proximity to the methyl group by two lateral aromatic rings each equipped with two long alkoxy chains has been rationally designed. The presence of amide tethers and a chelating phenanthroline fragment connected via an ester dipole formed a new class of gelating reagents and mesomorphic materials. A few of these compounds have the tendency to form macromolecule-like aggregates through noncovalent interactions in hydrocarbon solvents and were found to exhibit thermotropic cubic mesophases. In light of the X-ray molecular structure of the methoxy ligand, an infinite network maintained by intermolecular hydrogen bonds as well as by pi-pi stacking of the phenyl subunits was evidenced. FT-IR studies confirm that the common driving force for aggregation in the organogels and microsegregation in the mesophase is the occurrence of a tight intermolecular H-bonded network that does not persist in diluted solution. This situation is switched when the ligands are interlocked by a copper(I) cation. A strong intramolecular H-bond confirmed by X-ray diffraction of a single crystal for the methoxy case provides very stable complexes but inhibits the gelation of the solvents. Heating the complexes bearing long paraffin chains (n = 12 and 16) in the dried state leads to a self-organization into a columnar liquid-crystalline phase in which the columns are arranged along a 2D oblique symmetry as deduced from powder XRD experiments. In this case, the complexes with the appended counteranions self-assemble in a specific way to form columns. A striking observation is that the intramolecular hydrogen bond persists in the mesophase as it does in solution without any evidence of an extended network. As far as we are aware, these ligands and complexes are rare examples in which organogelation and thermotropic mesomorphic behavior could be observed in parallel with molecules bearing a chelating platform. Due to the synthetic availability of the 4-methyl-3,5-diacylaminobenzene core and the simplicity by which the chelating platforms can be graphed, this methodology represents a practical alternative to the production of functionalized organogelators and mesomorphic materials.

Journal Article↗
PubMed2005

Graph-representation of oxidative folding pathways.

BACKGROUND: The process of oxidative folding combines the formation of native disulfide bond with conformational folding resulting in the native three-dimensional fold. Oxidative folding pathways can be described in terms of disulfide intermediate species (DIS) which can also be isolated and characterized. Each DIS corresponds to a family of folding states (conformations) that the given DIS can adopt in three dimensions. RESULTS: The oxidative folding space can be represented as a network of DIS states interconnected by disulfide interchange reactions that can either create/abolish or rearrange disulfide bridges. We propose a simple 3D representation wherein the states having the same number of disulfide bridges are placed on separate planes. In this representation, the shuffling transitions are within the planes, and the redox edges connect adjacent planes. In a number of experimentally studied cases (bovine pancreatic trypsin inhibitor, insulin-like growth factor and epidermal growth factor), the observed intermediates appear as part of contiguous oxidative folding pathways. CONCLUSIONS: Such networks can be used to visualize folding pathways in terms of the experimentally observed intermediates. A simple visualization template written for the Tulip package http://www.tulip-software.org/ can be obtained from V.A.

Animals↗
PubMed2006

Comparative genomics and protein domain graph analyses link ubiquitination and RNA metabolism.

The human gene parkin, known to cause familial Parkinson disease, as well as several other genes, likely involved in other neurodegenerative diseases or in cancer, encode proteins of the RBR family of ubiquitin ligases. Here, we describe the structural diversity of the RBR family in order to infer their functional roles. Of particular interest is a relationship detected between RBR-mediated ubiquitination and RNA metabolism: a few RBR proteins contain RNA binding domains and DEAH-box RNA helicase domains. Global protein domain graph analyses demonstrate that this connection is not RBR-specific, but instead many other proteins contain both ubiquitination and RNA-related domains. These proteins are present in animals, plants and fungi, suggesting that the link between these two cellular processes is ancient. Our results show that global bioinformatic approaches, involving comparative genomics and domain network analyses, may unearth novel functional relationships involving well-known and thoroughly studied groups of proteins.

Algorithms↗
PubMed2006

How do brain tumors alter functional connectivity? A magnetoencephalography study.

OBJECTIVE: This study was undertaken to test the hypothesis that brain tumors interfere with normal brain function by disrupting functional connectivity of brain networks. METHODS: Functional connectivity was assessed by computing the synchronization likelihood in a broad band (0.5-60Hz) or in the gamma band (30-60Hz) between all pairwise combinations of magnetoencephalography signals. Magnetoencephalography recordings were made at rest in 17 brain tumor patients and 15 healthy control subjects. For a given threshold of synchronization likelihood values, graphs of the suprathreshold connections between each magnetoencephalography channel and the others channels were built. RESULTS: In some regions, a variable number of channels without connectivity (missing connective points) at this threshold was found. The number of missing connective points was higher in patients with brain tumors than in control subjects (p < 0.0001, broad and gamma band) and was higher for left-sided than right-sided tumors (p = 0.008, broad band; p < 0.0001, gamma band). Individual results analysis indicates that the majority of brain tumor patients display several regions with missing connective point alterations in the affected and in the contralateral hemisphere. INTERPRETATION: Our findings suggest that brain tumors induce a loss of functional connectivity that affects multiple brain regions, and that left side brain tumors have the more severe consequences in this respect.

