PathSys: integrating molecular interaction graphs for systems biology
Directory of Open Access Journals (Sweden)
Raval Alpan
2006-02-01
Full Text Available Abstract Background The goal of information integration in systems biology is to combine information from a number of databases and data sets, which are obtained from both high and low throughput experiments, under one data management scheme such that the cumulative information provides greater biological insight than is possible with individual information sources considered separately. Results Here we present PathSys, a graph-based system for creating a combined database of networks of interaction for generating integrated view of biological mechanisms. We used PathSys to integrate over 14 curated and publicly contributed data sources for the budding yeast (S. cerevisiae and Gene Ontology. A number of exploratory questions were formulated as a combination of relational and graph-based queries to the integrated database. Thus, PathSys is a general-purpose, scalable, graph-data warehouse of biological information, complete with a graph manipulation and a query language, a storage mechanism and a generic data-importing mechanism through schema-mapping. Conclusion Results from several test studies demonstrate the effectiveness of the approach in retrieving biologically interesting relations between genes and proteins, the networks connecting them, and of the utility of PathSys as a scalable graph-based warehouse for interaction-network integration and a hypothesis generator system. The PathSys's client software, named BiologicalNetworks, developed for navigation and analyses of molecular networks, is available as a Java Web Start application at http://brak.sdsc.edu/pub/BiologicalNetworks.
Computing paths and cycles in biological interaction graphs
Directory of Open Access Journals (Sweden)
von Kamp Axel
2009-06-01
Full Text Available Abstract Background Interaction graphs (signed directed graphs provide an important qualitative modeling approach for Systems Biology. They enable the analysis of causal relationships in cellular networks and can even be useful for predicting qualitative aspects of systems dynamics. Fundamental issues in the analysis of interaction graphs are the enumeration of paths and cycles (feedback loops and the calculation of shortest positive/negative paths. These computational problems have been discussed only to a minor extent in the context of Systems Biology and in particular the shortest signed paths problem requires algorithmic developments. Results We first review algorithms for the enumeration of paths and cycles and show that these algorithms are superior to a recently proposed enumeration approach based on elementary-modes computation. The main part of this work deals with the computation of shortest positive/negative paths, an NP-complete problem for which only very few algorithms are described in the literature. We propose extensions and several new algorithm variants for computing either exact results or approximations. Benchmarks with various concrete biological networks show that exact results can sometimes be obtained in networks with several hundred nodes. A class of even larger graphs can still be treated exactly by a new algorithm combining exhaustive and simple search strategies. For graphs, where the computation of exact solutions becomes time-consuming or infeasible, we devised an approximative algorithm with polynomial complexity. Strikingly, in realistic networks (where a comparison with exact results was possible this algorithm delivered results that are very close or equal to the exact values. This phenomenon can probably be attributed to the particular topology of cellular signaling and regulatory networks which contain a relatively low number of negative feedback loops. Conclusion The calculation of shortest positive
Seiller, Thomas
2014-01-01
In two previous papers, we exposed a combinatorial approach to the program of Geometry of Interaction, a program initiated by Jean-Yves Girard. The strength of our approach lies in the fact that we interpret proofs by simpler structures - graphs - than Girard's constructions, while generalizing the latter since they can be recovered as special cases of our setting. This third paper extends this approach by considering a generalization of graphs named graphings, which is in some way a geometri...
DEFF Research Database (Denmark)
Seiller, Thomas
2016-01-01
Interaction graphs were introduced as a general, uniform, construction of dynamic models of linear logic, encompassing all Geometry of Interaction (GoI) constructions introduced so far. This series of work was inspired from Girard's hyperfinite GoI, and develops a quantitative approach that should...... be understood as a dynamic version of weighted relational models. Until now, the interaction graphs framework has been shown to deal with exponentials for the constrained system ELL (Elementary Linear Logic) while keeping its quantitative aspect. Adapting older constructions by Girard, one can clearly define...... "full" exponentials, but at the cost of these quantitative features. We show here that allowing interpretations of proofs to use continuous (yet finite in a measure-theoretic sense) sets of states, as opposed to earlier Interaction Graphs constructions were these sets of states were discrete (and finite...
Directory of Open Access Journals (Sweden)
Falcon Seth
2007-09-01
Full Text Available Abstract Graph theoretical concepts are useful for the description and analysis of interactions and relationships in biological systems. We give a brief introduction into some of the concepts and their areas of application in molecular biology. We discuss software that is available through the Bioconductor project and present a simple example application to the integration of a protein-protein interaction and a co-expression network.
RJSplot: Interactive Graphs with R.
Barrios, David; Prieto, Carlos
2018-03-01
Data visualization techniques provide new methods for the generation of interactive graphs. These graphs allow a better exploration and interpretation of data but their creation requires advanced knowledge of graphical libraries. Recent packages have enabled the integration of interactive graphs in R. However, R provides limited graphical packages that allow the generation of interactive graphs for computational biology applications. The present project has joined the analytical power of R with the interactive graphical features of JavaScript in a new R package (RJSplot). It enables the easy generation of interactive graphs in R, provides new visualization capabilities, and contributes to the advance of computational biology analytical methods. At present, 16 interactive graphics are available in RJSplot, such as the genome viewer, Manhattan plots, 3D plots, heatmaps, dendrograms, networks, and so on. The RJSplot package is freely available online at http://rjsplot.net. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Interaction Graphs: Exponentials
Seiller, Thomas
2013-01-01
This paper is the fourth of a series exposing a systematic combinatorial approach to Girard's Geometry of Interaction program. This program aims at obtaining particular realizability models for linear logic that accounts for the dynamics of cut-elimination. This fourth paper tackles the complex issue of defining exponential connectives in this framework. In order to succeed in this, we use the notion of graphings, a generalization of graphs which was defined in earlier work. We explain how we...
Local Interaction on Random Graphs
Directory of Open Access Journals (Sweden)
Hans Haller
2010-08-01
Full Text Available We analyze dynamic local interaction in population games where the local interaction structure (modeled as a graph can change over time: A stochastic process generates a random sequence of graphs. This contrasts with models where the initial interaction structure (represented by a deterministic graph or the realization of a random graph cannot change over time.
Neuro-symbolic representation learning on biological knowledge graphs
Alshahrani, Mona
2017-04-21
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge.We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of SemanticWeb based knowledge bases in biology to use in machine learning and data analytics.https://github.com/bio-ontology-research-group/walking-rdf-and-owl.robert.hoehndorf@kaust.edu.sa.Supplementary data are available at Bioinformatics online.
Neuro-symbolic representation learning on biological knowledge graphs.
Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert
2017-09-01
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Interactive Graph Layout of a Million Nodes
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Peng Mi
2016-12-01
Full Text Available Sensemaking of large graphs, specifically those with millions of nodes, is a crucial task in many fields. Automatic graph layout algorithms, augmented with real-time human-in-the-loop interaction, can potentially support sensemaking of large graphs. However, designing interactive algorithms to achieve this is challenging. In this paper, we tackle the scalability problem of interactive layout of large graphs, and contribute a new GPU-based force-directed layout algorithm that exploits graph topology. This algorithm can interactively layout graphs with millions of nodes, and support real-time interaction to explore alternative graph layouts. Users can directly manipulate the layout of vertices in a force-directed fashion. The complexity of traditional repulsive force computation is reduced by approximating calculations based on the hierarchical structure of multi-level clustered graphs. We evaluate the algorithm performance, and demonstrate human-in-the-loop layout in two sensemaking case studies. Moreover, we summarize lessons learned for designing interactive large graph layout algorithms on the GPU.
Crossed products for interactions and graph algebras
DEFF Research Database (Denmark)
Kwasniewski, Bartosz
2014-01-01
. These results cover the case of crossed products by endomorphisms with hereditary ranges and complemented kernels. As model examples of interactions not coming from endomorphisms we introduce and study in detail interactions arising from finite graphs. The interaction (V,H) associated to a graph E acts...... on the core F_E of the graph algebra C*(E). By describing a partial homeomorphism dual to (V,H) we find the fundamental structure theorems for C*(E), such as Cuntz–Krieger uniqueness theorem, as results concerning reversible noncommutative dynamics on F_E . We also provide a new approach to calculation of K...
Analysis and enumeration algorithms for biological graphs
Marino, Andrea
2015-01-01
In this work we plan to revise the main techniques for enumeration algorithms and to show four examples of enumeration algorithms that can be applied to efficiently deal with some biological problems modelled by using biological networks: enumerating central and peripheral nodes of a network, enumerating stories, enumerating paths or cycles, and enumerating bubbles. Notice that the corresponding computational problems we define are of more general interest and our results hold in the case of arbitrary graphs. Enumerating all the most and less central vertices in a network according to their eccentricity is an example of an enumeration problem whose solutions are polynomial and can be listed in polynomial time, very often in linear or almost linear time in practice. Enumerating stories, i.e. all maximal directed acyclic subgraphs of a graph G whose sources and targets belong to a predefined subset of the vertices, is on the other hand an example of an enumeration problem with an exponential number of solutions...
Interactive Web Graphs with Fewer Restrictions
Fiedler, James
2012-01-01
There is growing popularity for interactive, statistical web graphs and programs to generate them. However, it seems that these programs tend to be somewhat restricted in which web browsers and statistical software are supported. For example, the software might use SVG (e.g., Protovis, gridSVG) or HTML canvas, both of which exclude most versions of Internet Explorer, or the software might be made specifically for R (gridSVG, CRanvas), thus excluding users of other stats software. There are more general tools (d3, Rapha lJS) which are compatible with most browsers, but using one of these to make statistical graphs requires more coding than is probably desired, and requires learning a new tool. This talk will present a method for making interactive web graphs, which, by design, attempts to support as many browsers and as many statistical programs as possible, while also aiming to be relatively easy to use and relatively easy to extend.
Multigraph: Interactive Data Graphs on the Web
Phillips, M. B.
2010-12-01
Many aspects of geophysical science involve time dependent data that is often presented in the form of a graph. Considering that the web has become a primary means of communication, there are surprisingly few good tools and techniques available for presenting time-series data on the web. The most common solution is to use a desktop tool such as Excel or Matlab to create a graph which is saved as an image and then included in a web page like any other image. This technique is straightforward, but it limits the user to one particular view of the data, and disconnects the graph from the data in a way that makes updating a graph with new data an often cumbersome manual process. This situation is somewhat analogous to the state of mapping before the advent of GIS. Maps existed only in printed form, and creating a map was a laborious process. In the last several years, however, the world of mapping has experienced a revolution in the form of web-based and other interactive computer technologies, so that it is now commonplace for anyone to easily browse through gigabytes of geographic data. Multigraph seeks to bring a similar ease of access to time series data. Multigraph is a program for displaying interactive time-series data graphs in web pages that includes a simple way of configuring the appearance of the graph and the data to be included. It allows multiple data sources to be combined into a single graph, and allows the user to explore the data interactively. Multigraph lets users explore and visualize "data space" in the same way that interactive mapping applications such as Google Maps facilitate exploring and visualizing geography. Viewing a Multigraph graph is extremely simple and intuitive, and requires no instructions. Creating a new graph for inclusion in a web page involves writing a simple XML configuration file and requires no programming. Multigraph can read data in a variety of formats, and can display data from a web service, allowing users to "surf
VIGOR: Interactive Visual Exploration of Graph Query Results.
Pienta, Robert; Hohman, Fred; Endert, Alex; Tamersoy, Acar; Roundy, Kevin; Gates, Chris; Navathe, Shamkant; Chau, Duen Horng
2018-01-01
Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analysts make sense of underlying patterns within a group of subgraph results. Visualizing graph query results is challenging, requiring effective summarization of a large number of subgraphs, each having potentially shared node-values, rich node features, and flexible structure across queries. We present VIGOR, a novel interactive visual analytics system, for exploring and making sense of query results. VIGOR uses multiple coordinated views, leveraging different data representations and organizations to streamline analysts sensemaking process. VIGOR contributes: (1) an exemplar-based interaction technique, where an analyst starts with a specific result and relaxes constraints to find other similar results or starts with only the structure (i.e., without node value constraints), and adds constraints to narrow in on specific results; and (2) a novel feature-aware subgraph result summarization. Through a collaboration with Symantec, we demonstrate how VIGOR helps tackle real-world problems through the discovery of security blindspots in a cybersecurity dataset with over 11,000 incidents. We also evaluate VIGOR with a within-subjects study, demonstrating VIGOR's ease of use over a leading graph database management system, and its ability to help analysts understand their results at higher speed and make fewer errors.
GRAPES: a software for parallel searching on biological graphs targeting multi-core architectures.
Giugno, Rosalba; Bonnici, Vincenzo; Bombieri, Nicola; Pulvirenti, Alfredo; Ferro, Alfredo; Shasha, Dennis
2013-01-01
Biological applications, from genomics to ecology, deal with graphs that represents the structure of interactions. Analyzing such data requires searching for subgraphs in collections of graphs. This task is computationally expensive. Even though multicore architectures, from commodity computers to more advanced symmetric multiprocessing (SMP), offer scalable computing power, currently published software implementations for indexing and graph matching are fundamentally sequential. As a consequence, such software implementations (i) do not fully exploit available parallel computing power and (ii) they do not scale with respect to the size of graphs in the database. We present GRAPES, software for parallel searching on databases of large biological graphs. GRAPES implements a parallel version of well-established graph searching algorithms, and introduces new strategies which naturally lead to a faster parallel searching system especially for large graphs. GRAPES decomposes graphs into subcomponents that can be efficiently searched in parallel. We show the performance of GRAPES on representative biological datasets containing antiviral chemical compounds, DNA, RNA, proteins, protein contact maps and protein interactions networks.
International Nuclear Information System (INIS)
Samatova, N F; Schmidt, M C; Hendrix, W; Breimyer, P; Thomas, K; Park, B-H
2008-01-01
Data-driven construction of predictive models for biological systems faces challenges from data intensity, uncertainty, and computational complexity. Data-driven model inference is often considered a combinatorial graph problem where an enumeration of all feasible models is sought. The data-intensive and the NP-hard nature of such problems, however, challenges existing methods to meet the required scale of data size and uncertainty, even on modern supercomputers. Maximal clique enumeration (MCE) in a graph derived from such biological data is often a rate-limiting step in detecting protein complexes in protein interaction data, finding clusters of co-expressed genes in microarray data, or identifying clusters of orthologous genes in protein sequence data. We report two key advances that address this challenge. We designed and implemented the first (to the best of our knowledge) parallel MCE algorithm that scales linearly on thousands of processors running MCE on real-world biological networks with thousands and hundreds of thousands of vertices. In addition, we proposed and developed the Graph Perturbation Theory (GPT) that establishes a foundation for efficiently solving the MCE problem in perturbed graphs, which model the uncertainty in the data. GPT formulates necessary and sufficient conditions for detecting the differences between the sets of maximal cliques in the original and perturbed graphs and reduces the enumeration time by more than 80% compared to complete recomputation
Directory of Open Access Journals (Sweden)
Luan Yihui
2009-09-01
Full Text Available Abstract Background Many aspects of biological functions can be modeled by biological networks, such as protein interaction networks, metabolic networks, and gene coexpression networks. Studying the statistical properties of these networks in turn allows us to infer biological function. Complex statistical network models can potentially more accurately describe the networks, but it is not clear whether such complex models are better suited to find biologically meaningful subnetworks. Results Recent studies have shown that the degree distribution of the nodes is not an adequate statistic in many molecular networks. We sought to extend this statistic with 2nd and 3rd order degree correlations and developed a pseudo-likelihood approach to estimate the parameters. The approach was used to analyze the MIPS and BIOGRID yeast protein interaction networks, and two yeast coexpression networks. We showed that 2nd order degree correlation information gave better predictions of gene interactions in both protein interaction and gene coexpression networks. However, in the biologically important task of predicting functionally homogeneous modules, degree correlation information performs marginally better in the case of the MIPS and BIOGRID protein interaction networks, but worse in the case of gene coexpression networks. Conclusion Our use of dK models showed that incorporation of degree correlations could increase predictive power in some contexts, albeit sometimes marginally, but, in all contexts, the use of third-order degree correlations decreased accuracy. However, it is possible that other parameter estimation methods, such as maximum likelihood, will show the usefulness of incorporating 2nd and 3rd degree correlations in predicting functionally homogeneous modules.
Network graph analysis of gene-gene interactions in genome-wide association study data.
Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung
2012-12-01
Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Generalized lattice graphs for 2D-visualization of biological information.
González-Díaz, H; Pérez-Montoto, L G; Duardo-Sanchez, A; Paniagua, E; Vázquez-Prieto, S; Vilas, R; Dea-Ayuela, M A; Bolas-Fernández, F; Munteanu, C R; Dorado, J; Costas, J; Ubeira, F M
2009-11-07
Several graph representations have been introduced for different data in theoretical biology. For instance, complex networks based on Graph theory are used to represent the structure and/or dynamics of different large biological systems such as protein-protein interaction networks. In addition, Randic, Liao, Nandy, Basak, and many others developed some special types of graph-based representations. This special type of graph includes geometrical constrains to node positioning in space and adopts final geometrical shapes that resemble lattice-like patterns. Lattice networks have been used to visually depict DNA and protein sequences but they are very flexible. However, despite the proved efficacy of new lattice-like graph/networks to represent diverse systems, most works focus on only one specific type of biological data. This work proposes a generalized type of lattice and illustrates how to use it in order to represent and compare biological data from different sources. We exemplify the following cases: protein sequence; mass spectra (MS) of protein peptide mass fingerprints (PMF); molecular dynamic trajectory (MDTs) from structural studies; mRNA microarray data; single nucleotide polymorphisms (SNPs); 1D or 2D-Electrophoresis study of protein polymorphisms and protein-research patent and/or copyright information. We used data available from public sources for some examples but for other, we used experimental results reported herein for the first time. This work may break new ground for the application of Graph theory in theoretical biology and other areas of biomedical sciences.
Ringo: Interactive Graph Analytics on Big-Memory Machines
Perez, Yonathan; Sosič, Rok; Banerjee, Arijit; Puttagunta, Rohan; Raison, Martin; Shah, Pararth; Leskovec, Jure
2016-01-01
We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges between the objects denoting interactions (friendships, physical interactions, links). Mining graphs provides valuable insights about individual objects as well as the relationships among them. In building Ringo, we take advantage of the fact that machines with large memory and many cores are widely available and also relatively affordable. This allows us to build an easy-to-use interactive high-performance graph analytics system. Graphs also need to be built from input data, which often resides in the form of relational tables. Thus, Ringo provides rich functionality for manipulating raw input data tables into various kinds of graphs. Furthermore, Ringo also provides over 200 graph analytics functions that can then be applied to constructed graphs. We show that a single big-memory machine provides a very attractive platform for performing analytics on all but the largest graphs as it offers excellent performance and ease of use as compared to alternative approaches. With Ringo, we also demonstrate how to integrate graph analytics with an iterative process of trial-and-error data exploration and rapid experimentation, common in data mining workloads. PMID:27081215
GraphAlignment: Bayesian pairwise alignment of biological networks
Czech Academy of Sciences Publication Activity Database
Kolář, Michal; Meier, J.; Mustonen, V.; Lässig, M.; Berg, J.
2012-01-01
Roč. 6, November 21 (2012) ISSN 1752-0509 Grant - others:Deutsche Forschungsgemeinschaft(DE) SFB 680; Deutsche Forschungsgemeinschaft(DE) SFB-TR12; Deutsche Forschungsgemeinschaft(DE) BE 2478/2-1 Institutional research plan: CEZ:AV0Z50520514 Keywords : Graph alignment * Biological networks * Parameter estimation * Bioconductor Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.982, year: 2012
GraphAlignment: Bayesian pairwise alignment of biological networks
Directory of Open Access Journals (Sweden)
Kolář Michal
2012-11-01
Full Text Available Abstract Background With increased experimental availability and accuracy of bio-molecular networks, tools for their comparative and evolutionary analysis are needed. A key component for such studies is the alignment of networks. Results We introduce the Bioconductor package GraphAlignment for pairwise alignment of bio-molecular networks. The alignment incorporates information both from network vertices and network edges and is based on an explicit evolutionary model, allowing inference of all scoring parameters directly from empirical data. We compare the performance of our algorithm to an alternative algorithm, Græmlin 2.0. On simulated data, GraphAlignment outperforms Græmlin 2.0 in several benchmarks except for computational complexity. When there is little or no noise in the data, GraphAlignment is slower than Græmlin 2.0. It is faster than Græmlin 2.0 when processing noisy data containing spurious vertex associations. Its typical case complexity grows approximately as O(N2.6. On empirical bacterial protein-protein interaction networks (PIN and gene co-expression networks, GraphAlignment outperforms Græmlin 2.0 with respect to coverage and specificity, albeit by a small margin. On large eukaryotic PIN, Græmlin 2.0 outperforms GraphAlignment. Conclusions The GraphAlignment algorithm is robust to spurious vertex associations, correctly resolves paralogs, and shows very good performance in identification of homologous vertices defined by high vertex and/or interaction similarity. The simplicity and generality of GraphAlignment edge scoring makes the algorithm an appropriate choice for global alignment of networks.
Use of Graph Database for the Integration of Heterogeneous Biological Data.
Yoon, Byoung-Ha; Kim, Seon-Kyu; Kim, Seon-Young
2017-03-01
Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.
Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data
Directory of Open Access Journals (Sweden)
Sungyoung Lee
2012-12-01
Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Bodner, Todd E.
2016-01-01
This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…
Exploring community structure in biological networks with random graphs
2014-01-01
Background Community structure is ubiquitous in biological networks. There has been an increased interest in unraveling the community structure of biological systems as it may provide important insights into a system’s functional components and the impact of local structures on dynamics at a global scale. Choosing an appropriate community detection algorithm to identify the community structure in an empirical network can be difficult, however, as the many algorithms available are based on a variety of cost functions and are difficult to validate. Even when community structure is identified in an empirical system, disentangling the effect of community structure from other network properties such as clustering coefficient and assortativity can be a challenge. Results Here, we develop a generative model to produce undirected, simple, connected graphs with a specified degrees and pattern of communities, while maintaining a graph structure that is as random as possible. Additionally, we demonstrate two important applications of our model: (a) to generate networks that can be used to benchmark existing and new algorithms for detecting communities in biological networks; and (b) to generate null models to serve as random controls when investigating the impact of complex network features beyond the byproduct of degree and modularity in empirical biological networks. Conclusion Our model allows for the systematic study of the presence of community structure and its impact on network function and dynamics. This process is a crucial step in unraveling the functional consequences of the structural properties of biological systems and uncovering the mechanisms that drive these systems. PMID:24965130
From protein interactions to functional annotation: graph alignment in Herpes
Czech Academy of Sciences Publication Activity Database
Kolář, Michal; Lassig, M.; Berg, J.
2008-01-01
Roč. 2, č. 90 (2008), e-e ISSN 1752-0509 Institutional research plan: CEZ:AV0Z50520514 Keywords : graph alignment * functional annotation * protein orthology Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.706, year: 2008
Graph Transformation with Dependencies for the Specification of Interactive Systems
Corradini, Andrea; Foss, Luciana; Ribeiro, Leila
We propose a notion of Graph Transformation Systems ( gts) with dependency relation, more expressive than a previously proposed one, and suitable for the specification of interactions. We show how a specification using gts with dependencies can be implemented, at a lower level of abstraction, by a transactional gts, that is, a gts equipped with the notion of observable (stable) items in which computations that correspond to “complete” interactions are characterized as transactions.
Directory of Open Access Journals (Sweden)
Moschopoulos Charalampos
2011-06-01
Full Text Available Abstract Background Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied. Results We adopt a two step procedure. During the first step, by applying both novel and well established protein-protein interaction (PPI weighting methods, weights are introduced to the original interactome graph based on the confidence level that a given interaction is a true-positive one. The second step applies clustering using established algorithms in the field of graph theory, as well as two variations of Spectral clustering. The clustered interactome networks are also cross-validated against the confirmed protein complexes present in the MIPS database. Conclusions The results of our experimental work demonstrate that interactome graph weighting methods clearly improve the clustering results of several clustering algorithms. Moreover, our proposed weighting scheme outperforms other approaches of PPI graph weighting.
Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization.
Ezzat, Ali; Zhao, Peilin; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong
2017-01-01
Experimental determination of drug-target interactions is expensive and time-consuming. Therefore, there is a continuous demand for more accurate predictions of interactions using computational techniques. Algorithms have been devised to infer novel interactions on a global scale where the input to these algorithms is a drug-target network (i.e., a bipartite graph where edges connect pairs of drugs and targets that are known to interact). However, these algorithms had difficulty predicting interactions involving new drugs or targets for which there are no known interactions (i.e., "orphan" nodes in the network). Since data usually lie on or near to low-dimensional non-linear manifolds, we propose two matrix factorization methods that use graph regularization in order to learn such manifolds. In addition, considering that many of the non-occurring edges in the network are actually unknown or missing cases, we developed a preprocessing step to enhance predictions in the "new drug" and "new target" cases by adding edges with intermediate interaction likelihood scores. In our cross validation experiments, our methods achieved better results than three other state-of-the-art methods in most cases. Finally, we simulated some "new drug" and "new target" cases and found that GRMF predicted the left-out interactions reasonably well.
Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution
Takahashi, Daniel Yasumasa; Sato, João Ricardo; Ferreira, Carlos Eduardo; Fujita, André
2012-01-01
The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a “fingerprint”. Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the “uncertainty” of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed. PMID:23284629
Ontology- and graph-based similarity assessment in biological networks.
Wang, Haiying; Zheng, Huiru; Azuaje, Francisco
2010-10-15
A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different 'guilt-by-association' analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a 'semantic similarity' space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks. http://rosalind.infj.ulst.ac.uk/SimTrek.html francisco.azuaje@crp-sante.lu Supplementary data are available at Bioinformatics online.
Strategy and pattern recognition in expert\\ud comprehension of 2 × 2 interaction graphs
Peebles, David
2013-01-01
I present a model of expert comprehension performance for 2 × 2 "interaction" graphs typically used to present data from two-way factorial research designs. Developed using the ACT-R cognitive architecture, the model simulates the cognitive and perceptual operations involved in interpreting interaction graphs and provides a detailed characterisation of the information\\ud extracted from the diagram, the prior knowledge required to interpret interaction graphs, and the knowledge generated durin...
Graphs of groups on surfaces interactions and models
White, AT
2001-01-01
The book, suitable as both an introductory reference and as a text book in the rapidly growing field of topological graph theory, models both maps (as in map-coloring problems) and groups by means of graph imbeddings on sufaces. Automorphism groups of both graphs and maps are studied. In addition connections are made to other areas of mathematics, such as hypergraphs, block designs, finite geometries, and finite fields. There are chapters on the emerging subfields of enumerative topological graph theory and random topological graph theory, as well as a chapter on the composition of English
PERSEUS-HUB: Interactive and Collective Exploration of Large-Scale Graphs
Directory of Open Access Journals (Sweden)
Di Jin
2017-07-01
Full Text Available Graphs emerge naturally in many domains, such as social science, neuroscience, transportation engineering, and more. In many cases, such graphs have millions or billions of nodes and edges, and their sizes increase daily at a fast pace. How can researchers from various domains explore large graphs interactively and efficiently to find out what is ‘important’? How can multiple researchers explore a new graph dataset collectively and “help” each other with their findings? In this article, we present Perseus-Hub, a large-scale graph mining tool that computes a set of graph properties in a distributed manner, performs ensemble, multi-view anomaly detection to highlight regions that are worth investigating, and provides users with uncluttered visualization and easy interaction with complex graph statistics. Perseus-Hub uses a Spark cluster to calculate various statistics of large-scale graphs efficiently, and aggregates the results in a summary on the master node to support interactive user exploration. In Perseus-Hub, the visualized distributions of graph statistics provide preliminary analysis to understand a graph. To perform a deeper analysis, users with little prior knowledge can leverage patterns (e.g., spikes in the power-law degree distribution marked by other users or experts. Moreover, Perseus-Hub guides users to regions of interest by highlighting anomalous nodes and helps users establish a more comprehensive understanding about the graph at hand. We demonstrate our system through the case study on real, large-scale networks.
Handbook of graph grammars and computing by graph transformation
Engels, G; Kreowski, H J; Rozenberg, G
1999-01-01
Graph grammars originated in the late 60s, motivated by considerations about pattern recognition and compiler construction. Since then, the list of areas which have interacted with the development of graph grammars has grown quite impressively. Besides the aforementioned areas, it includes software specification and development, VLSI layout schemes, database design, modeling of concurrent systems, massively parallel computer architectures, logic programming, computer animation, developmental biology, music composition, visual languages, and many others.The area of graph grammars and graph tran
Online interactive tutorials for creating graphs with excel 2007 or 2010.
Vanselow, Nicholas R; Bourret, Jason C
2012-01-01
Graphic display of clinical data is a useful tool for the behavior-analytic clinician. However, graphs can sometimes be difficult to create. We describe how to access and use an online interactive tutorial that teaches the user to create a variety of graphs often used by behavior analysts. Three tutorials are provided that cover the basics of Microsoft Excel 2007 or 2010, creating graphs for clinical purposes, and creating graphs for research purposes. The uses for this interactive tutorial and other similar programs are discussed.
Interactive exploration of large-scale time-varying data using dynamic tracking graphs
Widanagamaachchi, W.
2012-10-01
Exploring and analyzing the temporal evolution of features in large-scale time-varying datasets is a common problem in many areas of science and engineering. One natural representation of such data is tracking graphs, i.e., constrained graph layouts that use one spatial dimension to indicate time and show the "tracks" of each feature as it evolves, merges or disappears. However, for practical data sets creating the corresponding optimal graph layouts that minimize the number of intersections can take hours to compute with existing techniques. Furthermore, the resulting graphs are often unmanageably large and complex even with an ideal layout. Finally, due to the cost of the layout, changing the feature definition, e.g. by changing an iso-value, or analyzing properly adjusted sub-graphs is infeasible. To address these challenges, this paper presents a new framework that couples hierarchical feature definitions with progressive graph layout algorithms to provide an interactive exploration of dynamically constructed tracking graphs. Our system enables users to change feature definitions on-the-fly and filter features using arbitrary attributes while providing an interactive view of the resulting tracking graphs. Furthermore, the graph display is integrated into a linked view system that provides a traditional 3D view of the current set of features and allows a cross-linked selection to enable a fully flexible spatio-temporal exploration of data. We demonstrate the utility of our approach with several large-scale scientific simulations from combustion science. © 2012 IEEE.
Czech Academy of Sciences Publication Activity Database
Barseghyan, Diana; Khrabustovskyi, A.
2015-01-01
Roč. 48, č. 25 (2015), s. 255201 ISSN 1751-8113 Institutional support: RVO:61389005 Keywords : periodic quantum graphs * delta'-type interactions * spectral gaps Subject RIV: BE - Theoretical Physics Impact factor: 1.933, year: 2015
Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs
Directory of Open Access Journals (Sweden)
Theis Fabian J
2010-10-01
Full Text Available Abstract Background Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general but common situation of k-partite graphs. These graphs contain k different node types and links are only allowed between nodes of different types. In order to reveal their structural organization and describe the contained information in a more coarse-grained fashion, we ask how to detect clusters within each node type. Results Since entities in biological networks regularly have more than one function and hence participate in more than one cluster, we developed a k-partite graph partitioning algorithm that allows for overlapping (fuzzy clusters. It determines for each node a degree of membership to each cluster. Moreover, the algorithm estimates a weighted k-partite graph that connects the extracted clusters. Our method is fast and efficient, mimicking the multiplicative update rules commonly employed in algorithms for non-negative matrix factorization. It facilitates the decomposition of networks on a chosen scale and therefore allows for analysis and interpretation of structures on various resolution levels. Applying our algorithm to a tripartite disease-gene-protein complex network, we were able to structure this graph on a large scale into clusters that are functionally correlated and biologically meaningful. Locally, smaller clusters enabled reclassification or annotation of the clusters' elements. We exemplified this for the transcription factor MECP2. Conclusions In order to cope with the overwhelming amount of information available from biomedical literature, we need to tackle the challenge of finding structures in large networks with nodes of multiple types. To this end, we presented a novel fuzzy k-partite graph partitioning
VANLO - Interactive visual exploration of aligned biological networks
Directory of Open Access Journals (Sweden)
Linsen Lars
2009-10-01
Full Text Available Abstract Background Protein-protein interaction (PPI is fundamental to many biological processes. In the course of evolution, biological networks such as protein-protein interaction networks have developed. Biological networks of different species can be aligned by finding instances (e.g. proteins with the same common ancestor in the evolutionary process, so-called orthologs. For a better understanding of the evolution of biological networks, such aligned networks have to be explored. Visualization can play a key role in making the various relationships transparent. Results We present a novel visualization system for aligned biological networks in 3D space that naturally embeds existing 2D layouts. In addition to displaying the intra-network connectivities, we also provide insight into how the individual networks relate to each other by placing aligned entities on top of each other in separate layers. We optimize the layout of the entire alignment graph in a global fashion that takes into account inter- as well as intra-network relationships. The layout algorithm includes a step of merging aligned networks into one graph, laying out the graph with respect to application-specific requirements, splitting the merged graph again into individual networks, and displaying the network alignment in layers. In addition to representing the data in a static way, we also provide different interaction techniques to explore the data with respect to application-specific tasks. Conclusion Our system provides an intuitive global understanding of aligned PPI networks and it allows the investigation of key biological questions. We evaluate our system by applying it to real-world examples documenting how our system can be used to investigate the data with respect to these key questions. Our tool VANLO (Visualization of Aligned Networks with Layout Optimization can be accessed at http://www.math-inf.uni-greifswald.de/VANLO.
Analysis of protein-protein interaction networks by means of annotated graph mining algorithms
Rahmani, Hossein
2012-01-01
This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large
A critical analysis of computational protein design with sparse residue interaction graphs.
Jain, Swati; Jou, Jonathan D; Georgiev, Ivelin S; Donald, Bruce R
2017-03-01
Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their
An Interactive Teaching System for Bond Graph Modeling and Simulation in Bioengineering
Roman, Monica; Popescu, Dorin; Selisteanu, Dan
2013-01-01
The objective of the present work was to implement a teaching system useful in modeling and simulation of biotechnological processes. The interactive system is based on applications developed using 20-sim modeling and simulation software environment. A procedure for the simulation of bioprocesses modeled by bond graphs is proposed and simulators…
Infinite graphs in systematic biology, with an application to the species problem.
Alexander, Samuel A
2013-06-01
We argue that C. Darwin and more recently W. Hennig worked at times under the simplifying assumption of an eternal biosphere. So motivated, we explicitly consider the consequences which follow mathematically from this assumption, and the infinite graphs it leads to. This assumption admits certain clusters of organisms which have some ideal theoretical properties of species, shining some light onto the species problem. We prove a dualization of a law of T. A. Knight and C. Darwin, and sketch a decomposition result involving the internodons of D. Kornet, J. Metz and H. Schellinx. A further goal of this paper is to respond to B. Sturmfels' question, "Can biology lead to new theorems?"
Quick Mining of Isomorphic Exact Large Patterns from Large Graphs
Almasri, Islam
2014-12-01
The applications of the sub graph isomorphism search are growing with the growing number of areas that model their systems using graphs or networks. Specifically, many biological systems, such as protein interaction networks, molecular structures and protein contact maps, are modeled as graphs. The sub graph isomorphism search is concerned with finding all sub graphs that are isomorphic to a relevant query graph, the existence of such sub graphs can reflect on the characteristics of the modeled system. The most computationally expensive step in the search for isomorphic sub graphs is the backtracking algorithm that traverses the nodes of the target graph. In this paper, we propose a pruning approach that is inspired by the minimum remaining value heuristic that achieves greater scalability over large query and target graphs. Our testing on various biological networks shows that performance enhancement of our approach over existing state-of-the-art approaches varies between 6x and 53x. © 2014 IEEE.
Revealing Long-Range Interconnected Hubs in Human Chromatin Interaction Data Using Graph Theory
Boulos, R. E.; Arneodo, A.; Jensen, P.; Audit, B.
2013-09-01
We use graph theory to analyze chromatin interaction (Hi-C) data in the human genome. We show that a key functional feature of the genome—“master” replication origins—corresponds to DNA loci of maximal network centrality. These loci form a set of interconnected hubs both within chromosomes and between different chromosomes. Our results open the way to a fruitful use of graph theory concepts to decipher DNA structural organization in relation to genome functions such as replication and transcription. This quantitative information should prove useful to discriminate between possible polymer models of nuclear organization.
SNAPP: GRAPHING STUDENT INTERACTIONS IN A LEARNING MANAGEMENT SYSTEM
Directory of Open Access Journals (Sweden)
Kevin YEE,
2011-01-01
Full Text Available One of the more vexing problems in teaching fully-online classes concerns the development of community. As Rovai (2001 identified, online courses must combat feelings of isolation and impart a sense of personal and individual attention. To create a sense of belonging and togetherness, instructors typically need to surmount numerous technological hurdles inherent in online delivery, not least of which is the inescapable conclusion that the one factor most basic to the formation of community-face to face interaction-is by definition absent in an online class. Many new tech-based teaching tools have been developed in an attempt to ameliorate the digital alienation and promote interaction, such as discussion boards, synchronous chat rooms, and emerging media like wikis, blogs and podcasts, as well as virtual worlds, such as Second Life. As the frequency of interaction grows, so does the sense of belonging to a learning community (Dawson, 2008.
Zhang, Guo-Qiang; Luo, Lingyun; Ogbuji, Chime; Joslyn, Cliff; Mejino, Jose; Sahoo, Satya S
2012-01-01
The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions for detecting logical inconsistencies as well as other anomalies represented by the motifs. MOCH represents patterns of multi-type interaction as small labeled (with multiple types of edges) sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology, we performed exhaustive analyses of a variety of labeled sub-graph motifs. The quality assurance feature of MOCH comes from the distinct use of a subset of the edges of the graph motifs as constraints for disjointness, whereby bringing in rule-based flavor to the approach as well. With possible disjointness implied by antonyms, we performed manual inspection of the resulting FMA fragments and tracked down sources of abnormal inferred conclusions (logical inconsistencies), which are amendable for programmatic revision of the FMA. Our results demonstrate that MOCH provides a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation.
Referring Expression Generation in Interaction: A Graph-based perspective
Krahmer, E.J.; Goudbeek, M.B.; Theune, M.; Stent, Amanda; Bangalore, Srinivas
2014-01-01
An informative and comprehensive overview of the state-of-the-art in natural language generation (NLG) for interactive systems, this guide serves to introduce graduate students and new researchers to the field of natural language processing and artificial intelligence, while inspiring them with
Melas, Ioannis N; Samaga, Regina; Alexopoulos, Leonidas G; Klamt, Steffen
2013-01-01
Cross-referencing experimental data with our current knowledge of signaling network topologies is one central goal of mathematical modeling of cellular signal transduction networks. We present a new methodology for data-driven interrogation and training of signaling networks. While most published methods for signaling network inference operate on Bayesian, Boolean, or ODE models, our approach uses integer linear programming (ILP) on interaction graphs to encode constraints on the qualitative behavior of the nodes. These constraints are posed by the network topology and their formulation as ILP allows us to predict the possible qualitative changes (up, down, no effect) of the activation levels of the nodes for a given stimulus. We provide four basic operations to detect and remove inconsistencies between measurements and predicted behavior: (i) find a topology-consistent explanation for responses of signaling nodes measured in a stimulus-response experiment (if none exists, find the closest explanation); (ii) determine a minimal set of nodes that need to be corrected to make an inconsistent scenario consistent; (iii) determine the optimal subgraph of the given network topology which can best reflect measurements from a set of experimental scenarios; (iv) find possibly missing edges that would improve the consistency of the graph with respect to a set of experimental scenarios the most. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGFR/ErbB signaling against a library of high-throughput phosphoproteomic data measured in primary hepatocytes. Our methods detect interactions that are likely to be inactive in hepatocytes and provide suggestions for new interactions that, if included, would significantly improve the goodness of fit. Our framework is highly flexible and the underlying model requires only easily accessible biological knowledge. All related algorithms were implemented in a freely
Integrative network biology: graph prototyping for co-expression cancer networks.
Directory of Open Access Journals (Sweden)
Karl G Kugler
Full Text Available Network-based analysis has been proven useful in biologically-oriented areas, e.g., to explore the dynamics and complexity of biological networks. Investigating a set of networks allows deriving general knowledge about the underlying topological and functional properties. The integrative analysis of networks typically combines networks from different studies that investigate the same or similar research questions. In order to perform an integrative analysis it is often necessary to compare the properties of matching edges across the data set. This identification of common edges is often burdensome and computational intensive. Here, we present an approach that is different from inferring a new network based on common features. Instead, we select one network as a graph prototype, which then represents a set of comparable network objects, as it has the least average distance to all other networks in the same set. We demonstrate the usefulness of the graph prototyping approach on a set of prostate cancer networks and a set of corresponding benign networks. We further show that the distances within the cancer group and the benign group are statistically different depending on the utilized distance measure.
Tailored Random Graph Ensembles
International Nuclear Information System (INIS)
Roberts, E S; Annibale, A; Coolen, A C C
2013-01-01
Tailored graph ensembles are a developing bridge between biological networks and statistical mechanics. The aim is to use this concept to generate a suite of rigorous tools that can be used to quantify and compare the topology of cellular signalling networks, such as protein-protein interaction networks and gene regulation networks. We calculate exact and explicit formulae for the leading orders in the system size of the Shannon entropies of random graph ensembles constrained with degree distribution and degree-degree correlation. We also construct an ergodic detailed balance Markov chain with non-trivial acceptance probabilities which converges to a strictly uniform measure and is based on edge swaps that conserve all degrees. The acceptance probabilities can be generalized to define Markov chains that target any alternative desired measure on the space of directed or undirected graphs, in order to generate graphs with more sophisticated topological features.
A componential model of human interaction with graphs: 1. Linear regression modeling
Gillan, Douglas J.; Lewis, Robert
1994-01-01
Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.
International Nuclear Information System (INIS)
Delmotte, A; Barahona, M; Tate, E W; Yaliraki, S N
2011-01-01
Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding
2014-01-01
Background Integrating and analyzing heterogeneous genome-scale data is a huge algorithmic challenge for modern systems biology. Bipartite graphs can be useful for representing relationships across pairs of disparate data types, with the interpretation of these relationships accomplished through an enumeration of maximal bicliques. Most previously-known techniques are generally ill-suited to this foundational task, because they are relatively inefficient and without effective scaling. In this paper, a powerful new algorithm is described that produces all maximal bicliques in a bipartite graph. Unlike most previous approaches, the new method neither places undue restrictions on its input nor inflates the problem size. Efficiency is achieved through an innovative exploitation of bipartite graph structure, and through computational reductions that rapidly eliminate non-maximal candidates from the search space. An iterative selection of vertices for consideration based on non-decreasing common neighborhood sizes boosts efficiency and leads to more balanced recursion trees. Results The new technique is implemented and compared to previously published approaches from graph theory and data mining. Formal time and space bounds are derived. Experiments are performed on both random graphs and graphs constructed from functional genomics data. It is shown that the new method substantially outperforms the best previous alternatives. Conclusions The new method is streamlined, efficient, and particularly well-suited to the study of huge and diverse biological data. A robust implementation has been incorporated into GeneWeaver, an online tool for integrating and analyzing functional genomics experiments, available at http://geneweaver.org. The enormous increase in scalability it provides empowers users to study complex and previously unassailable gene-set associations between genes and their biological functions in a hierarchical fashion and on a genome-wide scale. This practical
A Study of Layout, Rendering, and Interaction Methods for Immersive Graph Visualization.
Kwon, Oh-Hyun; Muelder, Chris; Lee, Kyungwon; Ma, Kwan-Liu
2016-07-01
Information visualization has traditionally limited itself to 2D representations, primarily due to the prevalence of 2D displays and report formats. However, there has been a recent surge in popularity of consumer grade 3D displays and immersive head-mounted displays (HMDs). The ubiquity of such displays enables the possibility of immersive, stereoscopic visualization environments. While techniques that utilize such immersive environments have been explored extensively for spatial and scientific visualizations, contrastingly very little has been explored for information visualization. In this paper, we present our considerations of layout, rendering, and interaction methods for visualizing graphs in an immersive environment. We conducted a user study to evaluate our techniques compared to traditional 2D graph visualization. The results show that participants answered significantly faster with a fewer number of interactions using our techniques, especially for more difficult tasks. While the overall correctness rates are not significantly different, we found that participants gave significantly more correct answers using our techniques for larger graphs.
Directory of Open Access Journals (Sweden)
Hend Alrasheed
2017-03-01
Full Text Available Hyperbolicity is a global property of graphs that measures how close their structures are to trees in terms of their distances. It embeds multiple properties that facilitate solving several problems that found to be hard in the general graph form. In this paper, we investigate the hyperbolicity of graphs not only by considering Gromov’s notion of δ-hyperbolicity but also by analyzing its relationship to other graph’s parameters. This new perspective allows us to classify graphs with respect to their hyperbolicity and to show that many biological networks are hyperbolic. Then we introduce the eccentricity-based bending property which we exploit to identify the core vertices of a graph by proposing two models: the maximum-peak model and the minimum cover set model. In this extended version of the paper, we include some new theorems, as well as proofs of the theorems proposed in the conference paper. Also, we present the algorithms we used for each of the proposed core identification models, and we provide more analysis, explanations, and examples.
Radiation interactions with biological systems.
Islam, Muhammad Torequl
2017-05-01
The use of radiation, especially ionizing radiation (IR), is currently attracting great attention in the field of medical sciences. However, it should be mentioned that IR has both beneficial and harmful effects in biological systems. This review aims to focus on IR-mediated physiological events in a mechanistic way. Evidence from the databases, mainly from PUBMED and SCIENCE DIRECT were considered. IR directly and/or with their lyses products (indirect) causes oxidative stresses to biological systems. These activities may be localized and systematic. Otherwise, IR-induced non-/multi-targeted effects are also evident. IR in diagnosis and cancer radiotherapy is well-known. Reactive species produced by IR are not only beneficial, but also can exert harmful effects in a biological system such as aging, genetic instability and mutagenicity, membrane lysis and cell death, alteration of enzymatic activity and metabolic events, mitochondrial dysfunction, and even cancer. Additionally, DNA adducts formation, after IR-induced DNA breakage, is a cause of blockage of DNA repair capability with an increase in cellular radiosensitivity. These may allow cellular ruin even at low IR levels. Dependent on the dose, duration of action and quality, IR plays diverse roles in biological systems.
Modeling nonspecific interactions at biological interfaces
White, Andrew D.
Difficulties in applied biomaterials often arise from the complexities of interactions in biological environments. These interactions can be broadly broken into two categories: those which are important to function (strong binding to a single target) and those which are detrimental to function (weak binding to many targets). These will be referred to as specific and nonspecific interactions, respectively. Nonspecific interactions have been central to failures of biomaterials, sensors, and surface coatings in harsh biological environments. There is little modeling work on studying nonspecific interactions. Modeling all possible nonspecific interactions within a biological system is difficult, yet there are ways to both indirectly model nonspecific interactions and directly model many interactions using machine-learning. This research utilizes bioinformatics, phenomenological modeling, molecular simulations, experiments, and stochastic modeling to study nonspecific interactions. These techniques are used to study the hydration molecules which resist nonspecific interactions, the formation of salt bridges, the chemistry of protein surfaces, nonspecific stabilization of proteins in molecular chaperones, and analysis of high-throughput screening experiments. The common aspect for these systems is that nonspecific interactions are more important than specific interactions. Studying these disparate systems has created a set of principles for resisting nonspecific interactions which have been experimentally demonstrated with the creation and testing of novel materials which resist nonspecific interactions.
Biological interactions in the Sea
Indian Academy of Sciences (India)
ddattesh
Determinants of population abundance. Microhydrodynamic, behavioral & substrate availability process. Larval pool. Physical & larval transport processes. Local biotic interactions. & disturbance. Space. Scale of processes influencing the population. Population abundance. Time. Relative importance of density dependent ...
Critical controllability analysis of directed biological networks using efficient graph reduction.
Ishitsuka, Masayuki; Akutsu, Tatsuya; Nacher, Jose C
2017-10-30
Network science has recently integrated key concepts from control theory and has applied them to the analysis of the controllability of complex networks. One of the proposed frameworks uses the Minimum Dominating Set (MDS) approach, which has been successfully applied to the identification of cancer-related proteins and in analyses of large-scale undirected networks, such as proteome-wide protein interaction networks. However, many real systems are better represented by directed networks. Therefore, fast algorithms are required for the application of MDS to directed networks. Here, we propose an algorithm that utilises efficient graph reduction to identify critical control nodes in large-scale directed complex networks. The algorithm is 176-fold faster than existing methods and increases the computable network size to 65,000 nodes. We then applied the developed algorithm to metabolic pathways consisting of 70 plant species encompassing major plant lineages ranging from algae to angiosperms and to signalling pathways from C. elegans, D. melanogaster and H. sapiens. The analysis not only identified functional pathways enriched with critical control molecules but also showed that most control categories are largely conserved across evolutionary time, from green algae and early basal plants to modern angiosperm plant lineages.
A competing risks approach to "biologic" interaction
DEFF Research Database (Denmark)
Andersen, Per Kragh; Skrondal, Anders
2015-01-01
framework using competing risks and argue that sufficient cause interaction between two factors can be evaluated via the parameters in a particular statistical model, the additive hazard rate model. We present empirical conditions for presence of sufficient cause interaction and an example based on data......In epidemiology, the concepts of "biologic" and "statistical" interactions have been the subject of extensive debate. We present a new approach to biologic interaction based on Rothman's original (Am J Epidemiol, 104:587-592, 1976) discussion of sufficient causes. We do this in a probabilistic...
A graph modification approach for finding core-periphery structures in protein interaction networks.
Bruckner, Sharon; Hüffner, Falk; Komusiewicz, Christian
2015-01-01
The core-periphery model for protein interaction (PPI) networks assumes that protein complexes in these networks consist of a dense core and a possibly sparse periphery that is adjacent to vertices in the core of the complex. In this work, we aim at uncovering a global core-periphery structure for a given PPI network. We propose two exact graph-theoretic formulations for this task, which aim to fit the input network to a hypothetical ground truth network by a minimum number of edge modifications. In one model each cluster has its own periphery, and in the other the periphery is shared. We first analyze both models from a theoretical point of view, showing their NP-hardness. Then, we devise efficient exact and heuristic algorithms for both models and finally perform an evaluation on subnetworks of the S. cerevisiae PPI network.
Components in time-varying graphs.
Nicosia, Vincenzo; Tang, John; Musolesi, Mirco; Russo, Giovanni; Mascolo, Cecilia; Latora, Vito
2012-06-01
Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, today it is possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is, therefore, an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis.
Laser interaction with biological material mathematical modeling
Kulikov, Kirill
2014-01-01
This book covers the principles of laser interaction with biological cells and tissues of varying degrees of organization. The problems of biomedical diagnostics are considered. Scattering of laser irradiation of blood cells is modeled for biological structures (dermis, epidermis, vascular plexus). An analytic theory is provided which is based on solving the wave equation for the electromagnetic field. It allows the accurate analysis of interference effects arising from the partial superposition of scattered waves. Treated topics of mathematical modeling are: optical characterization of biological tissue with large-scale and small-scale inhomogeneities in the layers, heating blood vessel under laser irradiation incident on the outer surface of the skin and thermo-chemical denaturation of biological structures at the example of human skin.
Integrating interactive computational modeling in biology curricula.
Directory of Open Access Journals (Sweden)
Tomáš Helikar
2015-03-01
Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.
Integrating interactive computational modeling in biology curricula.
Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A
2015-03-01
While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.
NETAL: a new graph-based method for global alignment of protein-protein interaction networks.
Neyshabur, Behnam; Khadem, Ahmadreza; Hashemifar, Somaye; Arab, Seyed Shahriar
2013-07-01
The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together. We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein-protein interaction networks. Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal. Supplementary data are available at Bioinformatics online.
Abdelaziz, Ibrahim
2017-06-12
Drug-Drug Interactions (DDIs) are a major cause of preventable Adverse Drug Reactions (ADRs), causing a significant burden on the patients’ health and the healthcare system. It is widely known that clinical studies cannot sufficiently and accurately identify DDIs for new drugs before they are made available on the market. In addition, existing public and proprietary sources of DDI information are known to be incomplete and/or inaccurate and so not reliable. As a result, there is an emerging body of research on in-silico prediction of drug-drug interactions. In this paper, we present Tiresias, a large-scale similarity-based framework that predicts DDIs through link prediction. Tiresias takes in various sources of drug-related data and knowledge as inputs, and provides DDI predictions as outputs. The process starts with semantic integration of the input data that results in a knowledge graph describing drug attributes and relationships with various related entities such as enzymes, chemical structures, and pathways. The knowledge graph is then used to compute several similarity measures between all the drugs in a scalable and distributed framework. In particular, Tiresias utilizes two classes of features in a knowledge graph: local and global features. Local features are derived from the information directly associated to each drug (i.e., one hop away) while global features are learnt by minimizing a global loss function that considers the complete structure of the knowledge graph. The resulting similarity metrics are used to build features for a large-scale logistic regression model to predict potential DDIs. We highlight the novelty of our proposed Tiresias and perform thorough evaluation of the quality of the predictions. The results show the effectiveness of Tiresias in both predicting new interactions among existing drugs as well as newly developed drugs.
Institute for Multiscale Modeling of Biological Interactions
Energy Technology Data Exchange (ETDEWEB)
Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham
2009-12-26
The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.
Novel Methods for Drug-Target Interaction Prediction using Graph Mining
Ba Alawi, Wail
2016-08-31
The problem of developing drugs that can be used to cure diseases is important and requires a careful approach. Since pursuing the wrong candidate drug for a particular disease could be very costly in terms of time and money, there is a strong interest in minimizing such risks. Drug repositioning has become a hot topic of research, as it helps reduce these risks significantly at the early stages of drug development by reusing an approved drug for the treatment of a different disease. Still, finding new usage for a drug is non-trivial, as it is necessary to find out strong supporting evidence that the proposed new uses of drugs are plausible. Many computational approaches were developed to narrow the list of possible candidate drug-target interactions (DTIs) before any experiments are done. However, many of these approaches suffer from unacceptable levels of false positives. We developed two novel methods based on graph mining networks of drugs and targets. The first method (DASPfind) finds all non-cyclic paths that connect a drug and a target, and using a function that we define, calculates a score from all the paths. This score describes our confidence that DTI is correct. We show that DASPfind significantly outperforms other state-of-the-art methods in predicting the top ranked target for each drug. We demonstrate the utility of DASPfind by predicting 15 novel DTIs over a set of ion channel proteins, and confirming 12 out of these 15 DTIs through experimental evidence reported in literature and online drug databases. The second method (DASPfind+) modifies DASPfind in order to increase the confidence and reliability of the resultant predictions. Based on the structure of the drug-target interaction (DTI) networks, we introduced an optimization scheme that incrementally alters the network structure locally for each drug to achieve more robust top 1 ranked predictions. Moreover, we explored effects of several similarity measures between the targets on the prediction
Unraveling protein networks with power graph analysis.
Directory of Open Access Journals (Sweden)
Loïc Royer
Full Text Available Networks play a crucial role in computational biology, yet their analysis and representation is still an open problem. Power Graph Analysis is a lossless transformation of biological networks into a compact, less redundant representation, exploiting the abundance of cliques and bicliques as elementary topological motifs. We demonstrate with five examples the advantages of Power Graph Analysis. Investigating protein-protein interaction networks, we show how the catalytic subunits of the casein kinase II complex are distinguishable from the regulatory subunits, how interaction profiles and sequence phylogeny of SH3 domains correlate, and how false positive interactions among high-throughput interactions are spotted. Additionally, we demonstrate the generality of Power Graph Analysis by applying it to two other types of networks. We show how power graphs induce a clustering of both transcription factors and target genes in bipartite transcription networks, and how the erosion of a phosphatase domain in type 22 non-receptor tyrosine phosphatases is detected. We apply Power Graph Analysis to high-throughput protein interaction networks and show that up to 85% (56% on average of the information is redundant. Experimental networks are more compressible than rewired ones of same degree distribution, indicating that experimental networks are rich in cliques and bicliques. Power Graphs are a novel representation of networks, which reduces network complexity by explicitly representing re-occurring network motifs. Power Graphs compress up to 85% of the edges in protein interaction networks and are applicable to all types of networks such as protein interactions, regulatory networks, or homology networks.
Cell Biology of Astrocyte-Synapse Interactions.
Allen, Nicola J; Eroglu, Cagla
2017-11-01
Astrocytes, the most abundant glial cells in the mammalian brain, are critical regulators of brain development and physiology through dynamic and often bidirectional interactions with neuronal synapses. Despite the clear importance of astrocytes for the establishment and maintenance of proper synaptic connectivity, our understanding of their role in brain function is still in its infancy. We propose that this is at least in part due to large gaps in our knowledge of the cell biology of astrocytes and the mechanisms they use to interact with synapses. In this review, we summarize some of the seminal findings that yield important insight into the cellular and molecular basis of astrocyte-neuron communication, focusing on the role of astrocytes in the development and remodeling of synapses. Furthermore, we pose some pressing questions that need to be addressed to advance our mechanistic understanding of the role of astrocytes in regulating synaptic development. Copyright © 2017 Elsevier Inc. All rights reserved.
Uncertain Graph Sparsification
Parchas, Panos; Papailiou, Nikolaos; Papadias, Dimitris; Bonchi, Francesco
2016-01-01
Uncertain graphs are prevalent in several applications including communications systems, biological databases and social networks. The ever increasing size of the underlying data renders both graph storage and query processing extremely expensive. Sparsification has often been used to reduce the size of deterministic graphs by maintaining only the important edges. However, adaptation of deterministic sparsification methods fails in the uncertain setting. To overcome this problem, we introduce...
Noble, S D; Welsh, D J A
2000-01-01
We consider the equivalence classes of graphs induced by the unsigned versions of the Reidemeister moves on knot diagrams. Any graph which is reducible by some finite sequence of these moves, to a graph with no edges is called a knot graph. We show that the class of knot graphs strictly contains the set of delta-wye graphs. We prove that the dimension of the intersection of the cycle and cocycle spaces is an effective numerical invariant of these classes.
Olayan, Rawan S.
2017-11-23
Motivation Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. Results We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using five repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new, and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs.
Volatility behavior of visibility graph EMD financial time series from Ising interacting system
Zhang, Bo; Wang, Jun; Fang, Wen
2015-08-01
A financial market dynamics model is developed and investigated by stochastic Ising system, where the Ising model is the most popular ferromagnetic model in statistical physics systems. Applying two graph based analysis and multiscale entropy method, we investigate and compare the statistical volatility behavior of return time series and the corresponding IMF series derived from the empirical mode decomposition (EMD) method. And the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, we find that the degree distribution of visibility graph for the simulation series has the power law tails, and the assortative network exhibits the mixing pattern property. All these features are in agreement with the real market data, the research confirms that the financial model established by the Ising system is reasonable.
The Cytoskeleton: Mechanical, Physical, and Biological Interactions
1996-01-01
This workshop, entitled "The Cytoskeleton: Mechanical, Physical, and Biological Interactions," was sponsored by the Center for Advanced Studies in the Space Life Sciences at the Marine Biological Laboratory. This Center was established through a cooperative agreement between the MBL and the Life Sciences Division of the National Aeronautics and Space Administration. To achieve these goals, the Center sponsors a series of workshops on various topics in the life sciences. Elements of the cytoskeleton have been implicated in the effects of gravity on the growth of plants fungi. An intriguing finding in this regard is the report indicating that an integrin-like protein may be the gravireceptor in the internodal cells of Chara. Involvement of the cytoskeleton in cellular graviperception of the basidiomycete Flammulina velutipes has also been reported. Although the responses of mammalian cells to gravity are not well documented, it has been proposed that integrins can act as mechanochemical transducers in mammalian cells. Little is known about the integrated mechanical and physical properties of cytoplasm, this workshop would be the best place to begin developing interdisciplinary approaches to the effects of mechanical stresses on cells and their most likely responsive cytoplasmic elements- the fibrous proteins comprising the cytoskeleton.
Graph-cut Based Interactive Segmentation of 3D Materials-Science Images
2014-04-26
segmentation from the automatic propa- gation approach ( Si ) saved for retrieval. A cache allows multiple inter- actions that modify the segmentation Si to be...can be min- imized via graph cuts? IEEE Trans. Pattern Anal. Mach. Intell. 26(2), 147–159 (2004) 28. Kuang , Z., Schnieders, D., Zhou, H., Wong, K.Y...2004) 40. Rowenhorst, D., Lewis, A., Spanos, G.: Three-dimensional analy- sis of grain topology and interface curvature in a β-titanium alloy. Acta
Inferring ontology graph structures using OWL reasoning.
Rodríguez-García, Miguel Ángel; Hoehndorf, Robert
2018-01-05
Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.
Inferring ontology graph structures using OWL reasoning
Rodriguez-Garcia, Miguel Angel
2018-01-05
Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.
International Nuclear Information System (INIS)
Komarek, K.; Chrapan, J.; Herec, I.; Bucka, P.
2012-01-01
In the contribution the sensor for measuring biological objects 'Auro-Graph' is described, which was suggested and designed for measuring the expressions of human's aura. From the physical point of view the aura is a field with electrical charge in the surroundings of biological as well as non-biological object, whose expressions are measured by known interactions of electrical and magnetically field. It is a field with electrical field in the human's surrounding, where atoms of surroundings are being excited by operation of biopotential (authors)
International Nuclear Information System (INIS)
De Santis, Emilio; Marinelli, Carlo
2007-01-01
We introduce and study a class of infinite-horizon non-zero-sum non-cooperative stochastic games with infinitely many interacting agents using ideas of statistical mechanics. First we show, in the general case of asymmetric interactions, the existence of a strategy that allows any player to eliminate losses after a finite random time. In the special case of symmetric interactions, we also prove that, as time goes to infinity, the game converges to a Nash equilibrium. Moreover, assuming that all agents adopt the same strategy, using arguments related to those leading to perfect simulation algorithms, spatial mixing and ergodicity are proved. In turn, ergodicity allows us to prove 'fixation', i.e. players will adopt a constant strategy after a finite time. The resulting dynamics is related to zero-temperature Glauber dynamics on random graphs of possibly infinite volume
Temporal Representation in Semantic Graphs
Energy Technology Data Exchange (ETDEWEB)
Levandoski, J J; Abdulla, G M
2007-08-07
A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.
Proxy Graph: Visual Quality Metrics of Big Graph Sampling.
Nguyen, Quan Hoang; Hong, Seok-Hee; Eades, Peter; Meidiana, Amyra
2017-06-01
Data sampling has been extensively studied for large scale graph mining. Many analyses and tasks become more efficient when performed on graph samples of much smaller size. The use of proxy objects is common in software engineering for analysis and interaction with heavy objects or systems. In this paper, we coin the term 'proxy graph' and empirically investigate how well a proxy graph visualization can represent a big graph. Our investigation focuses on proxy graphs obtained by sampling; this is one of the most common proxy approaches. Despite the plethora of data sampling studies, this is the first evaluation of sampling in the context of graph visualization. For an objective evaluation, we propose a new family of quality metrics for visual quality of proxy graphs. Our experiments cover popular sampling techniques. Our experimental results lead to guidelines for using sampling-based proxy graphs in visualization.
Graph Creation, Visualisation and Transformation
Directory of Open Access Journals (Sweden)
Maribel Fernández
2010-03-01
Full Text Available We describe a tool to create, edit, visualise and compute with interaction nets - a form of graph rewriting systems. The editor, called GraphPaper, allows users to create and edit graphs and their transformation rules using an intuitive user interface. The editor uses the functionalities of the TULIP system, which gives us access to a wealth of visualisation algorithms. Interaction nets are not only a formalism for the specification of graphs, but also a rewrite-based computation model. We discuss graph rewriting strategies and a language to express them in order to perform strategic interaction net rewriting.
Olayan, Rawan S; Ashoor, Haitham; Bajic, Vladimir B
2018-04-01
Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using 5-repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs. The data and code are provided at https://bitbucket.org/RSO24/ddr/. vladimir.bajic@kaust.edu.sa. Supplementary data are available at Bioinformatics online.
Directory of Open Access Journals (Sweden)
Aleks Kissinger
2014-03-01
Full Text Available String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. Dixon, Duncan and Kissinger introduced string graphs, which are a combinatoric representations of string diagrams, amenable to automated reasoning about diagrammatic theories via graph rewrite systems. In this extended abstract, we show how the power of such rewrite systems can be greatly extended by introducing pattern graphs, which provide a means of expressing infinite families of rewrite rules where certain marked subgraphs, called !-boxes ("bang boxes", on both sides of a rule can be copied any number of times or removed. After reviewing the string graph formalism, we show how string graphs can be extended to pattern graphs and how pattern graphs and pattern rewrite rules can be instantiated to concrete string graphs and rewrite rules. We then provide examples demonstrating the expressive power of pattern graphs and how they can be applied to study interacting algebraic structures that are central to categorical quantum mechanics.
DEFF Research Database (Denmark)
Hartnell, B.L.; Vestergaard, Preben Dahl
There are many results dealing with the problem of decomposing a fixed graph into isomorphic subgraphs. There has also been work on characterizing graphs with the property that one can delete the edges of a number of edge disjoint copies of the subgraph and, regardless of how that is done......, the graph that remains can still be decomposed (such graphs are called or ). In this paper we consider the follwing variation. Given a fixed graph H, determine which graphs (call them ) have the property that every edge disjoint packing with H is maximum. In the case that the graph H is isomorphic...... to the path on 3 nodes, we characterize the equipackable graphs of girth 5 or more. randomly packable randomly decomposable equipackable maximal...
DEFF Research Database (Denmark)
Vestergaard, Preben Dahl; Hartnell, Bert L.
2006-01-01
There are many results dealing with the problem of decomposing a fixed graph into isomorphic subgraphs. There has also been work on characterizing graphs with the property that one can delete the edges of a number of edge disjoint copies of the subgraph and, regardless of how that is done......, the graph that remains can still be decomposed (such graphs are called randomly packable or randomly decomposable). In this paper we consider the following variation. Given a fixed graph H, determine which graphs (call them equipackable) have the property that every maximal edge disjoint packing with H...... is maximum. In the case that the graph H is isomorphic to the path on 3 nodes, we characterize the equipackable graphs of girth 5 or more....
The Graph Laplacian and the Dynamics of Complex Networks
Energy Technology Data Exchange (ETDEWEB)
Thulasidasan, Sunil [Los Alamos National Laboratory
2012-06-11
In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.
Graph passing in graph transformation
Ghamarian, A.H.; Rensink, Arend; Fish, Andrew; Lambers, Leen
Graph transformation works under the whole world assumption. Therefore, in realistic systems, both the individual graphs and the set of all such graphs can grow very large. In reactive formalisms such as process algebra, on the other hand, each system is split into smaller components which
Graph Passing in Graph Transformation
Ghamarian, A.H.; Rensink, Arend
2012-01-01
Graph transformation works under the whole world assumption. Therefore, in realistic systems, both the individual graphs and the set of all such graphs can grow very large. In reactive formalisms such as process algebra, on the other hand, each system is split into smaller components which
EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Shu, Qingya; Guo, Hanqi; Che, Limei; Yuan, Xiaoru; Liu, Junfeng; Liang, Jie
2016-04-19
We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based on ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.
DEFF Research Database (Denmark)
Merker, Martin
The topic of this PhD thesis is graph decompositions. While there exist various kinds of decompositions, this thesis focuses on three problems concerning edgedecompositions. Given a family of graphs H we ask the following question: When can the edge-set of a graph be partitioned so that each part...... k(T)-edge-connected graph whose size is divisible by the size of T admits a T-decomposition. This proves a conjecture by Barát and Thomassen from 2006. Moreover, we introduce a new arboricity notion where we restrict the diameter of the trees in a decomposition into forests. We conjecture......-connected planar graph contains two edge-disjoint 18/19 -thin spanning trees. Finally, we make progress on a conjecture by Baudon, Bensmail, Przybyło, and Wozniak stating that if a graph can be decomposed into locally irregular graphs, then there exists such a decomposition with at most 3 parts. We show...
Molecular and biological interactions in colorectal cancer
Heer, Pieter de
2007-01-01
The current thesis discusses the use of molecular and biological tumor markers to predict clinical outcome. By studying several key processes in the develepment of cancer as regulation of cell motility (non-receptor protein tyrosin adesion kinases, FAK, Src and paxillin, Apoptosis (caspase-3
Zhang, Yali; Wang, Jun
2017-09-01
In an attempt to investigate the nonlinear complex evolution of financial dynamics, a new financial price model - the multitype range-intensity contact (MRIC) financial model, is developed based on the multitype range-intensity interacting contact system, in which the interaction and transmission of different types of investment attitudes in a stock market are simulated by viruses spreading. Two new random visibility graph (VG) based analyses and Lempel-Ziv complexity (LZC) are applied to study the complex behaviors of return time series and the corresponding random sorted series. The VG method is the complex network theory, and the LZC is a non-parametric measure of complexity reflecting the rate of new pattern generation of a series. In this work, the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, the numerical empirical study shows the similar complexity behaviors between the model and the real markets, the research confirms that the financial model is reasonable to some extent.
Students' Evaluation of Classroom Interactions of Their Biology ...
African Journals Online (AJOL)
' classroom interaction and their feelings towards biology lessons. Three research questions guided the study. Copies of a questionnaire containing 48 items were distributed to 1,216 senior secondary two students from nine randomly selected ...
Biotic-Abiotic Nanoscale Interactions in Biological Fuel Cells
2014-03-28
such as ATP. This strategy, called oxidative phosphorylation, is embraced by all respiratory microorganisms. Most eukaryotes and many prokaryotes are...AFRL-OSR-VA-TR-2014-0087 (YIP-10) BIOTIC-ABIOTIC NANOSCALE INTERACTIONS IN BIOLOGICAL FUEL CELLS Mohamed El-Naggar UNIVERSITY OF SOUTHERN CALIFORNIA...Interactions in Biological Fuel Cells Award Number: FA9550-10-1-0144 Start Date: 04/15/2010 Program Manager: Patrick O. Bradshaw, PhD Air
Interactive analysis of systems biology molecular expression data
Prabhakar Sunil; Salt David E; Kane Michael D; Stephenson Alan; Ouyang Qi; Zhang Mingwu; Burgner John; Buck Charles; Zhang Xiang
2008-01-01
Abstract Background Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferr...
Senior High School Student Biology Learning in Interactive Teaching
Lu, Tan-Ni; Cowie, Bronwen; Jones, Alister
2010-01-01
This paper reports Grade 12 students' biology learning during interactive teaching classes in 2001 in Taiwan. The researcher as teacher, working within an interpretive framework, set out to improve her senior high school student biology teaching and learning. An intervention based on a social constructivist view of learning was designed,…
Students' Evaluation of Classroom Interactions of Their Biology ...
African Journals Online (AJOL)
Nekky Umera
Abstract. This correlational study investigated students' evaluation of their biology teachers' classroom interaction and their feelings towards biology lessons. Three research questions guided the study. Copies of a questionnaire containing 48 items were distributed to 1,216 senior secondary two students from nine ...
Interactions of electrons with biologically important molecules
International Nuclear Information System (INIS)
Pisklova, K.; Papp, P.; Stano, M.
2012-01-01
For the study of interactions of low-energy electrons with the molecules in the gas phase, the authors used electron-molecule cross-beam apparatus. The experiment is carried out in high vacuum, where molecules of the tested compound are inducted through a capillary. For purposes of this experiment the sample was electrically heated to 180 Deg C., giving a bundle of GlyGly molecules into the gas phase. The resulting signals can be evaluated in two different modes: mass spectrum - at continuous electron energy (e.g. 100 eV) they obtained the signal of intensity of the ions according to their mass to charge ratio; ionization and resonance spectra - for selected ion mass when the authors received the signal of intensity of the ions, depending on the energy of interacting electron.
Hendrix, William; Jenkins, John; Padmanabhan, Kanchana; Chakraborty, Arpan
2014-01-01
Practical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or clusters of nodes that share common patterns of attributes and relationships, the extraction of patterns that distinguish one category of graphs from another, and the use of those patterns to predict the category of new graphs. Hands-On Application of Graph Data Mining Each chapter in the book focuses on a graph mining task, such as link analysis, cluster analysis, and classification. Through applications using real data sets, the book demonstrates how computational techniques can help solve real-world problems. The applications covered include network intrusion detection, tumor cell diagnostics, face recognition, predictive toxicology, mining metabolic and protein-protein interaction networks, and community detection in social networks. De...
Measures of interaction contrast (biological interaction) - ic, ici and icp
DEFF Research Database (Denmark)
2015-01-01
It has become more common to investigate not only single factors effect on a outcome but also to look at the interaction between factors, as is facilitated by the last decade’s massive increase in computer resources to gather and analyses large databases. Several approaches haves been promoted.Fo...
Wang, Yishu; Zhao, Hongyu; Deng, Minghua; Fang, Huaying; Yang, Dejie
2017-08-24
Epistatic miniarrary profile (EMAP) studies have enabled the mapping of large-scale genetic interaction networks and generated large amounts of data in model organisms. It provides an incredible set of molecular tools and advanced technologies that should be efficiently understanding the relationship between the genotypes and phenotypes of individuals. However, the network information gained from EMAP cannot be fully exploited using the traditional statistical network models. Because the genetic network is always heterogeneous, for example, the network structure features for one subset of nodes are different from those of the left nodes. Exponentialfamily random graph models (ERGMs) are a family of statistical models, which provide a principled and flexible way to describe the structural features (e.g. the density, centrality and assortativity) of an observed network. However, the single ERGM is not enough to capture this heterogeneity of networks. In this paper, we consider a mixture ERGM (MixtureEGRM) networks, which model a network with several communities, where each community is described by a single EGRM.