Adult↗
PubMed2000

Biobibliometrics: information retrieval and visualization from co-occurrences of gene names in Medline abstracts.

Successful information retrieval from biomedical literature databases is becoming increasingly difficult. We have developed a prototype system for retrieving and visualizing information from literature and genomic databases using gene names. The premise of our work is that, if two genes have a related biological function, the co-occurrence of two gene names (or aliases of those genes) within the biomedical literature is more likely. From a collection of Medline documents, we have extracted the number of co-occurrences of every pair of Saccharomyces cerevisiae genes. The query is automatically conflated to include gene aliases as well. In addition, the retrieved document set can be filtered by the user with a MeSH term. From this co-occurrence data we construct a matrix that contains dissimilarity measurements of every pair of genes, based on their joint and individual occurrence statistics. A graph is generated from this matrix, with node and edge inclusion being determined by a user-defined threshold. Nodes of the graph represent genes, while edge lengths are a function of the occurrence of the two genes within the literature. Nodes can be hypertext-linked to sequence databases, while edges are linked to those Medline documents that generated them. The system is a tool for efficiently exploring the biomedical information landscape and may act as a inference network.

Databases, Factual↗
PubMed1997

Identification of synaptic connections in neural ensembles by graphical models.

A method for the identification of direct synaptic connections in a larger neural net is presented. It is based on a conditional correlation graph for multivariate point processes. The connections are identified via the partial spectral coherence of two neurons, given all others. It is shown how these coherences can be calculated by inversion of the spectral density matrix. In simulations with GENESIS, we discuss the relevance of the method for identifying different neural ensembles including an excitatory feedback loop and networks with lateral inhibitions.

Computer Graphics↗
PubMed2003

CLICK and EXPANDER: a system for clustering and visualizing gene expression data.

MOTIVATION: Microarrays have become a central tool in biological research. Their applications range from functional annotation to tissue classification and genetic network inference. A key step in the analysis of gene expression data is the identification of groups of genes that manifest similar expression patterns. This translates to the algorithmic problem of clustering genes based on their expression patterns. RESULTS: We present a novel clustering algorithm, called CLICK, and its applications to gene expression analysis. The algorithm utilizes graph-theoretic and statistical techniques to identify tight groups (kernels) of highly similar elements, which are likely to belong to the same true cluster. Several heuristic procedures are then used to expand the kernels into the full clusters. We report on the application of CLICK to a variety of gene expression data sets. In all those applications it outperformed extant algorithms according to several common figures of merit. We also point out that CLICK can be successfully used for the identification of common regulatory motifs in the upstream regions of co-regulated genes. Furthermore, we demonstrate how CLICK can be used to accurately classify tissue samples into disease types, based on their expression profiles. Finally, we present a new java-based graphical tool, called EXPANDER, for gene expression analysis and visualization, which incorporates CLICK and several other popular clustering algorithms. AVAILABILITY: http://www.cs.tau.ac.il/~rshamir/expander/expander.html

Algorithms↗
PubMed2006

Network community structure and loop coefficient method.

A modular structure, in which groups of tightly connected nodes could be resolved as separate entities, is a property that can be found in many complex networks. In this paper, we propose a algorithm for identifying communities in networks. It is based on a local measure, so-called loop coefficient that is a generalization of the clustering coefficient. Nodes with a large loop coefficient tend to be core inner community nodes, while other vertices are usually peripheral sites at the borders of communities. Our method gives satisfactory results for both artificial and real-world graphs, if they have a relatively pronounced modular structure. This type of algorithm could open a way of interpreting the role of nodes in communities in terms of the local loop coefficient, and could be used as a complement to other methods.

Journal Article↗
PubMed2005

HierS: hierarchical scaffold clustering using topological chemical graphs.