The influence of biological rhythms on host-parasite interactions.
Martinez-Bakker, Micaela; Helm, Barbara
2015-06-01
Biological rhythms, from circadian control of cellular processes to annual cycles in life history, are a main structural element of biology. Biological rhythms are considered adaptive because they enable organisms to partition activities to cope with, and take advantage of, predictable fluctuations in environmental conditions. A flourishing area of immunology is uncovering rhythms in the immune system of animals, including humans. Given the temporal structure of immunity, and rhythms in parasite activity and disease incidence, we propose that the intersection of chronobiology, disease ecology, and evolutionary biology holds the key to understanding host-parasite interactions. Here, we review host-parasite interactions while explicitly considering biological rhythms, and propose that rhythms: influence within-host infection dynamics and transmission between hosts, might account for diel and annual periodicity in host-parasite systems, and can lead to a host-parasite arms race in the temporal domain. Copyright © 2015 Elsevier Ltd. All rights reserved.
Quantitative Genetic Interactions Reveal Layers of Biological Modularity
Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.
2010-01-01
In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918
Interactive analysis of systems biology molecular expression data
Directory of Open Access Journals (Sweden)
Prabhakar Sunil
2008-02-01
Full Text Available Abstract Background Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations. Results Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data. Conclusion The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe in growth media (an ionomics dataset. This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.
Directory of Open Access Journals (Sweden)
Fúlvia Eloá Maricato
2017-09-01
Full Text Available Epistemology of biology has been the subject of many discussions in the field of Science and Biology education. This study aimed to bring new elaborations to enrich these discussions, highlighting its importance and how this epistemology canbe inserted in Science and Biology education. The presented investigation is anchored on three main pillars:(i some reflections on epistemologyof biology; (iithe importance and vagueness of the concept of biological/ecological interaction in literature; (iii the empirical investigation on epistemologyof biology by this research group. The semiotic analysis allowed us to infer that the research subjects: expressed to understand the importance, amplitude and centrality of this concept to the Biology Knowledge; evolved from a starting vision in which it was only understood the biological interactions with the external environment to one in which we start to understand the biological interactions in several levels of organization thus, advancing from a syncretic/abductive thinking to a deductive reasoning, going through the inductive one; and are concerned on how to teach the studied concept to their future students. This analysisallowed some reflections that can contribute to a creation of a solid epistemology of biology in its many contexts, with the main focus on initial teacher training.
Huang, Yun-An; Jastorff, Jan; Van den Stock, Jan; Van de Vliet, Laura; Dupont, Patrick; Vandenbulcke, Mathieu
2018-05-15
Psychological construction models of emotion state that emotions are variable concepts constructed by fundamental psychological processes, whereas according to basic emotion theory, emotions cannot be divided into more fundamental units and each basic emotion is represented by a unique and innate neural circuitry. In a previous study, we found evidence for the psychological construction account by showing that several brain regions were commonly activated when perceiving different emotions (i.e. a general emotion network). Moreover, this set of brain regions included areas associated with core affect, conceptualization and executive control, as predicted by psychological construction models. Here we investigate directed functional brain connectivity in the same dataset to address two questions: 1) is there a common pathway within the general emotion network for the perception of different emotions and 2) if so, does this common pathway contain information to distinguish between different emotions? We used generalized psychophysiological interactions and information flow indices to examine the connectivity within the general emotion network. The results revealed a general emotion pathway that connects neural nodes involved in core affect, conceptualization, language and executive control. Perception of different emotions could not be accurately classified based on the connectivity patterns from the nodes of the general emotion pathway. Successful classification was achieved when connections outside the general emotion pathway were included. We propose that the general emotion pathway functions as a common pathway within the general emotion network and is involved in shared basic psychological processes across emotions. However, additional connections within the general emotion network are required to classify different emotions, consistent with a constructionist account. Copyright © 2018 Elsevier Inc. All rights reserved.
Methylation of zebularine: a quantum mechanical study incorporating interactive 3D pdf graphs.
Selvam, Lalitha; Vasilyev, Vladislav; Wang, Feng
2009-08-20
Methylation of a cytidine deaminase inhibitor, 1-(beta-D-ribofuranosyl)-2-pyrimidone (i.e., zebularine (zeb)), which produces 1-(beta-D-ribofuranosyl)-5-methyl-2-pyrimidinone (d5), has been investigated using density functional theory models. The optimized structures of zeb and d5 and the valence orbitals primarily responsible for the methylation in d5 are presented using state-of-the-art interactive (on a computer or online) three-dimensional (3D) graphics in a portable document format (pdf) file, 3D-PDF (http://www.web3d.org/x3d/vrml/ ). The facility to embed 3D molecular structures into pdf documents has been developed jointly at Swinburne University of Technology and the National Computational Infrastructure, the Australian National University. The methyl fragment in the base moiety shows little effect on the sugar puckering but apparently affects anisotropic properties, such as condensed Fukui functions. Binding energy spectra, both valence space and core space, are noticeably affected; in particular, in the outer-valence space (e.g., IP < 20 eV). The methyl fragment delocalizes and diffuses into almost all valence space, but orbitals 8 (57a, IP = 12.57 eV), 18 (47a, IP = 14.70 eV), and 37 (28a, IP = 22.15 eV) are identified as fingerprint for the methyl fragment. In the inner shell, however, the impact of the methyl can be localized and identified by chemical shift. A small, global, red shift is found for the O-K, N-K and sugar C-K spectra, whereas the base C-K spectrum exhibits apparent methyl-related changes.
Olayan, Rawan S.
2017-12-01
Computational drug repurposing aims at finding new medical uses for existing drugs. The identification of novel drug-target interactions (DTIs) can be a useful part of such a task. Computational determination of DTIs is a convenient strategy for systematic screening of a large number of drugs in the attempt to identify new DTIs at low cost and with reasonable accuracy. This necessitates development of accurate computational methods that can help focus on the follow-up experimental validation on a smaller number of highly likely targets for a drug. Although many methods have been proposed for computational DTI prediction, they suffer the high false positive prediction rate or they do not predict the effect that drugs exert on targets in DTIs. In this report, first, we present a comprehensive review of the recent progress in the field of DTI prediction from data-centric and algorithm-centric perspectives. The aim is to provide a comprehensive review of computational methods for identifying DTIs, which could help in constructing more reliable methods. Then, we present DDR, an efficient method to predict the existence of DTIs. DDR achieves significantly more accurate results compared to the other state-of-theart methods. As supported by independent evidences, we verified as correct 22 out of the top 25 DDR DTIs predictions. This validation proves the practical utility of DDR, suggesting that DDR can be used as an efficient method to identify 5 correct DTIs. Finally, we present DDR-FE method that predicts the effect types of a drug on its target. On different representative datasets, under various test setups, and using different performance measures, we show that DDR-FE achieves extremely good performance. Using blind test data, we verified as correct 2,300 out of 3,076 DTIs effects predicted by DDR-FE. This suggests that DDR-FE can be used as an efficient method to identify correct effects of a drug on its target.
Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich
2012-01-01
Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test,p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38
International Nuclear Information System (INIS)
Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich
2012-01-01
Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of
Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich
2012-03-01
Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction
Directory of Open Access Journals (Sweden)
Zabiniako Vitaly
2014-12-01
Full Text Available In this article, the authors perform an analysis in order to assess adaptation of magnetic force-directed algorithms for context-based information extraction from multi-attributed graphs during visualization sessions. Theoretic standings behind magnetic force-directed approach are stated together with review on how particular features of respective algorithms in combination with appropriate visual techniques are especially suitable for improved processing and presenting of knowledge that is captured in form of graphs. The complexity of retrieving multi-attributed information within the proposed approach is handled with dedicated tools, such as selective attraction of nodes to MFE (Magnetic Force Emitter based on search criteria, localization of POI (Point of Interest regions, graph node anchoring, etc. Implicit compatibility of aforementioned tools with interactive nature of data exploration is distinguished. Description of case study, based on bibliometric network analysis is given, which is followed by the review of existing related works in this field. Conclusions are made and further studies in the field of visualization of multi-attributed graphs are defined.
ANALYTICAL METHODS FOR KINETIC STUDIES OF BIOLOGICAL INTERACTIONS: A REVIEW
Zheng, Xiwei; Bi, Cong; Li, Zhao; Podariu, Maria; Hage, David S.
2015-01-01
The rates at which biological interactions occur can provide important information concerning the mechanism and behavior of these processes in living systems. This review discusses several analytical methods that can be used to examine the kinetics of biological interactions. These techniques include common or traditional methods such as stopped-flow analysis and surface plasmon resonance spectroscopy, as well as alternative methods based on affinity chromatography and capillary electrophoresis. The general principles and theory behind these approaches are examined, and it is shown how each technique can be utilized to provide information on the kinetics of biological interactions. Examples of applications are also given for each method. In addition, a discussion is provided on the relative advantages or potential limitations of each technique regarding its use in kinetic studies. PMID:25700721
The fascinating world of graph theory
Benjamin, Arthur; Zhang, Ping
2015-01-01
Graph theory goes back several centuries and revolves around the study of graphs-mathematical structures showing relations between objects. With applications in biology, computer science, transportation science, and other areas, graph theory encompasses some of the most beautiful formulas in mathematics-and some of its most famous problems. The Fascinating World of Graph Theory explores the questions and puzzles that have been studied, and often solved, through graph theory. This book looks at graph theory's development and the vibrant individuals responsible for the field's growth. Introducin
Peng, Yifan; Arighi, Cecilia; Wu, Cathy H; Vijay-Shanker, K
2016-01-01
There has been a large growth in the number of biomedical publications that report experimental results. Many of these results concern detection of protein-protein interactions (PPI). In BioCreative V, we participated in the BioC task and developed a PPI system to detect text passages with PPIs in the full-text articles. By adopting the BioC format, the output of the system can be seamlessly added to the biocuration pipeline with little effort required for the system integration. A distinctive feature of our PPI system is that it utilizes extended dependency graph, an intermediate level of representation that attempts to abstract away syntactic variations in text. As a result, we are able to use only a limited set of rules to extract PPI pairs in the sentences, and additional rules to detect additional passages for PPI pairs. For evaluation, we used the 95 articles that were provided for the BioC annotation task. We retrieved the unique PPIs from the BioGRID database for these articles and show that our system achieves a recall of 83.5%. In order to evaluate the detection of passages with PPIs, we further annotated Abstract and Results sections of 20 documents from the dataset and show that an f-value of 80.5% was obtained. To evaluate the generalizability of the system, we also conducted experiments on AIMed, a well-known PPI corpus. We achieved an f-value of 76.1% for sentence detection and an f-value of 64.7% for unique PPI detection.Database URL: http://proteininformationresource.org/iprolink/corpora. © The Author(s) 2016. Published by Oxford University Press.
Predicting genetic interactions with random walks on biological networks
Directory of Open Access Journals (Sweden)
Singh Ambuj K
2009-01-01
Full Text Available Abstract Background Several studies have demonstrated that synthetic lethal genetic interactions between gene mutations provide an indication of functional redundancy between molecular complexes and pathways. These observations help explain the finding that organisms are able to tolerate single gene deletions for a large majority of genes. For example, system-wide gene knockout/knockdown studies in S. cerevisiae and C. elegans revealed non-viable phenotypes for a mere 18% and 10% of the genome, respectively. It has been postulated that the low percentage of essential genes reflects the extensive amount of genetic buffering that occurs within genomes. Consistent with this hypothesis, systematic double-knockout screens in S. cerevisiae and C. elegans show that, on average, 0.5% of tested gene pairs are synthetic sick or synthetic lethal. While knowledge of synthetic lethal interactions provides valuable insight into molecular functionality, testing all combinations of gene pairs represents a daunting task for molecular biologists, as the combinatorial nature of these relationships imposes a large experimental burden. Still, the task of mapping pairwise interactions between genes is essential to discovering functional relationships between molecular complexes and pathways, as they form the basis of genetic robustness. Towards the goal of alleviating the experimental workload, computational techniques that accurately predict genetic interactions can potentially aid in targeting the most likely candidate interactions. Building on previous studies that analyzed properties of network topology to predict genetic interactions, we apply random walks on biological networks to accurately predict pairwise genetic interactions. Furthermore, we incorporate all published non-interactions into our algorithm for measuring the topological relatedness between two genes. We apply our method to S. cerevisiae and C. elegans datasets and, using a decision tree
Ising models of strongly coupled biological networks with multivariate interactions
Merchan, Lina; Nemenman, Ilya
2013-03-01
Biological networks consist of a large number of variables that can be coupled by complex multivariate interactions. However, several neuroscience and cell biology experiments have reported that observed statistics of network states can be approximated surprisingly well by maximum entropy models that constrain correlations only within pairs of variables. We would like to verify if this reduction in complexity results from intricacies of biological organization, or if it is a more general attribute of these networks. We generate random networks with p-spin (p > 2) interactions, with N spins and M interaction terms. The probability distribution of the network states is then calculated and approximated with a maximum entropy model based on constraining pairwise spin correlations. Depending on the M/N ratio and the strength of the interaction terms, we observe a transition where the pairwise approximation is very good to a region where it fails. This resembles the sat-unsat transition in constraint satisfaction problems. We argue that the pairwise model works when the number of highly probable states is small. We argue that many biological systems must operate in a strongly constrained regime, and hence we expect the pairwise approximation to be accurate for a wide class of problems. This research has been partially supported by the James S McDonnell Foundation grant No.220020321.
Spectral partitioning in equitable graphs.
Barucca, Paolo
2017-06-01
Graph partitioning problems emerge in a wide variety of complex systems, ranging from biology to finance, but can be rigorously analyzed and solved only for a few graph ensembles. Here, an ensemble of equitable graphs, i.e., random graphs with a block-regular structure, is studied, for which analytical results can be obtained. In particular, the spectral density of this ensemble is computed exactly for a modular and bipartite structure. Kesten-McKay's law for random regular graphs is found analytically to apply also for modular and bipartite structures when blocks are homogeneous. An exact solution to graph partitioning for two equal-sized communities is proposed and verified numerically, and a conjecture on the absence of an efficient recovery detectability transition in equitable graphs is suggested. A final discussion summarizes results and outlines their relevance for the solution of graph partitioning problems in other graph ensembles, in particular for the study of detectability thresholds and resolution limits in stochastic block models.
Chemical Force Microscopy of Chemical and Biological Interactions
Energy Technology Data Exchange (ETDEWEB)
Noy, A
2006-01-02
Interactions between chemical functionalities define outcomes of the vast majority of important events in chemistry, biology and materials science. Chemical Force Microscopy (CFM)--a technique that uses direct chemical functionalization of AFM probes with specific functionalities--allows researchers to investigate these important interactions directly. We review the basic principles of CFM, some examples of its application, and theoretical models that provide the basis for understanding the experimental results. We also emphasize application of modern kinetic theory of non-covalent interactions strength to the analysis of CFM data.
Trudeau, Richard J
1994-01-01
Preface1. Pure Mathematics Introduction; Euclidean Geometry as Pure Mathematics; Games; Why Study Pure Mathematics?; What's Coming; Suggested Reading2. Graphs Introduction; Sets; Paradox; Graphs; Graph diagrams; Cautions; Common Graphs; Discovery; Complements and Subgraphs; Isomorphism; Recognizing Isomorphic Graphs; Semantics The Number of Graphs Having a Given nu; Exercises; Suggested Reading3. Planar Graphs Introduction; UG, K subscript 5, and the Jordan Curve Theorem; Are there More Nonplanar Graphs?; Expansions; Kuratowski's Theorem; Determining Whether a Graph is Planar or
Interaction mechanisms and biological effects of static magnetic fields
Energy Technology Data Exchange (ETDEWEB)
Tenforde, T.S.
1994-06-01
Mechanisms through which static magnetic fields interact with living systems are described and illustrated by selected experimental observations. These mechanisms include electrodynamic interactions with moving, ionic charges (blood flow and nerve impulse conduction), magnetomechanical interactions (orientation and translation of molecules structures and magnetic particles), and interactions with electronic spin states in charge transfer reactions (photo-induced electron transfer in photosynthesis). A general summary is also presented of the biological effects of static magnetic fields. There is convincing experimental evidence for magnetoreception mechanisms in several classes of lower organisms, including bacteria and marine organisms. However, in more highly evolved species of animals, there is no evidence that the interactions of static magnetic fields with flux densities up to 2 Tesla (1 Tesla [T] = 10{sup 4} Gauss) produce either behavioral or physiolocical alterations. These results, based on controlled studies with laboratory animals, are consistent with the outcome of recent epidemiological surveys on human populations exposed occupationally to static magnetic fields.
Interactions of nanomaterials and biological systems: implications to personalized nanomedicine☆
Zhang, Xue-Qing; Xu, Xiaoyang; Bertrand, Nicolas; Pridgen, Eric; Swami, Archana; Farokhzad, Omid C.
2012-01-01
The application of nanotechnology to personalized medicine provides an unprecedented opportunity to improve the treatment of many diseases. Nanomaterials offer several advantages as therapeutic and diagnostic tools due to design flexibility, small sizes, large surface-to-volume ratio, and ease of surface modification with multivalent ligands to increase avidity for target molecules. Nanomaterials can be engineered to interact with specific biological components, allowing them to benefit from the insights provided by personalized medicine techniques. To tailor these interactions, a comprehensive knowledge of how nanomaterials interact with biological systems is critical. Herein, we discuss how the interactions of nanomaterials with biological systems can guide their design for diagnostic, imaging and drug delivery purposes. A general overview of nanomaterials under investigation is provided with an emphasis on systems that have reached clinical trials. Finally, considerations for the development of personalized nanomedicines are summarized such as the potential toxicity, scientific and technical challenges in fabricating them, and regulatory and ethical issues raised by the utilization of nanomaterials. PMID:22917779
Diestel, Reinhard
2017-01-01
This standard textbook of modern graph theory, now in its fifth edition, combines the authority of a classic with the engaging freshness of style that is the hallmark of active mathematics. It covers the core material of the subject with concise yet reliably complete proofs, while offering glimpses of more advanced methods in each field by one or two deeper results, again with proofs given in full detail. The book can be used as a reliable text for an introductory course, as a graduate text, and for self-study. From the reviews: “This outstanding book cannot be substituted with any other book on the present textbook market. It has every chance of becoming the standard textbook for graph theory.”Acta Scientiarum Mathematiciarum “Deep, clear, wonderful. This is a serious book about the heart of graph theory. It has depth and integrity. ”Persi Diaconis & Ron Graham, SIAM Review “The book has received a very enthusiastic reception, which it amply deserves. A masterly elucidation of modern graph theo...
Biological interactions and human health effects of static magnetic fields
International Nuclear Information System (INIS)
Tenforde, T.S.
1994-09-01
Mechanisms through which static magnetic fields interact with living systems will be described and illustrated by selected experimental observations. These mechanisms include electrodynamic interactions with moving ionic charges (blood flow and nerve impulse conduction), magnetomechanical interactions (orientation and translation of molecular structures and magnetic particles), and interactions with electronic spin states in charge transfer reactions (photo-induced electron transfer in photosynthesis). A general summary will also be presented of the biological effects of static magnetic fields studied in the laboratory and in natural settings. One aspect of magnetic field effects that merits special concern is their influence on implanted medical electronic devices such as cardiac pacemakers. Several extensive studies have demonstrated closure of the reed switch in pacemakers exposed to relatively weak static magnetic fields, thereby causing them to revert to an asynchronous mode of operation that is potentially hazardous. Recommendations for human exposure limits are provided
Multiple graph regularized protein domain ranking
Wang, Jim Jing-Yan
2012-11-19
Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.
Multiple graph regularized protein domain ranking.
Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin
2012-11-19
Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.
Multiple graph regularized protein domain ranking
Directory of Open Access Journals (Sweden)
Wang Jim
2012-11-01
Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.
Directory of Open Access Journals (Sweden)
Kenneth K H Chui
2011-02-01
Full Text Available Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously.We introduce and demonstrate multi-panel (MP graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old, 1991-2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004-2005; and asthma-associated hospital visits for children aged 0-18 at Milwaukee Children's Hospital of Wisconsin, 1997-2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots.MP graphs can weave together two vital dynamics--temporality and demographics--that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts.
Maximal outerplanar graphs as chordal graphs, path-neighborhood graphs, and triangle graphs
R.C. Laskar (R.C.); H.M. Mulder (Martyn); B. Novick (Beth)
2011-01-01
textabstractMaximal outerplanar graphs are characterized using three different classes of graphs. A path-neighborhood graph is a connected graph in which every neighborhood induces a path. The triangle graph $T(G)$ has the triangles of the graph $G$ as its vertices, two of these being adjacent
Gould, Ronald
2012-01-01
This introduction to graph theory focuses on well-established topics, covering primary techniques and including both algorithmic and theoretical problems. The algorithms are presented with a minimum of advanced data structures and programming details. This thoroughly corrected 1988 edition provides insights to computer scientists as well as advanced undergraduates and graduate students of topology, algebra, and matrix theory. Fundamental concepts and notation and elementary properties and operations are the first subjects, followed by examinations of paths and searching, trees, and networks. S
Chartrand, Gary; Zhang, Ping
2010-01-01
Gary Chartrand has influenced the world of Graph Theory for almost half a century. He has supervised more than a score of Ph.D. dissertations and written several books on the subject. The most widely known of these texts, Graphs and Digraphs, … has much to recommend it, with clear exposition, and numerous challenging examples [that] make it an ideal textbook for the advanced undergraduate or beginning graduate course. The authors have updated their notation to reflect the current practice in this still-growing area of study. By the authors' estimation, the 5th edition is approximately 50% longer than the 4th edition. … the legendary Frank Harary, author of the second graph theory text ever produced, is one of the figures profiled. His book was the standard in the discipline for several decades. Chartrand, Lesniak and Zhang have produced a worthy successor.-John T. Saccoman, MAA Reviews, June 2012 (This book is in the MAA's basic library list.)As with the earlier editions, the current text emphasizes clear...
Directory of Open Access Journals (Sweden)
Divo1 Jean-Louis
2006-01-01
Full Text Available Abstract Background A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs. Results GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces. Conclusion GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at academy@genostar.com. A commercial licence form can be obtained for profit company at info@genostar.com. See also http://www.genostar.org.
CHARACTERISATION OF REGULAR GRAPHS AS LOOP GRAPHS ...
African Journals Online (AJOL)
There have been various generalisations of Cayley graphs, prototypes of transitive graphs. The most generalised is the description of graphs on general groupoids. What has clearly emerged in this exercise is that the philosophy of constructing graphs on groupoids offers a fruitful avenue from which we may understand ...
De Bruijn graphs and DNA graphs
Pendavingh, Rudi; Schuurman, Petra; Woeginger, Gerhard; Brandstädt, Andreas; Le, Van Bang
2001-01-01
In this paper we prove the NP-hardness of various recognition problems for subgraphs of De Bruijn graphs. In particular, the recognition of DNA graphs is shown to be NP-hard; DNA graphs are the vertex induced subgraphs of De Bruijn graphs over a four letter alphabet. As a consequence, two open
Finding optimal interaction interface alignments between biological complexes
Cui, Xuefeng
2015-06-13
Motivation: Biological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which are keys to understanding their evolutionary histories and functions. Although various structure alignment methods have been developed to successfully access the similarities of protein structures or certain types of interaction interfaces, existing alignment tools cannot directly align arbitrary types of interfaces formed by protein, DNA or RNA molecules. Specifically, they require a \\'blackbox preprocessing\\' to standardize interface types and chain identifiers. Yet their performance is limited and sometimes unsatisfactory. Results: Here we introduce a novel method, PROSTA-inter, that automatically determines and aligns interaction interfaces between two arbitrary types of complex structures. Our method uses sequentially remote fragments to search for the optimal superimposition. The optimal residue matching problem is then formulated as a maximum weighted bipartite matching problem to detect the optimal sequence order-independent alignment. Benchmark evaluation on all non-redundant protein-DNA complexes in PDB shows significant performance improvement of our method over TM-align and iAlign (with the \\'blackbox preprocessing\\'). Two case studies where our method discovers, for the first time, structural similarities between two pairs of functionally related protein-DNA complexes are presented. We further demonstrate the power of our method on detecting structural similarities between a protein-protein complex and a protein-RNA complex, which is biologically known as a protein-RNA mimicry case. © The Author 2015. Published by Oxford University Press.
Nanomaterials modulate stem cell differentiation: biological interaction and underlying mechanisms.
Wei, Min; Li, Song; Le, Weidong
2017-10-25
Stem cells are unspecialized cells that have the potential for self-renewal and differentiation into more specialized cell types. The chemical and physical properties of surrounding microenvironment contribute to the growth and differentiation of stem cells and consequently play crucial roles in the regulation of stem cells' fate. Nanomaterials hold great promise in biological and biomedical fields owing to their unique properties, such as controllable particle size, facile synthesis, large surface-to-volume ratio, tunable surface chemistry, and biocompatibility. Over the recent years, accumulating evidence has shown that nanomaterials can facilitate stem cell proliferation and differentiation, and great effort is undertaken to explore their possible modulating manners and mechanisms on stem cell differentiation. In present review, we summarize recent progress in the regulating potential of various nanomaterials on stem cell differentiation and discuss the possible cell uptake, biological interaction and underlying mechanisms.
Method and apparatus to image biological interactions in plants
Weisenberger, Andrew; Bonito, Gregory M.; Reid, Chantal D.; Smith, Mark Frederick
2015-12-22
A method to dynamically image the actual translocation of molecular compounds of interest in a plant root, root system, and rhizosphere without disturbing the root or the soil. The technique makes use of radioactive isotopes as tracers to label molecules of interest and to image their distribution in the plant and/or soil. The method allows for the study and imaging of various biological and biochemical interactions in the rhizosphere of a plant, including, but not limited to, mycorrhizal associations in such regions.
Electromagnetic field interaction with biological systems and microwave hyperthermia
International Nuclear Information System (INIS)
Behari, J.; Srivastava, G.P.
1997-01-01
The interaction of microwaves with biological system is best understood in terms of heating of the tissues. This in turn lead to changes in chemical reaction rates and current flows, the understanding of which demands a basic knowledge of mechanisms of microwave-biointeraction. A practical advantage of this lies in using this method for selective heating of tissues as in the case of cancer. Modality of heating by using interstitial implants and interstitial antennas is discussed. Design of antennas for specific heating profile is also presented. (author)
Diestel, Reinhard
2012-01-01
HauptbeschreibungThis standard textbook of modern graph theory, now in its fourth edition, combinesthe authority of a classic with the engaging freshness of style that is the hallmarkof active mathematics. It covers the core material of the subject with concise yetreliably complete proofs, while offering glimpses of more advanced methodsin each field by one or two deeper results, again with proofs given in full detail.The book can be used as a reliable text for an introductory course, as a graduatetext, and for self-study. Rezension"Deep, clear, wonderful. This is a serious book about the
Graph limits and hereditary properties
Janson, Svante
2011-01-01
We collect some general results on graph limits associated to hereditary classes of graphs. As examples, we consider some classes defined by forbidden subgraphs and some classes of intersection graphs, including triangle-free graphs, chordal graphs, cographs, interval graphs, unit interval graphs, threshold graphs, and line graphs.
Relations between the set-complexity and the structure of graphs and their sub-graphs.
Ignac, Tomasz M; Sakhanenko, Nikita A; Galas, David J
2012-09-21
: We describe some new conceptual tools for the rigorous, mathematical description of the "set-complexity" of graphs. This set-complexity has been shown previously to be a useful measure for analyzing some biological networks, and in discussing biological information in a quantitative fashion. The advances described here allow us to define some significant relationships between the set-complexity measure and the structure of graphs, and of their component sub-graphs. We show here that modular graph structures tend to maximize the set-complexity of graphs. We point out the relationship between modularity and redundancy, and discuss the significance of set-complexity in this regard. We specifically discuss the relationship between complexity and entropy in the case of complete-bipartite graphs, and present a new method for constructing highly complex, binary graphs. These results can be extended to the case of ternary graphs, and to other multi-edge graphs, which are fundamentally more relevant to biological structures and systems. Finally, our results lead us to an approach for extracting high complexity modular graphs from large, noisy graphs with low information content. We illustrate this approach with two examples.
Quantum information processing with graph states
International Nuclear Information System (INIS)
Schlingemann, Dirk-Michael
2005-04-01
Graph states are multiparticle states which are associated with graphs. Each vertex of the graph corresponds to a single system or particle. The links describe quantum correlations (entanglement) between pairs of connected particles. Graph states were initiated independently by two research groups: On the one hand, graph states were introduced by Briegel and Raussendorf as a resource for a new model of one-way quantum computing, where algorithms are implemented by a sequence of measurements at single particles. On the other hand, graph states were developed by the author of this thesis and ReinhardWerner in Braunschweig, as a tool to build quantum error correcting codes, called graph codes. The connection between the two approaches was fully realized in close cooperation of both research groups. This habilitation thesis provides a survey of the theory of graph codes, focussing mainly, but not exclusively on the author's own research work. We present the theoretical and mathematical background for the analysis of graph codes. The concept of one-way quantum computing for general graph states is discussed. We explicitly show how to realize the encoding and decoding device of a graph code on a one-way quantum computer. This kind of implementation is to be seen as a mathematical description of a quantum memory device. In addition to that, we investigate interaction processes, which enable the creation of graph states on very large systems. Particular graph states can be created, for instance, by an Ising type interaction between next neighbor particles which sits at the points of an infinitely extended cubic lattice. Based on the theory of quantum cellular automata, we give a constructive characterization of general interactions which create a translationally invariant graph state. (orig.)
Chartrand, Gary; Rosen, Kenneth H
2008-01-01
Beginning with the origin of the four color problem in 1852, the field of graph colorings has developed into one of the most popular areas of graph theory. Introducing graph theory with a coloring theme, Chromatic Graph Theory explores connections between major topics in graph theory and graph colorings as well as emerging topics. This self-contained book first presents various fundamentals of graph theory that lie outside of graph colorings, including basic terminology and results, trees and connectivity, Eulerian and Hamiltonian graphs, matchings and factorizations, and graph embeddings. The remainder of the text deals exclusively with graph colorings. It covers vertex colorings and bounds for the chromatic number, vertex colorings of graphs embedded on surfaces, and a variety of restricted vertex colorings. The authors also describe edge colorings, monochromatic and rainbow edge colorings, complete vertex colorings, several distinguishing vertex and edge colorings, and many distance-related vertex coloring...
Triactome: neuro-immune-adipose interactions. Implication in vascular biology
Directory of Open Access Journals (Sweden)
George Nikov Chaldakov
2014-04-01
Full Text Available Understanding how the precise interactions of nerves, immune cells and adipose tissue account for cardiovascular and metabolic biology is a central aim of biomedical research at present. A long standing paradigm holds that the vascular wall is composed of three concentric tissue coats (tunicae: intima, media, and adventitia. However, large- and medium-sized arteries, where usually atherosclerotic lesions develop, are consistently surrounded by periadventitial adipose tissue, we recently designated tunica adiposa (in brief, adiposa like intima, media, adventitia. According to present paradigm, atherosclerosis is an immune-mediated inflammatory disease featured by endothelial dysfunction/intimal thickening, medial atrophy and adventitial lesions associated with adipose dysfunction, whereas hypertension is characterized by hyperinnervation-associated medial thickening due to smooth muscle cell hypertrophy/hyperplasia. Periadventitial adipose tissue expansion is associated with increased infiltration of immune cells, both adipocytes and immunocytes secreting pro-inflammatory and anti-inflammatory (metabotrophic signaling proteins collectively dubbed adipokines. However, the role of perivascular nerves and their interactions with immune cells and paracrine adipose tissue is not yet evaluated in such an integrated way. The present review attempts to briefly highlight the findings in basic and translational sciences in this area focusing on neuro-immune-adipose interactions, herein referred to as triactome. Triactome-targeted pharmacology may provide a novel therapeutic approach in cardiovascular disease.
Perception of social interactions for spatially scrambled biological motion.
Thurman, Steven M; Lu, Hongjing
2014-01-01
It is vitally important for humans to detect living creatures in the environment and to analyze their behavior to facilitate action understanding and high-level social inference. The current study employed naturalistic point-light animations to examine the ability of human observers to spontaneously identify and discriminate socially interactive behaviors between two human agents. Specifically, we investigated the importance of global body form, intrinsic joint movements, extrinsic whole-body movements, and critically, the congruency between intrinsic and extrinsic motions. Motion congruency is hypothesized to be particularly important because of the constraint it imposes on naturalistic action due to the inherent causal relationship between limb movements and whole body motion. Using a free response paradigm in Experiment 1, we discovered that many naïve observers (55%) spontaneously attributed animate and/or social traits to spatially-scrambled displays of interpersonal interaction. Total stimulus motion energy was strongly correlated with the likelihood that an observer would attribute animate/social traits, as opposed to physical/mechanical traits, to the scrambled dot stimuli. In Experiment 2, we found that participants could identify interactions between spatially-scrambled displays of human dance as long as congruency was maintained between intrinsic/extrinsic movements. Violating the motion congruency constraint resulted in chance discrimination performance for the spatially-scrambled displays. Finally, Experiment 3 showed that scrambled point-light dancing animations violating this constraint were also rated as significantly less interactive than animations with congruent intrinsic/extrinsic motion. These results demonstrate the importance of intrinsic/extrinsic motion congruency for biological motion analysis, and support a theoretical framework in which early visual filters help to detect animate agents in the environment based on several fundamental
Perception of social interactions for spatially scrambled biological motion.
Directory of Open Access Journals (Sweden)
Steven M Thurman
Full Text Available It is vitally important for humans to detect living creatures in the environment and to analyze their behavior to facilitate action understanding and high-level social inference. The current study employed naturalistic point-light animations to examine the ability of human observers to spontaneously identify and discriminate socially interactive behaviors between two human agents. Specifically, we investigated the importance of global body form, intrinsic joint movements, extrinsic whole-body movements, and critically, the congruency between intrinsic and extrinsic motions. Motion congruency is hypothesized to be particularly important because of the constraint it imposes on naturalistic action due to the inherent causal relationship between limb movements and whole body motion. Using a free response paradigm in Experiment 1, we discovered that many naïve observers (55% spontaneously attributed animate and/or social traits to spatially-scrambled displays of interpersonal interaction. Total stimulus motion energy was strongly correlated with the likelihood that an observer would attribute animate/social traits, as opposed to physical/mechanical traits, to the scrambled dot stimuli. In Experiment 2, we found that participants could identify interactions between spatially-scrambled displays of human dance as long as congruency was maintained between intrinsic/extrinsic movements. Violating the motion congruency constraint resulted in chance discrimination performance for the spatially-scrambled displays. Finally, Experiment 3 showed that scrambled point-light dancing animations violating this constraint were also rated as significantly less interactive than animations with congruent intrinsic/extrinsic motion. These results demonstrate the importance of intrinsic/extrinsic motion congruency for biological motion analysis, and support a theoretical framework in which early visual filters help to detect animate agents in the environment based on
Biological efficiency of interaction between various radiation and chemicals
International Nuclear Information System (INIS)
Kim, Jin Kyu; Yu, Dong Han; Lee, Byoung Hun; Petin, Vladislav G.; Geras'kin, Stanislav A.; Cebulska-Wasilewska, Antonina; Panek, Agnieszka; Wiechec, Anna
2004-06-01
This research project has been carried out jointly with INP (Poland) to develop technologies to assess the biological efficiency of interaction between radiation and chemicals. Through the cooperative project, KAERI and INP have established wide variety of bioassay techniques applicable to radiation bioscience, human monitoring, molecular epidemiology and environmental science. The joint experiment, in special, made it possible to utilize the merits of both institutes and to upgrade and verify KAERI's current technology level. All results of the cooperative research will be jointly published in high standard scientific journals listed in the Science Citation Index (SCI), which can make the role of fundamental basis for improving relationship between Korea and Poland. Research skills such as Trad-MCN assay, SCGE assay, immunohistochemical assay and molecular assay developed through joint research will be further elaborated and will be continuously used for the collaboration between two institutes
The role of antioxidant-protein interactions in biological membrane
International Nuclear Information System (INIS)
McGillivray, Duncan J; Singh, Rachna; Melton, Laurence D.; Worcester, David L.; Gilbert, Elliot P.
2009-01-01
Full text: Oxidative damage of cellular membranes has been linked to a variety of disease pathologies, including cardiac disease, Alzheimer's and complications due to diabetes. The oxidation of unsaturated and polyunsaturated fatty acid chains found in cellular membranes leads to significant alteration in membrane physical properties, including lipid orientation and membrane permeability, which ultimately affect biological function. Polyphenols are naturally occurring phytochemicals present in a number of fruit and vegetables that are of interest for their anti-oxidative powers. These polyphenols inhibit lipid oxidation in cellular membrane surfaces, although the mechanism of this inhibition is not entirely clear. Moreover, the polyphenols have significant binding affinity for proteins, which can lead to the formation of soluble and insoluble protein-polyphenol complexes Significantly, in the presence of casein proteins the oxidation inhibition the polyphenols in the membrane is significantly enhanced (as assessed by Lipid Peroxidation Inhibition Capacity assays). Thus the antioxidant pathway appears to involve these protein/polyphenol complexes, as well as direct antioxidant action by the polyphenol. Here we discuss neutron and x-ray scattering results from phospholipid membranes, looking at the positioning of two examples of polyphenolic antioxidants in phospholipid membranes, quercetin and phloretin, the antioxidants' impact on the membrane organisation, and the interaction between antioxidant and extra-membranous protein. This information sheds light on the mechanism of antioxidant protection in these systems, which may be used to understand biological responses to oxidative stress.
How Genetic and Other Biological Factors Interact with Smoking Decisions.
Bierut, Laura; Cesarini, David
2015-09-01
Despite clear links between genes and smoking, effective public policy requires far richer measurement of the feedback between biological, behavioral, and environmental factors. The Kavli HUMAN Project (KHP) plans to exploit the plummeting costs of data gathering and to make creative use of new technologies to construct a longitudinal panel data set that would compare favorably to existing longitudinal surveys, both in terms of the richness of the behavioral measures and the cost-effectiveness of the data collection. By developing a more comprehensive approach to characterizing behavior than traditional methods, KHP will allow researchers to paint a much richer picture of an individual's life-cycle trajectory of smoking, alcohol, and drug use, and interactions with other choices and environmental factors. The longitudinal nature of KHP will be particularly valuable in light of the increasing evidence for how smoking behavior affects physiology and health. The KHP could have a transformative impact on the understanding of the biology of addictive behaviors such as smoking, and of a rich range of prevention and amelioration policies.
Molecular infection biology : interactions between microorganisms and cells
National Research Council Canada - National Science Library
Hacker, Jörg (Jörg Hinrich); Heesemann, Jurgen
2002-01-01
... and epidemiology of infectious diseases. Investigators, specialists, clinicians, and graduate students in biology, pharmacy, and medicine will find Molecular Infection Biology an invaluable addition to their professional libraries...
Fixation Time for Evolutionary Graphs
Nie, Pu-Yan; Zhang, Pei-Ai
Evolutionary graph theory (EGT) is recently proposed by Lieberman et al. in 2005. EGT is successful for explaining biological evolution and some social phenomena. It is extremely important to consider the time of fixation for EGT in many practical problems, including evolutionary theory and the evolution of cooperation. This study characterizes the time to asymptotically reach fixation.
Energy Technology Data Exchange (ETDEWEB)
Bozzo, S.R.; Galdos, F.; Hakoopian, R.
1977-01-01
This plotting package contains routines found useful for drawing graphs. Written in FORTRAN EXTENDED version 4 as used on a CDC 6600 computer, the interactive package uses a DTC 300/S terminal as the output device. The routines included in the package are PLOT, TEXT1, LINE, and AXIS. 1 table.
Graph-based iterative Group Analysis enhances microarray interpretation
Directory of Open Access Journals (Sweden)
Amtmann Anna
2004-07-01
Full Text Available Abstract 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.
Scale-space measures for graph topology link protein network architecture to function.
Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen
2014-06-15
The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.
Microbiology and atmospheric processes: chemical interactions of primary biological aerosols
Directory of Open Access Journals (Sweden)
L. Deguillaume
2008-07-01
Full Text Available This paper discusses the influence of primary biological aerosols (PBA on atmospheric chemistry and vice versa through microbiological and chemical properties and processes. Several studies have shown that PBA represent a significant fraction of air particulate matter and hence affect the microstructure and water uptake of aerosol particles. Moreover, airborne micro-organisms, namely fungal spores and bacteria, can transform chemical constituents of the atmosphere by metabolic activity. Recent studies have emphasized the viability of bacteria and metabolic degradation of organic substances in cloud water. On the other hand, the viability and metabolic activity of airborne micro-organisms depend strongly on physical and chemical atmospheric parameters such as temperature, pressure, radiation, pH value and nutrient concentrations. In spite of recent advances, however, our knowledge of the microbiological and chemical interactions of PBA in the atmosphere is rather limited. Further targeted investigations combining laboratory experiments, field measurements, and modelling studies will be required to characterize the chemical feedbacks, microbiological activities at the air/snow/water interface supplied to the atmosphere.
Human Possibilities: The Interaction of Biology and Culture
Directory of Open Access Journals (Sweden)
Riane Eisler
2015-06-01
Full Text Available This article briefly describes the two main strands of a new unified theory about human nature and human possibilities: cultural transformation theory and bio-culturalism. Bio-culturalism combines findings from neuroscience about how our brains develop in interaction with our environments with findings from the study of relational dynamics, a new method of social analysis focusing on what kinds of relations—from intimate to international—a particular culture or subculture supports. Bio-culturalism recognizes that our species has a vast spectrum of genetic capacities, ranging from consciousness, caring, empathy, cooperation, and creativity to insensitivity, cruelty, exploitation, and destructiveness, and proposes that which of these capacities are expressed or inhibited largely hinges on the nature of our cultural environments. Cultural transformation theory looks at the whole span of human cultural evolution from the perspective of the tension between the contrasting configurations of the partnership system and the domination system as two underlying possibilities for structuring beliefs, institutions, and relationships. The article describes the core components of partnership- and domination-oriented societies, provides examples of each, and proposes that our future hinges on accelerating the cultural transformation from domination to partnership in our time of nuclear and biological weapons and the ever more efficient despoliation of nature, when high technology guided by an ethos of domination and conquest could take us to an evolutionary dead end.
da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier
2018-01-01
A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.
Dynamic planar embeddings of dynamic graphs
DEFF Research Database (Denmark)
Holm, Jacob; Rotenberg, Eva
2017-01-01
, exploiting that the complement of a spanning tree of a connected plane graph is a spanning tree of the dual graph. The primal and dual trees are interpreted as having the same Euler tour, and a main idea of the new algorithm is an elegant interaction between top trees over the two trees via their common...
Dynamic planar embeddings of dynamic graphs
DEFF Research Database (Denmark)
Holm, Jacob; Rotenberg, Eva
2015-01-01
that the complement of a spanning tree of a connected plane graph is a spanning tree of the dual graph. The primal and dual trees are interpreted as having the same Euler tour, and a main idea of the new algorithm is an elegant interaction between top trees over the two trees via their common Euler tour....
GRAPHIE: graph based histology image explorer.
Ding, Hao; Wang, Chao; Huang, Kun; Machiraju, Raghu
2015-01-01
Histology images comprise one of the important sources of knowledge for phenotyping studies in systems biology. However, the annotation and analyses of histological data have remained a manual, subjective and relatively low-throughput process. We introduce Graph based Histology Image Explorer (GRAPHIE)-a visual analytics tool to explore, annotate and discover potential relationships in histology image collections within a biologically relevant context. The design of GRAPHIE is guided by domain experts' requirements and well-known InfoVis mantras. By representing each image with informative features and then subsequently visualizing the image collection with a graph, GRAPHIE allows users to effectively explore the image collection. The features were designed to capture localized morphological properties in the given tissue specimen. More importantly, users can perform feature selection in an interactive way to improve the visualization of the image collection and the overall annotation process. Finally, the annotation allows for a better prospective examination of datasets as demonstrated in the users study. Thus, our design of GRAPHIE allows for the users to navigate and explore large collections of histology image datasets. We demonstrated the usefulness of our visual analytics approach through two case studies. Both of the cases showed efficient annotation and analysis of histology image collection.
Biological General Repository for Interaction Datasets (BioGRID)
U.S. Department of Health & Human Services — BioGRID is an online interaction repository with data on raw protein and genetic interactions from major model organism species. All interaction data are freely...
Directory of Open Access Journals (Sweden)
Hannah Matthew A
2006-12-01
Full Text Available Abstract Background Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Results Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs. PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis. PageMan offers a complete user's guide, a web-based over-representation analysis as
Bapat, Ravindra B
2014-01-01
This new edition illustrates the power of linear algebra in the study of graphs. The emphasis on matrix techniques is greater than in other texts on algebraic graph theory. Important matrices associated with graphs (for example, incidence, adjacency and Laplacian matrices) are treated in detail. Presenting a useful overview of selected topics in algebraic graph theory, early chapters of the text focus on regular graphs, algebraic connectivity, the distance matrix of a tree, and its generalized version for arbitrary graphs, known as the resistance matrix. Coverage of later topics include Laplacian eigenvalues of threshold graphs, the positive definite completion problem and matrix games based on a graph. Such an extensive coverage of the subject area provides a welcome prompt for further exploration. The inclusion of exercises enables practical learning throughout the book. In the new edition, a new chapter is added on the line graph of a tree, while some results in Chapter 6 on Perron-Frobenius theory are reo...
Evolutionary Games of Multiplayer Cooperation on Graphs
Arranz, Jordi; Traulsen, Arne
2016-01-01
There has been much interest in studying evolutionary games in structured populations, often modeled as graphs. However, most analytical results so far have only been obtained for two-player or linear games, while the study of more complex multiplayer games has been usually tackled by computer simulations. Here we investigate evolutionary multiplayer games on graphs updated with a Moran death-Birth process. For cycles, we obtain an exact analytical condition for cooperation to be favored by natural selection, given in terms of the payoffs of the game and a set of structure coefficients. For regular graphs of degree three and larger, we estimate this condition using a combination of pair approximation and diffusion approximation. For a large class of cooperation games, our approximations suggest that graph-structured populations are stronger promoters of cooperation than populations lacking spatial structure. Computer simulations validate our analytical approximations for random regular graphs and cycles, but show systematic differences for graphs with many loops such as lattices. In particular, our simulation results show that these kinds of graphs can even lead to more stringent conditions for the evolution of cooperation than well-mixed populations. Overall, we provide evidence suggesting that the complexity arising from many-player interactions and spatial structure can be captured by pair approximation in the case of random graphs, but that it need to be handled with care for graphs with high clustering. PMID:27513946
Evolutionary Games of Multiplayer Cooperation on Graphs.
Peña, Jorge; Wu, Bin; Arranz, Jordi; Traulsen, Arne
2016-08-01
There has been much interest in studying evolutionary games in structured populations, often modeled as graphs. However, most analytical results so far have only been obtained for two-player or linear games, while the study of more complex multiplayer games has been usually tackled by computer simulations. Here we investigate evolutionary multiplayer games on graphs updated with a Moran death-Birth process. For cycles, we obtain an exact analytical condition for cooperation to be favored by natural selection, given in terms of the payoffs of the game and a set of structure coefficients. For regular graphs of degree three and larger, we estimate this condition using a combination of pair approximation and diffusion approximation. For a large class of cooperation games, our approximations suggest that graph-structured populations are stronger promoters of cooperation than populations lacking spatial structure. Computer simulations validate our analytical approximations for random regular graphs and cycles, but show systematic differences for graphs with many loops such as lattices. In particular, our simulation results show that these kinds of graphs can even lead to more stringent conditions for the evolution of cooperation than well-mixed populations. Overall, we provide evidence suggesting that the complexity arising from many-player interactions and spatial structure can be captured by pair approximation in the case of random graphs, but that it need to be handled with care for graphs with high clustering.
Kundu, Kousik; Costa, Fabrizio; Backofen, Rolf
2013-07-01
State-of-the-art experimental data for determining binding specificities of peptide recognition modules (PRMs) is obtained by high-throughput approaches like peptide arrays. Most prediction tools applicable to this kind of data are based on an initial multiple alignment of the peptide ligands. Building an initial alignment can be error-prone, especially in the case of the proline-rich peptides bound by the SH3 domains. Here, we present a machine-learning approach based on an efficient graph-kernel technique to predict the specificity of a large set of 70 human SH3 domains, which are an important class of PRMs. The graph-kernel strategy allows us to (i) integrate several types of physico-chemical information for each amino acid, (ii) consider high-order correlations between these features and (iii) eliminate the need for an initial peptide alignment. We build specialized models for each human SH3 domain and achieve competitive predictive performance of 0.73 area under precision-recall curve, compared with 0.27 area under precision-recall curve for state-of-the-art methods based on position weight matrices. We show that better models can be obtained when we use information on the noninteracting peptides (negative examples), which is currently not used by the state-of-the art approaches based on position weight matrices. To this end, we analyze two strategies to identify subsets of high confidence negative data. The techniques introduced here are more general and hence can also be used for any other protein domains, which interact with short peptides (i.e. other PRMs). The program with the predictive models can be found at http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/SH3PepInt.tar.gz. We also provide a genome-wide prediction for all 70 human SH3 domains, which can be found under http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/Genome-Wide-Predictions.tar.gz. Supplementary data are available at Bioinformatics online.