An exhaustive ring-based algorithm, HierS, has been developed in order to provide an intuitive approach to compound clustering for analyzing high-throughput screening results. The recursive algorithm rapidly identifies all possible ring-delimited substructures within a set of compounds. Molecules are grouped by shared ring substructures (scaffolds) so that common scaffolds obtain higher membership. Once all of the scaffolds for a set of compounds are identified, the hierarchical structural relationships between the scaffold structures are established. The complex network of hierarchical relationships is then utilized to navigate compounds in a structurally directed fashion. When the scaffold hierarchy is traversed, over-represented structural features can be rapidly identified so that excess compounds that contain them can be removed without significantly impacting the structural diversity landscape of the compound set. Furthermore, the removed compounds can provide the opportunity to follow-up on active compounds that had previously been discarded because of practical limitations on follow-up capacity. A Web-based interface has been developed that incorporates this algorithm in order to allow for an interactive analysis. In addition, biological data are coupled to scaffolds by the inclusion of activity histograms, which indicate how the compounds in each scaffold class performed in previous high-throughput screening campaigns.

Algorithms↗
PubMed2003

Deriving phylogenetic trees from the similarity analysis of metabolic pathways.

MOTIVATION: Comparative analysis of metabolic pathways in different genomes can give insights into the understanding of evolutionary and organizational relationships among species. This type of analysis allows one to measure the evolution of complete processes (with different functional roles) rather than the individual elements of a conventional analysis. We present a new technique for the phylogenetic analysis of metabolic pathways based on the topology of the underlying graphs. A distance measure between graphs is defined using the similarity between nodes of the graphs and the structural relationship between them. This distance measure is applied to the enzyme-enzyme relational graphs derived from metabolic pathways. Using this approach, pathways and group of pathways of different organisms are compared to each other and the resulting distance matrix is used to obtain a phylogenetic tree. RESULTS: We apply the method to the Citric Acid Cycle and the Glycolysis pathways of different groups of organisms, as well as to the Carbohydrate metabolic networks. Phylogenetic trees obtained from the experiments were close to existing phylogenies and revealed interesting relationships among organisms.

Algorithms↗
PubMed2003

Scaling laws for the movement of people between locations in a large city.

Large scale simulations of the movements of people in a "virtual" city and their analyses are used to generate insights into understanding the dynamic processes that depend on the interactions between people. Models, based on these interactions, can be used in optimizing traffic flow, slowing the spread of infectious diseases, or predicting the change in cell phone usage in a disaster. We analyzed cumulative and aggregated data generated from the simulated movements of 1.6 x 10(6) individuals in a computer (pseudo-agent-based) model during a typical day in Portland, Oregon. This city is mapped into a graph with 181,206 nodes representing physical locations such as buildings. Connecting edges model individual's flow between nodes. Edge weights are constructed from the daily traffic of individuals moving between locations. The number of edges leaving a node (out-degree), the edge weights (out-traffic), and the edge weights per location (total out-traffic) are fitted well by power-law distributions. The power-law distributions also fit subgraphs based on work, school, and social/recreational activities. The resulting weighted graph is a "small world" and has scaling laws consistent with an underlying hierarchical structure. We also explore the time evolution of the largest connected component and the distribution of the component sizes. We observe a strong linear correlation between the out-degree and total out-traffic distributions and significant levels of clustering. We discuss how these network features can be used to characterize social networks and their relationship to dynamic processes.

Community Networks↗
PubMed1988

Computer graphics in medicine: a survey.

Increased interest is presently given to three-dimensional (3-D) medical applications due to simultaneous emergence of high-resolution imaging systems and computer graphics techniques. This paper intends to present a survey of this field together with discussion and prospective views. The general framework is composed of six parts: data acquisition and preprocessing, polygonal object representation, voxel description, system architecture, medical applications, and prospects. Data base acquisition includes characterization of imaging modalities and medical specificity. Preprocessing schemes are directed to improvements (filtering), windowing, and spatial anisotropy (linear or spline interpolation). The two following sections are devoted to descriptions of the main object representations. Particular emphasis is given to optimal contour approximation, surface triangulation, mathematical surfaces on one hand, and cuberille and voxel representations on the other. Display capabilities--hidden surface removal, surface normal shading, structure enhancement--and data base structuration--hierarchical and nonhierarchical (graph and tree encoding)--are, respectively, described. An overview of 3-D systems is further given (Section V), and features of medical applications are reviewed and gathered in basic functionalities, surgery, and radiotherapy specifications (Section VI). The last section provides some prospective views on reconstruction from a few projections, model-guided labeling, multimodality image overlay, and local image network. Some of these issues are illustrated by examples of 3-D images.

Computer Graphics↗
PubMed1994

Expert system support using Bayesian belief networks in the diagnosis of fine needle aspiration biopsy specimens of the breast.

AIM: To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast. METHODS: Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node. RESULTS: The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. Atypical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases. CONCLUSION: The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

Bayes Theorem↗
PubMed2005

Dynamic algorithms for the shortest path routing problem: learning automata-based solutions.