Floral biology and the effects of plant-pollinator interaction on ...
African Journals Online (AJOL)
Reproductive biology and patterns of plant-pollinator interaction are fundamental to gene flow, diversity and evolutionary success of plants. Consequently, we examined the magnitude of insect-plant interaction based on the dynamics of breeding systems and floral biology and their effects on pollination intensity, fruit and ...
Environmental evolutionary graph theory.
Maciejewski, Wes; Puleo, Gregory J
2014-11-07
Understanding the influence of an environment on the evolution of its resident population is a major challenge in evolutionary biology. Great progress has been made in homogeneous population structures while heterogeneous structures have received relatively less attention. Here we present a structured population model where different individuals are best suited to different regions of their environment. The underlying structure is a graph: individuals occupy vertices, which are connected by edges. If an individual is suited for their vertex, they receive an increase in fecundity. This framework allows attention to be restricted to the spatial arrangement of suitable habitat. We prove some basic properties of this model and find some counter-intuitive results. Notably, (1) the arrangement of suitable sites is as important as their proportion, and (2) decreasing the proportion of suitable sites may result in a decrease in the fixation time of an allele. Copyright © 2014 Elsevier Ltd. All rights reserved.
Lichen-moss interactions within biological soil crusts
Ruckteschler, Nina; Williams, Laura; Büdel, Burkhard; Weber, Bettina
2015-04-01
Biological soil crusts (biocrusts) create well-known hotspots of microbial activity, being important components of hot and cold arid terrestrial regions. They colonize the uppermost millimeters of the soil, being composed of fungi, (cyano-) bacteria, algae, lichens, bryophytes and archaea in varying proportions. Biocrusts protect the (semi-) arid landscape from wind and water erosion, and also increase water holding capacity and nutrient content. Depending on location and developmental stage, composition and species abundance vary within biocrusts. As species live in close contact, they are expected to influence each other, but only a few interactions between different organisms have so far been explored. In the present study, we investigated the effects of the lichen Fulgensia fulgens whilst growing on the moss Trichostomum crispulum. While 77% of Fulgensia fulgens thalli were found growing associated with mosses in a German biocrust, up to 95% of Fulgensia bracteata thalli were moss-associated in a Swedish biocrust. In 49% (Germany) and in 78% (Sweden) of cases, thalli were observed on the moss T. crispulum and less frequently on four and three different moss species. Beneath F. fulgens and F. bracteata thalli, the mosses were dead and in close vicinity to the lichens the mosses appeared frail, bringing us to the assumption that the lichens may release substances harming the moss. We prepared a water extract from the lichen F. fulgens and used this to water the moss thalli (n = 6) on a daily basis over a time-span of three weeks. In a control setup, artificial rainwater was applied to the moss thalli (n = 6). Once a week, maximum CO2 gas exchange rates of the thalli were measured under constant conditions and at the end of the experiment the chlorophyll content of the moss samples was determined. In the course of the experiment net photosynthesis (NP) of the treatment samples decreased concurrently with an increase in dark respiration (DR). The control samples
Toward an interactive article: integrating journals and biological databases
Directory of Open Access Journals (Sweden)
Marygold Steven J
2011-05-01
Full Text Available Abstract Background Journal articles and databases are two major modes of communication in the biological sciences, and thus integrating these critical resources is of urgent importance to increase the pace of discovery. Projects focused on bridging the gap between journals and databases have been on the rise over the last five years and have resulted in the development of automated tools that can recognize entities within a document and link those entities to a relevant database. Unfortunately, automated tools cannot resolve ambiguities that arise from one term being used to signify entities that are quite distinct from one another. Instead, resolving these ambiguities requires some manual oversight. Finding the right balance between the speed and portability of automation and the accuracy and flexibility of manual effort is a crucial goal to making text markup a successful venture. Results We have established a journal article mark-up pipeline that links GENETICS journal articles and the model organism database (MOD WormBase. This pipeline uses a lexicon built with entities from the database as a first step. The entity markup pipeline results in links from over nine classes of objects including genes, proteins, alleles, phenotypes and anatomical terms. New entities and ambiguities are discovered and resolved by a database curator through a manual quality control (QC step, along with help from authors via a web form that is provided to them by the journal. New entities discovered through this pipeline are immediately sent to an appropriate curator at the database. Ambiguous entities that do not automatically resolve to one link are resolved by hand ensuring an accurate link. This pipeline has been extended to other databases, namely Saccharomyces Genome Database (SGD and FlyBase, and has been implemented in marking up a paper with links to multiple databases. Conclusions Our semi-automated pipeline hyperlinks articles published in GENETICS to
Integral trees and integral graphs
Wang, Ligong
2005-01-01
This monograph deals with integral graphs, Laplacian integral regular graphs, cospectral graphs and cospectral integral graphs. The organization of this work, which consists of eight chapters, is as follows.
Directory of Open Access Journals (Sweden)
Amine Labriji
2017-07-01
Full Text Available The topic of identifying the similarity of graphs was considered as highly recommended research field in the Web semantic, artificial intelligence, the shape recognition and information research. One of the fundamental problems of graph databases is finding similar graphs to a graph query. Existing approaches dealing with this problem are usually based on the nodes and arcs of the two graphs, regardless of parental semantic links. For instance, a common connection is not identified as being part of the similarity of two graphs in cases like two graphs without common concepts, the measure of similarity based on the union of two graphs, or the one based on the notion of maximum common sub-graph (SCM, or the distance of edition of graphs. This leads to an inadequate situation in the context of information research. To overcome this problem, we suggest a new measure of similarity between graphs, based on the similarity measure of Wu and Palmer. We have shown that this new measure satisfies the properties of a measure of similarities and we applied this new measure on examples. The results show that our measure provides a run time with a gain of time compared to existing approaches. In addition, we compared the relevance of the similarity values obtained, it appears that this new graphs measure is advantageous and offers a contribution to solving the problem mentioned above.
Loukas, A.
2015-01-01
We have recently seen a surge of research focusing on the processing of graph data. The emerging field of signal processing on graphs focuses on the extension of classical discrete signal processing techniques to the graph setting. Arguably, the greatest breakthrough of the field has been the
Indian Academy of Sciences (India)
IAS Admin
graph. We also note before closing this general discus- sion that among the family of regular and connected graphs, the graphs in the family of SRGs are character- ized by having exactly three distinct eigenvalues of the adjacency matrix. The friendship theorem asserts that if friendship in a community is a symmetric relation ...
Brouwer, A.E.; Haemers, W.H.
2012-01-01
This book gives an elementary treatment of the basic material about graph spectra, both for ordinary, and Laplace and Seidel spectra. The text progresses systematically, by covering standard topics before presenting some new material on trees, strongly regular graphs, two-graphs, association
Graphing Inequalities, Connecting Meaning
Switzer, J. Matt
2014-01-01
Students often have difficulty with graphing inequalities (see Filloy, Rojano, and Rubio 2002; Drijvers 2002), and J. Matt Switzer's students were no exception. Although students can produce graphs for simple inequalities, they often struggle when the format of the inequality is unfamiliar. Even when producing a correct graph of an…
Pluhař, Z; Weidenmüller, H A
2014-04-11
For time-reversal invariant graphs we prove the Bohigas-Giannoni-Schmit conjecture in its most general form: For graphs that are mixing in the classical limit, all spectral correlation functions coincide with those of the Gaussian orthogonal ensemble of random matrices. For open graphs, we derive the analogous identities for all S-matrix correlation functions.
Sotirov, Renata
2017-01-01
The graph bisection problem is the problem of partitioning the vertex set of a graph into two sets of given sizes such that the sum of weights of edges joining these two sets is optimized. We present a semidefinite programming relaxation for the graph bisection problem with a matrix variable of
Hyperbolicity in median graphs
Indian Academy of Sciences (India)
If is hyperbolic, we denote by () the sharp hyperbolicity constant of , i.e., ( X ) = inf { ≥ 0 : X is − hyperbolic } . In this paper we study the hyperbolicity of median graphs and we also obtain some results about general hyperbolic graphs. In particular, we prove that a median graph is hyperbolic if and only if its ...
Clustering: An Interactive Technique to Enhance Learning in Biology.
Ambron, Joanna
1988-01-01
Explains an interdisciplinary approach to biology and writing which increases students' mastery of vocabulary, scientific concepts, creativity, and expression. Describes modifications of the clustering technique used to summarize lectures, integrate reading and understand textbook material. (RT)
Interacting domain-specific languages with biological problem solving environments
Cickovski, Trevor M.
Iteratively developing a biological model and verifying results with lab observations has become standard practice in computational biology. This process is currently facilitated by biological Problem Solving Environments (PSEs), multi-tiered and modular software frameworks which traditionally consist of two layers: a computational layer written in a high level language using design patterns, and a user interface layer which hides its details. Although PSEs have proven effective, they still enforce some communication overhead between biologists refining their models through repeated comparison with experimental observations in vitro or in vivo, and programmers actually implementing model extensions and modifications within the computational layer. I illustrate the use of biological Domain-Specific Languages (DSLs) as a middle-level PSE tier to ameliorate this problem by providing experimentalists with the ability to iteratively test and develop their models using a higher degree of expressive power compared to a graphical interface, while saving the requirement of general purpose programming knowledge. I develop two radically different biological DSLs: XML-based BIOLOGO will model biological morphogenesis using a cell-centered stochastic cellular automaton and translate into C++ modules for an object-oriented PSE C OMPUCELL3D, and MDLab will provide a set of high-level Python libraries for running molecular dynamics simulations, using wrapped functionality from the C++ PSE PROTOMOL. I describe each language in detail, including its its roles within the larger PSE and its expressibility in terms of representable phenomena, and a discussion of observations from users of the languages. Moreover I will use these studies to draw general conclusions about biological DSL development, including dependencies upon the goals of the corresponding PSE, strategies, and tradeoffs.
Discriminative graph embedding for label propagation.
Nguyen, Canh Hao; Mamitsuka, Hiroshi
2011-09-01
In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.
Gross, Jonathan L
2003-01-01
The Handbook of Graph Theory is the most comprehensive single-source guide to graph theory ever published. Best-selling authors Jonathan Gross and Jay Yellen assembled an outstanding team of experts to contribute overviews of more than 50 of the most significant topics in graph theory-including those related to algorithmic and optimization approaches as well as ""pure"" graph theory. They then carefully edited the compilation to produce a unified, authoritative work ideal for ready reference.Designed and edited with non-experts in mind, the Handbook of Graph Theory makes information easy to fi
Hell, Pavol
2004-01-01
This is a book about graph homomorphisms. Graph theory is now an established discipline but the study of graph homomorphisms has only recently begun to gain wide acceptance and interest. The subject gives a useful perspective in areas such as graph reconstruction, products, fractional and circular colourings, and has applications in complexity theory, artificial intelligence, telecommunication, and, most recently, statistical physics.Based on the authors' lecture notes for graduate courses, this book can be used as a textbook for a second course in graph theory at 4th year or master's level an
Wong, Pak C.; Mackey, Patrick S.; Perrine, Kenneth A.; Foote, Harlan P.; Thomas, James J.
2008-12-23
Methods for visualizing a graph by automatically drawing elements of the graph as labels are disclosed. In one embodiment, the method comprises receiving node information and edge information from an input device and/or communication interface, constructing a graph layout based at least in part on that information, wherein the edges are automatically drawn as labels, and displaying the graph on a display device according to the graph layout. In some embodiments, the nodes are automatically drawn as labels instead of, or in addition to, the label-edges.
A cognitive architecture-based model of graph comprehension
Peebles, David
2012-01-01
I present a model of expert comprehension performance for 2 × 2 "interaction" graphs typically used to present data from two-way factorial research designs. Developed using the ACT-R cognitive architecture, the model simulates the cognitive and perceptual operations involved in interpreting interaction graphs and provides a detailed characterisation of the information extracted from the diagram, the prior knowledge required to interpret interaction graphs, and the knowledge generated during t...
Assessing statistical significance in causal graphs.
Chindelevitch, Leonid; Loh, Po-Ru; Enayetallah, Ahmed; Berger, Bonnie; Ziemek, Daniel
2012-02-20
Causal graphs are an increasingly popular tool for the analysis of biological datasets. In particular, signed causal graphs--directed graphs whose edges additionally have a sign denoting upregulation or downregulation--can be used to model regulatory networks within a cell. Such models allow prediction of downstream effects of regulation of biological entities; conversely, they also enable inference of causative agents behind observed expression changes. However, due to their complex nature, signed causal graph models present special challenges with respect to assessing statistical significance. In this paper we frame and solve two fundamental computational problems that arise in practice when computing appropriate null distributions for hypothesis testing. First, we show how to compute a p-value for agreement between observed and model-predicted classifications of gene transcripts as upregulated, downregulated, or neither. Specifically, how likely are the classifications to agree to the same extent under the null distribution of the observed classification being randomized? This problem, which we call "Ternary Dot Product Distribution" owing to its mathematical form, can be viewed as a generalization of Fisher's exact test to ternary variables. We present two computationally efficient algorithms for computing the Ternary Dot Product Distribution and investigate its combinatorial structure analytically and numerically to establish computational complexity bounds.Second, we develop an algorithm for efficiently performing random sampling of causal graphs. This enables p-value computation under a different, equally important null distribution obtained by randomizing the graph topology but keeping fixed its basic structure: connectedness and the positive and negative in- and out-degrees of each vertex. We provide an algorithm for sampling a graph from this distribution uniformly at random. We also highlight theoretical challenges unique to signed causal graphs
Simplicial complexes of graphs
Jonsson, Jakob
2008-01-01
A graph complex is a finite family of graphs closed under deletion of edges. Graph complexes show up naturally in many different areas of mathematics, including commutative algebra, geometry, and knot theory. Identifying each graph with its edge set, one may view a graph complex as a simplicial complex and hence interpret it as a geometric object. This volume examines topological properties of graph complexes, focusing on homotopy type and homology. Many of the proofs are based on Robin Forman's discrete version of Morse theory. As a byproduct, this volume also provides a loosely defined toolbox for attacking problems in topological combinatorics via discrete Morse theory. In terms of simplicity and power, arguably the most efficient tool is Forman's divide and conquer approach via decision trees; it is successfully applied to a large number of graph and digraph complexes.
Pixels to Graphs by Associative Embedding
Newell, Alejandro
2017-06-22
Graphs are a useful abstraction of image content. Not only can graphs represent details about individual objects in a scene but they can capture the interactions between pairs of objects. We present a method for training a convolutional neural network such that it takes in an input image and produces a full graph. This is done end-to-end in a single stage with the use of associative embeddings. The network learns to simultaneously identify all of the elements that make up a graph and piece them together. We benchmark on the Visual Genome dataset, and report a Recall@50 of 9.7% compared to the prior state-of-the-art at 3.4%, a nearly threefold improvement on the challenging task of scene graph generation.
Positron interactions and transport in biologically relevant molecules
International Nuclear Information System (INIS)
Makochekanwa, C; Jones, A; Caradonna, P; Slaughter, D; Sullivan, J; Buckman, S; Bankovic, A; Petrovic, Z; Malovic, G; Dujko, S; Marler, J; Nixon, K; Brunger, M
2009-01-01
We present new, high-resolution measurements of positron scattering from biologically relevant molecules, such as water and formic acid. The measurements include absolute determinations of total scattering and positronium formation and they have enabled us to assemble a set of cross sections for these molecules which can be used in an investigation of positron transport in these systems.
Directory of Open Access Journals (Sweden)
David ePeebles
2015-10-01
Full Text Available The distinction between informational and computational equivalence of representations, first articulated by Larkin and Simon (1987 has been a fundamental principle in the analysis of diagrammatic reasoning which has been supported empirically on numerous occasions. We present an experiment that investigates this principle in relation to the performance of expert graph users of 2 x 2 'interaction' bar and line graphs. The study sought to determine whether expert interpretation is affected by graph format in the same way that novice interpretations are. The findings revealed that, unlike novices - and contrary to the assumptions of several graph comprehension models - experts' performance was the same for both graph formats, with their interpretation of bar graphs being no worse than that for line graphs. We discuss the implications of the study for guidelines for presenting such data and for models of expert graph comprehension.
Graphing trillions of triangles.
Burkhardt, Paul
2017-07-01
The increasing size of Big Data is often heralded but how data are transformed and represented is also profoundly important to knowledge discovery, and this is exemplified in Big Graph analytics. Much attention has been placed on the scale of the input graph but the product of a graph algorithm can be many times larger than the input. This is true for many graph problems, such as listing all triangles in a graph. Enabling scalable graph exploration for Big Graphs requires new approaches to algorithms, architectures, and visual analytics. A brief tutorial is given to aid the argument for thoughtful representation of data in the context of graph analysis. Then a new algebraic method to reduce the arithmetic operations in counting and listing triangles in graphs is introduced. Additionally, a scalable triangle listing algorithm in the MapReduce model will be presented followed by a description of the experiments with that algorithm that led to the current largest and fastest triangle listing benchmarks to date. Finally, a method for identifying triangles in new visual graph exploration technologies is proposed.
SING: subgraph search in non-homogeneous graphs.
Di Natale, Raffaele; Ferro, Alfredo; Giugno, Rosalba; Mongiovì, Misael; Pulvirenti, Alfredo; Shasha, Dennis
2010-02-19
Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image understanding. Since subgraph isomorphism is a computationally hard problem, indexing techniques have been intensively exploited to speed up the process. Such systems filter out those graphs which cannot contain the query, and apply a subgraph isomorphism algorithm to each residual candidate graph. The applicability of such systems is limited to databases of small graphs, because their filtering power degrades on large graphs. In this paper, SING (Subgraph search In Non-homogeneous Graphs), a novel indexing system able to cope with large graphs, is presented. The method uses the notion of feature, which can be a small subgraph, subtree or path. Each graph in the database is annotated with the set of all its features. The key point is to make use of feature locality information. This idea is used to both improve the filtering performance and speed up the subgraph isomorphism task. Extensive tests on chemical compounds, biological networks and synthetic graphs show that the proposed system outperforms the most popular systems in query time over databases of medium and large graphs. Other specific tests show that the proposed system is effective for single large graphs.
Chartrand, Gary
1984-01-01
Graph theory is used today in the physical sciences, social sciences, computer science, and other areas. Introductory Graph Theory presents a nontechnical introduction to this exciting field in a clear, lively, and informative style. Author Gary Chartrand covers the important elementary topics of graph theory and its applications. In addition, he presents a large variety of proofs designed to strengthen mathematical techniques and offers challenging opportunities to have fun with mathematics. Ten major topics - profusely illustrated - include: Mathematical Models, Elementary Concepts of Grap
Pathfinder: Visual Analysis of Paths in Graphs
Partl, C.; Gratzl, S.; Streit, M.; Wassermann, A. M.; Pfister, H.; Schmalstieg, D.; Lex, A.
2016-01-01
The analysis of paths in graphs is highly relevant in many domains. Typically, path-related tasks are performed in node-link layouts. Unfortunately, graph layouts often do not scale to the size of many real world networks. Also, many networks are multivariate, i.e., contain rich attribute sets associated with the nodes and edges. These attributes are often critical in judging paths, but directly visualizing attributes in a graph layout exacerbates the scalability problem. In this paper, we present visual analysis solutions dedicated to path-related tasks in large and highly multivariate graphs. We show that by focusing on paths, we can address the scalability problem of multivariate graph visualization, equipping analysts with a powerful tool to explore large graphs. We introduce Pathfinder (Figure 1), a technique that provides visual methods to query paths, while considering various constraints. The resulting set of paths is visualized in both a ranked list and as a node-link diagram. For the paths in the list, we display rich attribute data associated with nodes and edges, and the node-link diagram provides topological context. The paths can be ranked based on topological properties, such as path length or average node degree, and scores derived from attribute data. Pathfinder is designed to scale to graphs with tens of thousands of nodes and edges by employing strategies such as incremental query results. We demonstrate Pathfinder's fitness for use in scenarios with data from a coauthor network and biological pathways. PMID:27942090
Pathfinder: Visual Analysis of Paths in Graphs.
Partl, C; Gratzl, S; Streit, M; Wassermann, A M; Pfister, H; Schmalstieg, D; Lex, A
2016-06-01
The analysis of paths in graphs is highly relevant in many domains. Typically, path-related tasks are performed in node-link layouts. Unfortunately, graph layouts often do not scale to the size of many real world networks. Also, many networks are multivariate, i.e., contain rich attribute sets associated with the nodes and edges. These attributes are often critical in judging paths, but directly visualizing attributes in a graph layout exacerbates the scalability problem. In this paper, we present visual analysis solutions dedicated to path-related tasks in large and highly multivariate graphs. We show that by focusing on paths, we can address the scalability problem of multivariate graph visualization, equipping analysts with a powerful tool to explore large graphs. We introduce Pathfinder (Figure 1), a technique that provides visual methods to query paths, while considering various constraints. The resulting set of paths is visualized in both a ranked list and as a node-link diagram. For the paths in the list, we display rich attribute data associated with nodes and edges, and the node-link diagram provides topological context. The paths can be ranked based on topological properties, such as path length or average node degree, and scores derived from attribute data. Pathfinder is designed to scale to graphs with tens of thousands of nodes and edges by employing strategies such as incremental query results. We demonstrate Pathfinder's fitness for use in scenarios with data from a coauthor network and biological pathways.
Sensor for measurement of biological objects and their mutual interaction - patent No. 285 085
International Nuclear Information System (INIS)
Komarek, K.; Chrapan, J.; Herec, I.
2006-01-01
In this paper the sensor for measurement of biological objects 'Aurograph' is described. The 'Aurograph' was proposed for measurement of human aura. The aura is characterised as a space with electric charge in vicinity of biological but also non-biological object. Their expression can be measured by known interactions of electric and magnetic fields. It is the space with electric charge in locality of human body where by action of bio-potential the atoms of surrounding are excited
Creating more effective graphs
Robbins, Naomi B
2012-01-01
A succinct and highly readable guide to creating effective graphs The right graph can be a powerful tool for communicating information, improving a presentation, or conveying your point in print. If your professional endeavors call for you to present data graphically, here's a book that can help you do it more effectively. Creating More Effective Graphs gives you the basic knowledge and techniques required to choose and create appropriate graphs for a broad range of applications. Using real-world examples everyone can relate to, the author draws on her years of experience in gr
DEFF Research Database (Denmark)
Mansutti, Alessio; Miculan, Marino; Peressotti, Marco
2017-01-01
We introduce loose graph simulations (LGS), a new notion about labelled graphs which subsumes in an intuitive and natural way subgraph isomorphism (SGI), regular language pattern matching (RLPM) and graph simulation (GS). Being a unification of all these notions, LGS allows us to express directly...... also problems which are “mixed” instances of previous ones, and hence which would not fit easily in any of them. After the definition and some examples, we show that the problem of finding loose graph simulations is NP-complete, we provide formal translation of SGI, RLPM, and GS into LGSs, and we give...
DEFF Research Database (Denmark)
Thomassen, Carsten
2014-01-01
We prove a general result on graph factors modulo k . A special case says that, for each natural number k , every (12k−7)-edge-connected graph with an even number of vertices contains a spanning subgraph in which each vertex has degree congruent to k modulo 2k.......We prove a general result on graph factors modulo k . A special case says that, for each natural number k , every (12k−7)-edge-connected graph with an even number of vertices contains a spanning subgraph in which each vertex has degree congruent to k modulo 2k....
Gelfand, I M; Shnol, E E
1969-01-01
The second in a series of systematic studies by a celebrated mathematician I. M. Gelfand and colleagues, this volume presents students with a well-illustrated sequence of problems and exercises designed to illuminate the properties of functions and graphs. Since readers do not have the benefit of a blackboard on which a teacher constructs a graph, the authors abandoned the customary use of diagrams in which only the final form of the graph appears; instead, the book's margins feature step-by-step diagrams for the complete construction of each graph. The first part of the book employs simple fu
Energy Technology Data Exchange (ETDEWEB)
Lothian, Joshua [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Powers, Sarah S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sullivan, Blair D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Baker, Matthew B. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Schrock, Jonathan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Poole, Stephen W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2013-10-01
The benchmarking effort within the Extreme Scale Systems Center at Oak Ridge National Laboratory seeks to provide High Performance Computing benchmarks and test suites of interest to the DoD sponsor. The work described in this report is a part of the effort focusing on graph generation. A previously developed benchmark, SystemBurn, allowed the emulation of different application behavior profiles within a single framework. To complement this effort, similar capabilities are desired for graph-centric problems. This report examines existing synthetic graph generator implementations in preparation for further study on the properties of their generated synthetic graphs.
A scalable community detection algorithm for large graphs using stochastic block models
Peng, Chengbin
2017-11-24
Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of
Characterisations of Intersection Graphs by Vertex Orderings
Wood, David R.
2004-01-01
Characterisations of interval graphs, comparability graphs, co-comparability graphs, permutation graphs, and split graphs in terms of linear orderings of the vertex set are presented. As an application, it is proved that interval graphs, co-comparability graphs, AT-free graphs, and split graphs have bandwidth bounded by their maximum degree.
Identification of Inhibitors of Biological Interactions Involving Intrinsically Disordered Proteins
Directory of Open Access Journals (Sweden)
Daniela Marasco
2015-04-01
Full Text Available Protein–protein interactions involving disordered partners have unique features and represent prominent targets in drug discovery processes. Intrinsically Disordered Proteins (IDPs are involved in cellular regulation, signaling and control: they bind to multiple partners and these high-specificity/low-affinity interactions play crucial roles in many human diseases. Disordered regions, terminal tails and flexible linkers are particularly abundant in DNA-binding proteins and play crucial roles in the affinity and specificity of DNA recognizing processes. Protein complexes involving IDPs are short-lived and typically involve short amino acid stretches bearing few “hot spots”, thus the identification of molecules able to modulate them can produce important lead compounds: in this scenario peptides and/or peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. Here, we propose a panoramic review of the structural features of IDPs and how they regulate molecular recognition mechanisms focusing attention on recently reported drug-design strategies in the field of IDPs.
Spectral clustering and biclustering learning large graphs and contingency tables
Bolla, Marianna
2013-01-01
Explores regular structures in graphs and contingency tables by spectral theory and statistical methods This book bridges the gap between graph theory and statistics by giving answers to the demanding questions which arise when statisticians are confronted with large weighted graphs or rectangular arrays. Classical and modern statistical methods applicable to biological, social, communication networks, or microarrays are presented together with the theoretical background and proofs. This book is suitable for a one-semester course for graduate students in data mining, mult
Directory of Open Access Journals (Sweden)
A. Assari
2016-01-01
Full Text Available In this paper, a graph is assigned to any probability measure on the σ-algebra of Borel sets of a topological space. Using this construction, it is proved that given any number n (finite or infinite there exists a nonregular graph such that its clique, chromatic, and dominating number equals n.
De Jong, Marvin L.
1993-01-01
Describes the powerful graphing ability of computer algebra systems (CAS) to create three-dimensional graphs or surface graphics of electric potentials. Provides equations along with examples of the printouts. Lists the programs Mathematica, Maple, Derive, Theorist, MathCad, and MATLAB as promising CAS systems. (MVL)
de Mol, M.J.; Rensink, Arend; Hunt, James J.
This paper introduces an approach for adding graph transformation-based functionality to existing JAVA programs. The approach relies on a set of annotations to identify the intended graph structure, as well as on user methods to manipulate that structure, within the user’s own JAVA class
Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM
1999-01-01
Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems
Joyner, W David
2017-01-01
This textbook acts as a pathway to higher mathematics by seeking and illuminating the connections between graph theory and diverse fields of mathematics, such as calculus on manifolds, group theory, algebraic curves, Fourier analysis, cryptography and other areas of combinatorics. An overview of graph theory definitions and polynomial invariants for graphs prepares the reader for the subsequent dive into the applications of graph theory. To pique the reader’s interest in areas of possible exploration, recent results in mathematics appear throughout the book, accompanied with examples of related graphs, how they arise, and what their valuable uses are. The consequences of graph theory covered by the authors are complicated and far-reaching, so topics are always exhibited in a user-friendly manner with copious graphs, exercises, and Sage code for the computation of equations. Samples of the book’s source code can be found at github.com/springer-math/adventures-in-graph-theory. The text is geared towards ad...
Packing Degenerate Graphs Greedily
Czech Academy of Sciences Publication Activity Database
Allen, P.; Böttcher, J.; Hladký, J.; Piguet, Diana
2017-01-01
Roč. 61, August (2017), s. 45-51 ISSN 1571-0653 R&D Projects: GA ČR GJ16-07822Y Institutional support: RVO:67985807 Keywords : tree packing conjecture * graph packing * graph processes Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics
DEFF Research Database (Denmark)
Husfeldt, Thore
2015-01-01
This chapter presents an introduction to graph colouring algorithms. The focus is on vertex-colouring algorithms that work for general classes of graphs with worst-case performance guarantees in a sequential model of computation. The presentation aims to demonstrate the breadth of available...
Moment graphs and representations
DEFF Research Database (Denmark)
Jantzen, Jens Carsten
2012-01-01
Moment graphs and sheaves on moment graphs are basically combinatorial objects that have be used to describe equivariant intersectiion cohomology. In these lectures we are going to show that they can be used to provide a direct link from this cohomology to the representation theory of simple Lie...
Directory of Open Access Journals (Sweden)
Behnaz Tolue
2018-07-01
Full Text Available In this paper we introduce stable subgroup graph associated to the group $G$. It is a graph with vertex set all subgroups of $G$ and two distinct subgroups $H_1$ and $H_2$ are adjacent if $St_{G}(H_1\\cap H_2\
Likhtenshtein, Gertz
2016-01-01
This book presents the versatile and pivotal role of electron spin interactions in nature. It provides the background, methodologies and tools for basic areas related to spin interactions, such as spin chemistry and biology, electron transfer, light energy conversion, photochemistry, radical reactions, magneto-chemistry and magneto-biology. The book also includes an overview of designing advanced magnetic materials, optical and spintronic devices and photo catalysts. This monograph appeals to scientists and graduate students working in the areas related to spin interactions physics, biophysics, chemistry and chemical engineering.
Generalized connectivity of graphs
Li, Xueliang
2016-01-01
Noteworthy results, proof techniques, open problems and conjectures in generalized (edge-) connectivity are discussed in this book. Both theoretical and practical analyses for generalized (edge-) connectivity of graphs are provided. Topics covered in this book include: generalized (edge-) connectivity of graph classes, algorithms, computational complexity, sharp bounds, Nordhaus-Gaddum-type results, maximum generalized local connectivity, extremal problems, random graphs, multigraphs, relations with the Steiner tree packing problem and generalizations of connectivity. This book enables graduate students to understand and master a segment of graph theory and combinatorial optimization. Researchers in graph theory, combinatorics, combinatorial optimization, probability, computer science, discrete algorithms, complexity analysis, network design, and the information transferring models will find this book useful in their studies.
Product of Locally Primitive Graphs
Directory of Open Access Journals (Sweden)
Amir Assari
2014-01-01
Full Text Available Many large graphs can be constructed from existing smaller graphs by using graph operations, such as the product of two graphs. Many properties of such large graphs are closely related to those of the corresponding smaller ones. In this paper we consider the product of two locally primitive graphs and prove that only tensor product of them will also be locally primitive.
Graph Abstraction and Abstract Graph Transformation
Boneva, I.B.; Rensink, Arend; Kurban, M.E.; Bauer, J.
2007-01-01
Many important systems like concurrent heap-manipulating programs, communication networks, or distributed algorithms are hard to verify due to their inherent dynamics and unboundedness. Graphs are an intuitive representation of states of these systems, where transitions can be conveniently described
Hyperfine interaction measurements in biological compounds: the case of hydroxyapatite
International Nuclear Information System (INIS)
Leite Neto, Osmar Flavio da Silveira
2014-01-01
The use o nanoparticles in current medicine are under intense investigation. The possible advantages proposed by these systems are very impressive and the results may be quite schemer. In this scenario, the association of nanoparticles with radioactive materials (radionuclide) may be the most important step since the discovery of radioactive for nuclear medicine and radiopharmacy, especially for cancer targeting and therapy. The hyperfine interaction of the nuclear probe 111 Cd in the Hydroxyapatite compounds has been investigated by perturbed angular correlation (PAC) spectroscopy in room temperature for the hydroxyapatite made in the temperatures of 90°C, 35°C and with Ho doped, both thermalized and not. The thermalized samples were heated to T= 1273 K for 6 h. The 111 Cd was broadcast in the structure of the material by diffusion, closing in quartz tubes were heated – together with the radioactive PAC probe 111 In/ 111 Cd to T = 1073 K for 12 h. In not thermalized samples the PAC spectra indicate a distribution of frequency, but in the thermalized samples, the PAC spectra shows the presence of β-tri calcium phosphate in the structure of this kind of Hydroxyapatite. (author)
Topology of molecular interaction networks
Winterbach, W.; Van Mieghem, P.; Reinders, M.; Wang, H.; De Ridder, D.
2013-01-01
Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over
Subgraph detection using graph signals
Chepuri, Sundeep Prabhakar
2017-03-06
In this paper we develop statistical detection theory for graph signals. In particular, given two graphs, namely, a background graph that represents an usual activity and an alternative graph that represents some unusual activity, we are interested in answering the following question: To which of the two graphs does the observed graph signal fit the best? To begin with, we assume both the graphs are known, and derive an optimal Neyman-Pearson detector. Next, we derive a suboptimal detector for the case when the alternative graph is not known. The developed theory is illustrated with numerical experiments.
Biological activities and DNA interactions of Amanita ovoidea.
Doğan, Hasan Hüseyin; Arslan, Emine
2015-01-01
Amanita ovoidea (Bull.) Link (Amanitaceae) is a well-known species due to its pleasant aroma and flavor since ancient times in the worldwide. This species is also known in Turkey and people consume it extensively. To evaluate medicinal importance of A. ovoidea for human health, to explain the effect of mushroom extracts on bacterial DNA, and to find preventive role on bacterial disease. Chloroform, acetone, and methanol extracts of A. ovoidea were tested for the antimicrobial activities against four Gram-positive bacteria, five Gram-negative bacteria, and yeast using a micro-dilution method. In addition, DNA binding, DNA cleavage activity, and restriction enzyme digestion of the methanol extract of A. ovoidea were examined at different concentrations (40.000-78.125 µg/mL). The highest minimum inhibitory concentration (MIC) value observed against the test micro-organisms was with the chloroform extract (MIC 19.5 µg/mL concentration) against Candida albicans. Other highest antimicrobial effects observed against the test micro-organisms were with the methanol extracts against Bacillus subtilis, Staphylococcus aureus, Listeria monocytogenes, Streptococcus pyogenes, Candida albicans, Klebsiella pneumoniae, Proteus vulgaris, and Salmonella enteritidis (MICs, 78 µg/mL concentrations). All concentrations reduced the mobility of plasmid DNA. BamHI and HindIII targeted specially to supercoils and cut them. Amanita ovoidea extract prevented cutting with HindIII by binding especially to the AA region in open circular DNA. Present results demonstrated that A. ovoidea has excellent antimicrobial and antifungal activities by its DNA interaction activity on pBR322.
Darabos, Christian; Qiu, Jingya; Moore, Jason H
2016-01-01
Complex diseases are the result of intricate interactions between genetic, epigenetic and environmental factors. In previous studies, we used epidemiological and genetic data linking environmental exposure or genetic variants to phenotypic disease to construct Human Phenotype Networks and separately analyze the effects of both environment and genetic factors on disease interactions. To better capture the intricacies of the interactions between environmental exposure and the biological pathways in complex disorders, we integrate both aspects into a single "tripartite" network. Despite extensive research, the mechanisms by which chemical agents disrupt biological pathways are still poorly understood. In this study, we use our integrated network model to identify specific biological pathway candidates possibly disrupted by environmental agents. We conjecture that a higher number of co-occurrences between an environmental substance and biological pathway pair can be associated with a higher likelihood that the substance is involved in disrupting that pathway. We validate our model by demonstrating its ability to detect known arsenic and signal transduction pathway interactions and speculate on candidate cell-cell junction organization pathways disrupted by cadmium. The validation was supported by distinct publications of cell biology and genetic studies that associated environmental exposure to pathway disruption. The integrated network approach is a novel method for detecting the biological effects of environmental exposures. A better understanding of the molecular processes associated with specific environmental exposures will help in developing targeted molecular therapies for patients who have been exposed to the toxicity of environmental chemicals.
Graph-based unsupervised feature selection and multiview ...
Indian Academy of Sciences (India)
Home; Journals; Journal of Biosciences; Volume 40; Issue 4. Graph-based unsupervised feature selection and multiview clustering for microarray data. Tripti Swarnkar Pabitra Mitra ... Keywords. Biological functional enrichment; clustering; explorative data analysis; feature selection; gene selection; graph-based learning.
Graph-based unsupervised feature selection and multiview ...
Indian Academy of Sciences (India)
2015-09-28
Sep 28, 2015 ... Biological functional enrichment; clustering; explorative data analysis; feature selection; gene selection; graph-based learning. Published online: 28 September ...... RFGS: random forest gene selection; SVST: Support vector sampling technique; SOM: Self-organizing map; GUFS: proposed graph-based.
Recent developments in systems biology and metabolic engineering of plant microbe interactions
Directory of Open Access Journals (Sweden)
Vishal Kumar
2016-09-01
Full Text Available Microorganisms play a crucial role in the sustainability of the various ecosystems. The characterization of various interactions between microorganisms and other biotic factors is a necessary footstep to understand the association and functions of microbial communities. Among the different microbial interactions in an ecosystem, plant-microbe interaction plays an important role to balance the ecosystem. The present review explores plant microbe interactions using gene editing and system biology tools towards the comprehension in improvement of plant traits. Further, system biology tools like FBA, OptKnock and constrain based modeling helps in understanding such interactions as a whole. In addition, various gene editing tools have been summarized and a strategy has been hypothesized for the development of disease free plants. Furthermore, we have tried to summarize the predictions through data retrieved from various types of sources such as high throughput sequencing data (e.g. single nucleotide polymorphism (SNP detection, RNA-seq, proteomics and metabolic models have been reconstructed from such sequences for species communities. It is well known fact that systems biology approaches and modeling of biological networks will enable us to learn the insight of such network and will also help further in understanding these interactions.
Hage, David S
2017-06-01
The interactions between biochemical and chemical agents in the body are important in many clinical processes. Affinity chromatography and high-performance affinity chromatography (HPAC), in which a column contains an immobilized biologically related binding agent, are 2 methods that can be used to study these interactions. This review presents various approaches that can be used in affinity chromatography and HPAC to characterize the strength or rate of a biological interaction, the number and types of sites that are involved in this process, and the interactions between multiple solutes for the same binding agent. A number of applications for these methods are examined, with an emphasis on recent developments and high-performance affinity methods. These applications include the use of these techniques for fundamental studies of biological interactions, high-throughput screening of drugs, work with modified proteins, tools for personalized medicine, and studies of drug-drug competition for a common binding agent. The wide range of formats and detection methods that can be used with affinity chromatography and HPAC for examining biological interactions makes these tools attractive for various clinical and pharmaceutical applications. Future directions in the development of small-scale columns and the coupling of these methods with other techniques, such as mass spectrometry or other separation methods, should continue to increase the flexibility and ease with which these approaches can be used in work involving clinical or pharmaceutical samples. © 2016 American Association for Clinical Chemistry.
Bollobas, Bela
2004-01-01
The ever-expanding field of extremal graph theory encompasses a diverse array of problem-solving methods, including applications to economics, computer science, and optimization theory. This volume, based on a series of lectures delivered to graduate students at the University of Cambridge, presents a concise yet comprehensive treatment of extremal graph theory.Unlike most graph theory treatises, this text features complete proofs for almost all of its results. Further insights into theory are provided by the numerous exercises of varying degrees of difficulty that accompany each chapter. A
Advances on plant-pathogen interactions from molecular toward systems biology perspectives.
Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique
2017-05-01
In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.
Effects of Interactions between ZnO Nanoparticles and Saccharides on Biological Responses
Directory of Open Access Journals (Sweden)
Mi-Ran Go
2018-02-01
Full Text Available Zinc oxide (ZnO nanoparticles (NPs are widely used as a Zn supplement, because Zn plays a role in many cellular and immune functions but public concern about their potentially undesirable effects on the human body is growing. When NPs are added in food matrices, interactions between NPs and food components occur, which can affect biological systems. In this study, interactions between ZnO NPs and saccharides were investigated by measuring changes in hydrodynamic radius, zeta potential and solubility and by quantifying amounts of adsorbed saccharides on NPs; acacia honey, sugar mixtures (containing equivalent amounts of fructose, glucose, sucrose and maltose and monosaccharide solutions were used as model compounds. Biological responses of NPs dispersed in different saccharides were also evaluated in human intestinal cells and rats in terms of cytotoxicity, cellular uptake, intestinal transport and oral absorption. The results demonstrate that the hydrodynamic radii and zeta potentials of NPs were highly affected by saccharides. In addition, trace nutrients influenced NP/saccharide interactions and interactive effects between saccharides on the interactions were found. NPs in all saccharides increased inhibition of cell proliferation and enhanced cellular uptake. Oral absorption of NPs was highly enhanced by 5% glucose, which is in-line with intestinal transport result. These findings show that ZnO NPs interact with saccharides and these interactions affects biological responses.
Decomposing Oriented Graphs into Six Locally Irregular Oriented Graphs
DEFF Research Database (Denmark)
Bensmail, Julien; Renault, Gabriel
2016-01-01
An undirected graph G is locally irregular if every two of its adjacent vertices have distinct degrees. We say that G is decomposable into k locally irregular graphs if there exists a partition E1∪E2∪⋯∪Ek of the edge set E(G) such that each Ei induces a locally irregular graph. It was recently...... conjectured by Baudon et al. that every undirected graph admits a decomposition into at most three locally irregular graphs, except for a well-characterized set of indecomposable graphs. We herein consider an oriented version of this conjecture. Namely, can every oriented graph be decomposed into at most...... three locally irregular oriented graphs, i.e. whose adjacent vertices have distinct outdegrees? We start by supporting this conjecture by verifying it for several classes of oriented graphs. We then prove a weaker version of this conjecture. Namely, we prove that every oriented graph can be decomposed...
The biological context of HIV-1 host interactions reveals subtle insights into a system hijack
Directory of Open Access Journals (Sweden)
Pinney John W
2010-06-01
Full Text Available Abstract Background In order to replicate, HIV, like all viruses, needs to invade a host cell and hijack it for its own use, a process that involves multiple protein interactions between virus and host. The HIV-1, Human Protein Interaction Database available at NCBI's website captures this information from the primary literature, containing over 2,500 unique interactions. We investigate the general properties and biological context of these interactions and, thus, explore the molecular specificity of the HIV-host perturbation. In particular, we investigate (i whether HIV preferentially interacts with highly connected and 'central' proteins, (ii known phenotypic properties of host proteins inferred from essentiality and disease-association data, and (iii biological context (molecular function, processes and location of the host proteins to identify attributes most strongly associated with specific HIV interactions. Results After correcting for ascertainment bias in the literature, we demonstrate a significantly greater propensity for HIV to interact with highly connected and central host proteins. Unexpectedly, we find there are no associations between HIV interaction and inferred essentiality. Similarly, we find a tendency for HIV not to interact with proteins encoded by genes associated with disease. Crucially, we find that functional categories over-represented in HIV-host interactions are innately enriched for highly connected and central proteins in the host system. Conclusions Our results imply that HIV's propensity to interact with highly connected and central proteins is a consequence of interactions with particular cellular functions, rather than being a direct effect of network topological properties. The lack of a propensity for interactions with phenotypically essential proteins suggests a selective pressure to minimise virulence in retroviral evolution. Thus, the specificity of HIV-host interactions is complex, and only superficially
Alspach, BR
1985-01-01
This volume deals with a variety of problems involving cycles in graphs and circuits in digraphs. Leading researchers in this area present here 3 survey papers and 42 papers containing new results. There is also a collection of unsolved problems.
Learning Probabilistic Decision Graphs
DEFF Research Database (Denmark)
Jaeger, Manfred; Dalgaard, Jens; Silander, Tomi
2004-01-01
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence relations that cannot be captured in a Bayesian network structure, and can sometimes provide computationally more...
Wilson, Robin J
1985-01-01
Graph Theory has recently emerged as a subject in its own right, as well as being an important mathematical tool in such diverse subjects as operational research, chemistry, sociology and genetics. This book provides a comprehensive introduction to the subject.
Efficiently Controllable Graphs.
Gokler, Can; Lloyd, Seth; Shor, Peter; Thompson, Kevin
2017-06-30
We investigate graphs that can be disconnected into small components by removing a vanishingly small fraction of their vertices. We show that, when a controllable quantum network is described by such a graph and the gaps in eigenfrequencies and in transition frequencies are bounded exponentially in the number of vertices, the network is efficiently controllable, in the sense that universal quantum computation can be performed using a control sequence polynomial in the size of the network while controlling a vanishingly small fraction of subsystems. We show that networks corresponding to finite-dimensional lattices are efficiently controllable and explore generalizations to percolation clusters and random graphs. We show that the classical computational complexity of estimating the ground state of Hamiltonians described by controllable graphs is polynomial in the number of subsystems or qubits.
GraphCrunch 2: Software tool for network modeling, alignment and clustering
Directory of Open Access Journals (Sweden)
Hayes Wayne
2011-01-01
Full Text Available Abstract Background Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. Results We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL" for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other
DEFF Research Database (Denmark)
Bakhshesh, Davood; Barba, Luis; Bose, Prosenjit
2018-01-01
In this paper, we introduce a variation of the well-studied Yao graphs. Given a set of points S⊂R2 and an angle 0Yao graph cY(θ) with vertex set S and angle θ as follows. For each p,q∈S, we add an edge from p to q in cY(θ) if there exists a cone with apex p...
Uniform Single Valued Neutrosophic Graphs
Directory of Open Access Journals (Sweden)
S. Broumi
2017-09-01
Full Text Available In this paper, we propose a new concept named the uniform single valued neutrosophic graph. An illustrative example and some properties are examined. Next, we develop an algorithmic approach for computing the complement of the single valued neutrosophic graph. A numerical example is demonstrated for computing the complement of single valued neutrosophic graphs and uniform single valued neutrosophic graph.
Rashmanlou, Hossein; Samanta, Sovan; Pal, Madhumangal; Borzooei, R A
2016-01-01
The main purpose of this paper is to introduce the notion of vague h-morphism on vague graphs and regular vague graphs. The action of vague h-morphism on vague strong regular graphs are studied. Some elegant results on weak and co weak isomorphism are derived. Also, [Formula: see text]-complement of highly irregular vague graphs are defined.
Categorical constructions in graph theory
Directory of Open Access Journals (Sweden)
Richard T. Bumby
1986-01-01
Full Text Available This paper presents some graph-theoretic questions from the viewpoint of the portion of category theory which has become common knowledge. In particular, the reader is encouraged to consider whether there is only one natural category of graphs and how theories of directed graphs and undirected graphs are related.
Probabilistic Graph Layout for Uncertain Network Visualization.
Schulz, Christoph; Nocaj, Arlind; Goertler, Jochen; Deussen, Oliver; Brandes, Ulrik; Weiskopf, Daniel
2017-01-01
We present a novel uncertain network visualization technique based on node-link diagrams. Nodes expand spatially in our probabilistic graph layout, depending on the underlying probability distributions of edges. The visualization is created by computing a two-dimensional graph embedding that combines samples from the probabilistic graph. A Monte Carlo process is used to decompose a probabilistic graph into its possible instances and to continue with our graph layout technique. Splatting and edge bundling are used to visualize point clouds and network topology. The results provide insights into probability distributions for the entire network-not only for individual nodes and edges. We validate our approach using three data sets that represent a wide range of network types: synthetic data, protein-protein interactions from the STRING database, and travel times extracted from Google Maps. Our approach reveals general limitations of the force-directed layout and allows the user to recognize that some nodes of the graph are at a specific position just by chance.
Commuting projections on graphs
Energy Technology Data Exchange (ETDEWEB)
Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Zikatanov, Ludmil T. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Mathematics
2013-02-19
For a given (connected) graph, we consider vector spaces of (discrete) functions defined on its vertices and its edges. These two spaces are related by a discrete gradient operator, Grad and its adjoint, ₋Div, referred to as (negative) discrete divergence. We also consider a coarse graph obtained by aggregation of vertices of the original one. Then a coarse vertex space is identified with the subspace of piecewise constant functions over the aggregates. We consider the ℓ_{2}-projection Q_{H} onto the space of these piecewise constants. In the present paper, our main result is the construction of a projection π _{H} from the original edge-space onto a properly constructed coarse edge-space associated with the edges of the coarse graph. The projections π _{H} and Q_{H} commute with the discrete divergence operator, i.e., we have div π _{H} = Q_{H} div. The respective pair of coarse edge-space and coarse vertexspace offer the potential to construct two-level, and by recursion, multilevel methods for the mixed formulation of the graph Laplacian which utilizes the discrete divergence operator. The performance of one two-level method with overlapping Schwarz smoothing and correction based on the constructed coarse spaces for solving such mixed graph Laplacian systems is illustrated on a number of graph examples.