This paper presents the first Learning Automaton-based solution to the dynamic single source shortest path problem. It involves finding the shortest path in a single-source stochastic graph topology where there are continuous probabilistic updates in the edge-weights. The algorithm is significantly more efficient than the existing solutions, and can be used to find the "statistical" shortest path tree in the "average" graph topology. It converges to this solution irrespective of whether there are new changes in edge-weights taking place or not. In such random settings, the proposed learning automata solution converges to the set of shortest paths. On the other hand, the existing algorithms will fail to exhibit such a behavior, and would recalculate the affected shortest paths after each weight-change. The important contribution of the proposed algorithm is that all the edges in a stochastic graph are not probed, and even if they are, they are not all probed equally often. Indeed, the algorithm attempts to almost always probe only those edges that will be included in the shortest path graph, while probing the other edges minimally. This increases the performance of the proposed algorithm. All the algorithms were tested in environments where edge-weights change stochastically, and where the graph topologies undergo multiple simultaneous edge-weight updates. Its superiority in terms of the average number of processed nodes, scanned edges and the time per update operation, when compared with the existing algorithms, was experimentally established. The algorithm can be applicable in domains ranging from ground transportation to aerospace, from civilian applications to military, from spatial database applications to telecommunications networking.

Algorithms↗
PubMed1999

Molecular co-crystals of 2-aminothiazole derivatives.

A series of molecular adducts of 2-aminothiazole derivatives - 2-aminothiazole, 2-amino-2-thiazoline and 2-aminobenzothiazole with the carboxylic-acid-substituted heterocyclics indole-2-carboxylic acid, N-methylpyrrole-2-carboxylic acid and thiophene-2-carboxylic acid - have been prepared and characterized using X-ray powder diffraction and in five cases by single-crystal X-ray diffraction methods. These five compounds are the adducts of 2-amino-2-thiazolium with indole-2-carboxylate [(C(3)H(7)N(2)S)(+)(C(9)H(6)NO(2))(-)], and N-methylpyrrole-2-carboxylate [(C(3)H(7)N(2)S)(+)-(C(6)H(6)NO(2))(-)], 2-aminobenzothiazolium with indole-2-carboxylate [(C(7)H(7)N(2)S)(+)(C(9)H(6)NO(2))(-)], N-methylpyrrole-2-carboxylate [(C(7)H(7)N(2)S)(+)(C(6)H(6)NO(2))(-)] and thiophene-2-carboxylate [(C(7)H(7)N(2)S)(+)(C(5)H(3)O(2)S)(-)]. All complexes involve proton transfer, as indicated by IR spectroscopy, while the five crystal structures display similar hydrogen-bonding patterns with the dominant interaction being an R(2)(2)(8) graph set dimer association between carboxylate groups and the amine/heterocyclic nitrogen sites. Futhermore, in each case a subsiduary interaction between an amino proton and a carboxylate oxygen completes a linear hydrogen-bonded chain. In addition to this, the indole-2-carboxylate molecules in the adduct structure with 2-amino-2-thiazolium form associated dimers which add to the hydrogen-bonding network.

Journal Article↗
PubMed2005

The hydrogen-bonding network in (+)-N-tosyl-L-glutamic acid.

The asymmetric unit of the alpha polymorph of (+)-N-tosyl-L-glutamic acid, C12H15NO6S, contains two independent molecules which differ in conformation. The carboxylic acid groups form an infinite zigzag chain with characteristic R(2)(2)(8) rings running along the b axis. Intermolecular N-H...O and C-H...O contacts mediate the formation of a three-dimensional supramolecular structure described by R(4)(3)(22), R(6)(6)(44) and R(8)(8)(54) graph-set descriptors. Comparison of the extended structure with that of N-(benzenesulfonyl)glutamic acid shows that a subtle difference in the periphery of the molecule, i.e. the replacement of the toluyl group with a phenyl group, can be accompanied by dramatic changes in molecular assembly.

Crystallography, X-Ray↗
PubMed2004

Mining functional modules in genetic networks with decomposable graphical models.

In recent years, graphical models have become an increasingly important tool for the structural analysis of genome-wide expression profiles at the systems level. Here we present a new graphical modelling technique, which is based on decomposable graphical models, and apply it to a set of gene expression profiles from acute lymphoblastic leukemia (ALL). The new method explains probabilistic dependencies of expression levels in terms of the concerted action of underlying genetic functional modules, which are represented as so-called "cliques" in the graph. In addition, the method uses continuous-valued (instead of discretized) expression levels, and makes no particular assumption about their probability distribution. We show that the method successfully groups members of known functional modules to cliques. Our method allows the evaluation of the importance of genes for global cellular functions based on both link count and the clique membership count.

Gene Expression Profiling↗