Bollobás, Béla
1998-01-01
The time has now come when graph theory should be part of the education of every serious student of mathematics and computer science, both for its own sake and to enhance the appreciation of mathematics as a whole. This book is an in-depth account of graph theory, written with such a student in mind; it reflects the current state of the subject and emphasizes connections with other branches of pure mathematics. The volume grew out of the author's earlier book, Graph Theory -- An Introductory Course, but its length is well over twice that of its predecessor, allowing it to reveal many exciting new developments in the subject. Recognizing that graph theory is one of several courses competing for the attention of a student, the book contains extensive descriptive passages designed to convey the flavor of the subject and to arouse interest. In addition to a modern treatment of the classical areas of graph theory such as coloring, matching, extremal theory, and algebraic graph theory, the book presents a detailed ...
Hierarchy of graph matchbox manifolds
Lukina, Olga
2011-01-01
We study a class of graph foliated spaces, or graph matchbox manifolds, initially constructed by Kenyon and Ghys. For graph foliated spaces we introduce a quantifier of dynamical complexity which we call its level. We develop the fusion construction, which allows us to associate to every two graph foliated spaces a third one which contains the former two in its closure. Although the underlying idea of the fusion is simple, it gives us a powerful tool to study graph foliated spaces. Using fusi...
Linear representation of a graph
Directory of Open Access Journals (Sweden)
Eduardo Montenegro
2019-10-01
Full Text Available In this paper the linear representation of a graph is defined. A linear representation of a graph is a subgroup of $GL(p,\\mathbb{R}$, the group of invertible matrices of order $ p $ and real coefficients. It will be demonstrated that every graph admits a linear representation. In this paper, simple and finite graphs will be used, framed in the graphs theory's area
Low-level radiation: biological interactions, risks, and benefits. A bibliography
International Nuclear Information System (INIS)
1978-09-01
The bibliography contains 3294 references that were selected from the Department of Energy's data base (EDB). The subjects covered are lower-level radiation effects on man, environmental radiation, and other biological interactions of radiation that appear to be applicable to the low-level radiation problem
Domínguez, Moralba; Cortes-Figueroa, Jose´ E.; Meléndez, Enrique
2018-01-01
Bioinorganic topics are ubiquitous in the inorganic chemistry curriculum; however, experiments to enhance understanding of related topics are scarce. In this proposed laboratory, upper undergraduate students assess the biological interaction of molybdenocene dichloride (Cp2MoCl2) with bovine serum albumin (BSA) by fluorescence spectroscopy.…
Low-level radiation: biological interactions, risks, and benefits. A bibliography
Energy Technology Data Exchange (ETDEWEB)
None
1978-09-01
The bibliography contains 3294 references that were selected from the Department of Energy's data base (EDB). The subjects covered are lower-level radiation effects on man, environmental radiation, and other biological interactions of radiation that appear to be applicable to the low-level radiation problem.
On the mechanisms of interaction of low-intensity millimeter waves with biological objects
Energy Technology Data Exchange (ETDEWEB)
Betskii, O.V.
1994-07-01
The interaction of low-intensity millimeter-band electromagnetic waves with biological objects is examined. These waves are widely used in medical practice as a means of physiotherapy for the treatment of various human disorders. Principal attention is given to the mechanisms through which millimeter waves act on the human organism.
Floral biology and the effects of plant-pollinator interaction on ...
African Journals Online (AJOL)
oyelana
2012-10-18
Oct 18, 2012 ... 1Department of Biological Sciences, College of Natural Sciences, Redeemer's University, Mowe, Ogun State, Nigeria. 2Department of Biosciences and ... breeding systems, seed production, and the degree of mutual interdependence ... Despite the potentials for mutual benefits, plant- pollinator interactions ...
Chen, Ran; Riviere, Jim E
2017-05-01
The understanding of nano-bio interactions is deemed essential in the design, application, and safe handling of nanomaterials. Proper characterization of the intrinsic physicochemical properties, including their size, surface charge, shape, and functionalization, is needed to consider the fate or impact of nanomaterials in biological and environmental systems. The characterizations of their interactions with surrounding chemical species are often hindered by the complexity of biological or environmental systems, and the drastically different surface physicochemical properties among a large population of nanomaterials. The complexity of these interactions is also due to the diverse ligands of different chemical properties present in most biomacromolecules, and multiple conformations they can assume at different conditions to minimize their conformational free energy. Often these interactions are collectively determined by multiple physical or chemical forces, including electrostatic forces, hydrogen bonding, and hydrophobic forces, and calls for multidimensional characterization strategies, both experimentally and computationally. Through these characterizations, the understanding of the roles surface physicochemical properties of nanomaterials and their surface interactions with biomacromolecules can play in their applications in biomedical and environmental fields can be obtained. To quantitatively decipher these physicochemical surface interactions, computational methods, including physical, statistical, and pharmacokinetic models, can be used for either analyses of large amounts of experimental characterization data, or theoretical prediction of the interactions, and consequent biological behavior in the body after administration. These computational methods include molecular dynamics simulation, structure-activity relationship models such as biological surface adsorption index, and physiologically-based pharmacokinetic models. WIREs Nanomed Nanobiotechnol 2017
On some interconnections between combinatorial optimization and extremal graph theory
Directory of Open Access Journals (Sweden)
Cvetković Dragoš M.
2004-01-01
Full Text Available The uniting feature of combinatorial optimization and extremal graph theory is that in both areas one should find extrema of a function defined in most cases on a finite set. While in combinatorial optimization the point is in developing efficient algorithms and heuristics for solving specified types of problems, the extremal graph theory deals with finding bounds for various graph invariants under some constraints and with constructing extremal graphs. We analyze by examples some interconnections and interactions of the two theories and propose some conclusions.
jsGraph and jsNMR—Advanced Scientific Charting
Directory of Open Access Journals (Sweden)
Norman Pellet
2014-09-01
Full Text Available The jsGraph library is a versatile javascript library that allows advanced charting to be rendered interactively in web browsers without relying on server-side image processing. jsGraph is released under the MIT license and is free of charge. While being highly customizable through an intuitive javascript API, jsGraph is optimized to render a large quantity of data in a short amount of time. jsGraphs can display line, scatter, contour or zone series. Examples can be consulted on the project home page [1]. Customization of the chart, its axis and its series is achieved through simple but comprehensive JSON configurations.
Interactions Between Biological Cells and Layered Double Hydroxides: Towards Functional Materials.
Forano, Claude; Bruna, Felipe; Mousty, Christine; Prevot, Vanessa
2018-03-08
This review highlights the current research on the interactions between biological cells and Layered Double Hydroxides (LDH). The as-prepared biohybrid materials appear extremely attractive in diverse fields of application relating to health care, environment and energy production. We describe how thanks to the main features of biological cells and LDH layers, various strategies of assemblies can be carried out for constructing smart biofunctional materials. The interactions between the two components are described with a peculiar attention to the adsorption, biocompatibilization, LDH layer internalization, antifouling and antimicrobial properties. The most significant achievements including authors' results, involving biological cells and LDH assemblies in waste water treatment, bioremediation and bioenergy generation are specifically addressed. © 2018 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Energies and physicochemical properties of cation-π interactions in biological structures.
Du, Qi-Shi; Meng, Jian-Zong; Liao, Si-Ming; Huang, Ri-Bo
2012-04-01
The cation-π interactions occur frequently within or between proteins due to six (Phe, Tyr, Trp, Arg, Lys, and His) of the twenty natural amino acids potentially interacting with metallic cations via these interactions. In this study, quantum chemical calculations and molecular orbital (MO) theory are used to study the energies and properties of cation-π interactions in biological structures. The cation-π interactions of H⁺ and Li⁺ are similar to hydrogen bonds and lithium bonds, respectively, in which the small, naked cations H⁺ and Li⁺ are buried deep within the π-electron density of aromatic molecules, forming stable cation-π bonds that are much stronger than the cation-π interactions of other alkali metal cations. The cation-π interactions of metallic cations with atomic masses greater than that of Li⁺ arise mainly from the coordinate bond comprising empty valence atomic orbitals (AOs) of metallic cations and π-MOs of aromatic molecules, though electrostatic interactions may also contribute to the cation-π interaction. The binding strength of cation-π interactions is determined by the charge and types of AOs in the metallic cations. Cation-π interaction energies are distance- and orientation-dependent; energies decrease with the distance (r) and the orientation angle (θ). In solution, the cation-π energies decrease with the increase of the dielectric constant (ɛ) of the solvent; however, solvation has less influence on the H⁺-π and H₃O⁺-π interactions than on interactions with other cations. The conclusions from this study provide useful theoretical insights into the nature of cation-π interactions and may contribute to the development of better force field parameters for describing the molecular dynamics of cation-π interactions within and between proteins. Copyright Â© 2011 Elsevier Inc. All rights reserved.
Decentralized formation of random regular graphs for robust multi-agent networks
Yazicioglu, A. Yasin
2014-12-15
Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs have significant impact on the robustness of networked systems. One family of robust graphs is the random regular graphs. In this paper, we present a locally applicable reconfiguration scheme to build random regular graphs through self-organization. For any connected initial graph, the proposed scheme maintains connectivity and the average degree while minimizing the degree differences and randomizing the links. As such, if the average degree of the initial graph is an integer, then connected regular graphs are realized uniformly at random as time goes to infinity.
GRAMI: Generalized Frequent Subgraph Mining in Large Graphs
El Saeedy, Mohammed El Sayed
2011-07-24
Mining frequent subgraphs is an important operation on graphs. Most existing work assumes a database of many small graphs, but modern applications, such as social networks, citation graphs or protein-protein interaction in bioinformatics, are modeled as a single large graph. Interesting interactions in such applications may be transitive (e.g., friend of a friend). Existing methods, however, search for frequent isomorphic (i.e., exact match) subgraphs and cannot discover many useful patterns. In this paper we propose GRAMI, a framework that generalizes frequent subgraph mining in a large single graph. GRAMI discovers frequent patterns. A pattern is a graph where edges are generalized to distance-constrained paths. Depending on the definition of the distance function, many instantiations of the framework are possible. Both directed and undirected graphs, as well as multiple labels per vertex, are supported. We developed an efficient implementation of the framework that models the frequency resolution phase as a constraint satisfaction problem, in order to avoid the costly enumeration of all instances of each pattern in the graph. We also implemented CGRAMI, a version that supports structural and semantic constraints; and AGRAMI, an approximate version that supports very large graphs. Our experiments on real data demonstrate that our framework is up to 3 orders of magnitude faster and discovers more interesting patterns than existing approaches.
Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.
Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh
2017-07-03
Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.
Li, Dongdong; Ma, Yinchu; Du, Jinzhi; Tao, Wei; Du, Xiaojiao; Yang, Xianzhu; Wang, Jun
2017-05-10
Precisely controlling the interaction of nanoparticles with biological systems (nanobio interactions) from the injection site to biological targets shows great potential for biomedical applications. Inspired by the ability of nanoparticles to alter their physicochemical properties according to different stimuli, we explored the tumor acidity and near-infrared (NIR) light activated transformable nanoparticle DA TAT-NP IR&DOX . This nanoparticle consists of a tumor acidity-activated TAT [the TAT lysine residues' amines was modified with 2,3-dimethylmaleic anhydride (DA)], a flexible chain polyphosphoester core coencapsulated a NIR dye IR-780, and DOX (doxorubicin). The physicochemical properties of the nanoparticle can be controlled in a stepwise fashion using tumor acidity and NIR light, resulting in adjustable nanobio interactions. The resulting transformable nanoparticle DA TAT-NP IR&DOX efficiently avoids the interaction with mononuclear phagocyte system (MPS) ("stealth" state) due to the masking of the TAT peptide during blood circulation. Once it has accumulated in the tumor tissues, DA TAT-NP IR&DOX is reactivated by tumor acidity and transformed into the "recognize" state in order to promote interaction with tumor cells and enhance cellular internalization. Then, this nanoparticle is transformed into "attack" state under NIR irradiation, achieving the supersensitive DOX release from the flexible chain polyphosphoester core in order to increase the DOX-DNA interaction. This concept provides new avenues for the creation of transformable drug delivery systems that have the ability to control nanobio interactions.
Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping
2013-04-01
Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.
Biophysics of DNA-Protein Interactions From Single Molecules to Biological Systems
Williams, Mark C
2011-01-01
This book presents a concise overview of current research on the biophysics of DNA-protein interactions. A wide range of new and classical methods are presented by authors investigating physical mechanisms by which proteins interact with DNA. For example, several chapters address the mechanisms by which proteins search for and recognize specific binding sites on DNA, a process critical for cellular function. Single molecule methods such as force spectroscopy as well as fluorescence imaging and tracking are described in these chapters as well as other parts of the book that address the dynamics of protein-DNA interactions. Other important topics include the mechanisms by which proteins engage DNA sequences and/or alter DNA structure. These simple but important model interactions are then placed in the broader biological context with discussion of larger protein-DNA complexes . Topics include replication forks, recombination complexes, DNA repair interactions, and ultimately, methods to understand the chromatin...
Hierarchical graphs for rule-based modeling of biochemical systems
Directory of Open Access Journals (Sweden)
Hu Bin
2011-02-01
Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for
Hierarchical graphs for rule-based modeling of biochemical systems.
Lemons, Nathan W; Hu, Bin; Hlavacek, William S
2011-02-02
In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal) of an edge represents a class of association (dissociation) reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR) complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for specifying rule-based models, such as the BioNetGen language
The STAPL Parallel Graph Library
Harshvardhan,
2013-01-01
This paper describes the stapl Parallel Graph Library, a high-level framework that abstracts the user from data-distribution and parallelism details and allows them to concentrate on parallel graph algorithm development. It includes a customizable distributed graph container and a collection of commonly used parallel graph algorithms. The library introduces pGraph pViews that separate algorithm design from the container implementation. It supports three graph processing algorithmic paradigms, level-synchronous, asynchronous and coarse-grained, and provides common graph algorithms based on them. Experimental results demonstrate improved scalability in performance and data size over existing graph libraries on more than 16,000 cores and on internet-scale graphs containing over 16 billion vertices and 250 billion edges. © Springer-Verlag Berlin Heidelberg 2013.
Fundamentals of algebraic graph transformation
Ehrig, Hartmut; Prange, Ulrike; Taentzer, Gabriele
2006-01-01
Graphs are widely used to represent structural information in the form of objects and connections between them. Graph transformation is the rule-based manipulation of graphs, an increasingly important concept in computer science and related fields. This is the first textbook treatment of the algebraic approach to graph transformation, based on algebraic structures and category theory. Part I is an introduction to the classical case of graph and typed graph transformation. In Part II basic and advanced results are first shown for an abstract form of replacement systems, so-called adhesive high-level replacement systems based on category theory, and are then instantiated to several forms of graph and Petri net transformation systems. Part III develops typed attributed graph transformation, a technique of key relevance in the modeling of visual languages and in model transformation. Part IV contains a practical case study on model transformation and a presentation of the AGG (attributed graph grammar) tool envir...
GOGrapher: A Python library for GO graph representation and analysis.
Muller, Brian; Richards, Adam J; Jin, Bo; Lu, Xinghua
2009-07-07
The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve.
GOGrapher: A Python library for GO graph representation and analysis
Directory of Open Access Journals (Sweden)
Lu Xinghua
2009-07-01
Full Text Available Abstract Background The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. Findings An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. Conclusion The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve.
Quantitative graph theory mathematical foundations and applications
Dehmer, Matthias
2014-01-01
The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical techniques, this book covers a wide range of quantitative-graph theoretical concepts and methods, including those pertaining to real and random graphs such as:Comparative approaches (graph similarity or distance)Graph measures to characterize graphs quantitat
Two Particles on a Star Graph, II
Czech Academy of Sciences Publication Activity Database
Harmer, Mark
2008-01-01
Roč. 15, č. 4 (2008), s. 473-480 ISSN 1061-9208 R&D Projects: GA MŠk(CZ) LC06002 Institutional research plan: CEZ:AV0Z10480505 Keywords : star graph * delta function interaction Subject RIV: BE - Theoretical Physics Impact factor: 0.944, year: 2008
Energy Technology Data Exchange (ETDEWEB)
Tenforde, T.S.
1992-05-01
Interest in the mechanisms of interaction and the biological effects of static magnetic fields has increased significantly during the past two decades as a result of the growing number of applications of these fields in research, industry and medicine. A major stimulus for research on the bioeffects of static magnetic fields has been the effort to develop new technologies for energy production and storage that utilize intense magnetic fields (e.g., thermonuclear fusion reactors and superconducting magnet energy storage devices). Interest in the possible biological interactions and health effects of static magnetic fields has also been increased as a result of recent developments in magnetic levitation as a mode of public transportation. In addition, the rapid emergence of magnetic resonance imaging as a new clinical diagnostic procedure has, in recent years, provided a strong rationale for defining the possible biological effects of magnetic fields with high flux densities. In this review, the principal interaction mechanisms of static magnetic fields will be described, and a summary will be given of the present state of knowledge of the biological, environmental, and human health effects of these fields.
Extracting Gene Networks for Low-Dose Radiation Using Graph Theoretical Algorithms
Energy Technology Data Exchange (ETDEWEB)
Voy, Brynn H [ORNL; Scharff, Jon [University of Tennessee, Knoxville (UTK); Perkins, Andy [University of Tennessee, Knoxville (UTK); Saxton, Arnold [University of Tennessee, Knoxville (UTK); Borate, Bhavesh [University of Tennessee, Knoxville (UTK); Chesler, Elissa J [ORNL; Branstetter, Lisa R [ORNL; Langston, Michael A [University of Tennessee, Knoxville (UTK)
2006-01-01
Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., ''guilt-by-association''). We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.
Extracting gene networks for low-dose radiation using graph theoretical algorithms.
Directory of Open Access Journals (Sweden)
Brynn H Voy
2006-07-01
Full Text Available Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., "guilt-by-association". We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.
Ribes, Luis
2017-01-01
This book offers a detailed introduction to graph theoretic methods in profinite groups and applications to abstract groups. It is the first to provide a comprehensive treatment of the subject. The author begins by carefully developing relevant notions in topology, profinite groups and homology, including free products of profinite groups, cohomological methods in profinite groups, and fixed points of automorphisms of free pro-p groups. The final part of the book is dedicated to applications of the profinite theory to abstract groups, with sections on finitely generated subgroups of free groups, separability conditions in free and amalgamated products, and algorithms in free groups and finite monoids. Profinite Graphs and Groups will appeal to students and researchers interested in profinite groups, geometric group theory, graphs and connections with the theory of formal languages. A complete reference on the subject, the book includes historical and bibliographical notes as well as a discussion of open quest...
White, AT
1985-01-01
The field of topological graph theory has expanded greatly in the ten years since the first edition of this book appeared. The original nine chapters of this classic work have therefore been revised and updated. Six new chapters have been added, dealing with: voltage graphs, non-orientable imbeddings, block designs associated with graph imbeddings, hypergraph imbeddings, map automorphism groups and change ringing.Thirty-two new problems have been added to this new edition, so that there are now 181 in all; 22 of these have been designated as ``difficult'''' and 9 as ``unsolved''''. Three of the four unsolved problems from the first edition have been solved in the ten years between editions; they are now marked as ``difficult''''.
Graph theory and interconnection networks
Hsu, Lih-Hsing
2008-01-01
The advancement of large scale integrated circuit technology has enabled the construction of complex interconnection networks. Graph theory provides a fundamental tool for designing and analyzing such networks. Graph Theory and Interconnection Networks provides a thorough understanding of these interrelated topics. After a brief introduction to graph terminology, the book presents well-known interconnection networks as examples of graphs, followed by in-depth coverage of Hamiltonian graphs. Different types of problems illustrate the wide range of available methods for solving such problems. The text also explores recent progress on the diagnosability of graphs under various models.
Kaltashov, Igor A; Desiderio, Dominic M; Nibbering, Nico M
2012-01-01
The definitive guide to mass spectrometry techniques in biology and biophysics The use of mass spectrometry (MS) to study the architecture and dynamics of proteins is increasingly common within the biophysical community, and Mass Spectrometry in Structural Biology and Biophysics: Architecture, Dynamics, and Interaction of Biomolecules, Second Edition provides readers with detailed, systematic coverage of the current state of the art. Offering an unrivalled overview of modern MS-based armamentarium that can be used to solve the most challenging problems in biophysics, structural biol
Endomorphisms of graph algebras
DEFF Research Database (Denmark)
Conti, Roberto; Hong, Jeong Hee; Szymanski, Wojciech
2012-01-01
We initiate a systematic investigation of endomorphisms of graph C*-algebras C*(E), extending several known results on endomorphisms of the Cuntz algebras O_n. Most but not all of this study is focused on endomorphisms which permute the vertex projections and globally preserve the diagonal MASA D......_E of C*(E). Our results pertain both automorphisms and proper endomorphisms. Firstly, the Weyl group and the restricted Weyl group of a graph C*-algebra are introduced and investigated. In particular, criteria of outerness for automorphisms in the restricted Weyl group are found. We also show...
Stevanovic, Dragan
2015-01-01
Spectral Radius of Graphs provides a thorough overview of important results on the spectral radius of adjacency matrix of graphs that have appeared in the literature in the preceding ten years, most of them with proofs, and including some previously unpublished results of the author. The primer begins with a brief classical review, in order to provide the reader with a foundation for the subsequent chapters. Topics covered include spectral decomposition, the Perron-Frobenius theorem, the Rayleigh quotient, the Weyl inequalities, and the Interlacing theorem. From this introduction, the
Age by Disease Biological Interactions: Implications for Late-Life Depression
Directory of Open Access Journals (Sweden)
Brandon eMcKinney
2012-11-01
Full Text Available Onset of depressive symptoms after the age of 65, or late-life depression (LLD, is common and poses a significant burden on affected individuals, caretakers and society. Evidence suggests a unique biological basis for LLD, but current hypotheses do not account for its pathophysiological complexity. Here we propose a novel etiological framework for LLD, the age-by-disease biological interaction hypothesis, based on the observations that the subset of genes that undergoes lifelong progressive changes in expression is restricted to a specific set of biological processes, and that a disproportionate number of these age-dependent genes have been previously and similarly implicated in neurodegenerative and neuropsychiatric disorders, including depression. The age-by-disease biological interaction hypothesis posits that age-dependent biological processes (i are pushed in LLD-promoting directions by changes in gene expression naturally occurring during brain aging, which (ii directly contribute to pathophysiological mechanisms of LLD, and (iii that individual variability in rates of age-dependent changes determines risk or resiliency to develop age-related disorders, including LLD. We review observations supporting this hypothesis, including consistent and specific age-dependent changes in brain gene expression, and their overlap with neuropsychiatric and neurodegenerative disease pathways. We then review preliminary reports supporting the genetic component of this hypothesis. Other potential biological mediators of age-dependent gene changes are proposed. We speculate that studies examining the relative contribution of these mechanisms to age-dependent changes and related disease mechanisms will not only provide critical information on the biology of normal aging of the human brain, but will inform our understanding our age-dependent diseases, in time fostering the development of new interventions for prevention and treatment of age-dependent diseases
Thompson, Katerina V; Nelson, Kären C; Marbach-Ad, Gili; Keller, Michael; Fagan, William F
2010-01-01
There is widespread agreement within the scientific and education communities that undergraduate biology curricula fall short in providing students with the quantitative and interdisciplinary problem-solving skills they need to obtain a deep understanding of biological phenomena and be prepared fully to contribute to future scientific inquiry. MathBench Biology Modules were designed to address these needs through a series of interactive, Web-based modules that can be used to supplement existing course content across the biological sciences curriculum. The effect of the modules was assessed in an introductory biology course at the University of Maryland. Over the course of the semester, students showed significant increases in quantitative skills that were independent of previous math course work. Students also showed increased comfort with solving quantitative problems, whether or not they ultimately arrived at the correct answer. A survey of spring 2009 graduates indicated that those who had experienced MathBench in their course work had a greater appreciation for the role of mathematics in modern biology than those who had not used MathBench. MathBench modules allow students from diverse educational backgrounds to hone their quantitative skills, preparing them for more complex mathematical approaches in upper-division courses.
Topics in graph theory graphs and their Cartesian product
Imrich, Wilfried; Rall, Douglas F
2008-01-01
From specialists in the field, you will learn about interesting connections and recent developments in the field of graph theory by looking in particular at Cartesian products-arguably the most important of the four standard graph products. Many new results in this area appear for the first time in print in this book. Written in an accessible way, this book can be used for personal study in advanced applications of graph theory or for an advanced graph theory course.
Formation of Robust Multi-Agent Networks through Self-Organizing Random Regular Graphs
Yasin Yazicioǧlu, A.
2015-11-25
Multi-Agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-Agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small number of links. One family of such graphs is the random regular graphs. In this paper, we present a decentralized scheme for transforming any connected interaction graph with a possibly non-integer average degree of k into a connected random m-regular graph for some m ϵ [k+k ] 2. Accordingly, the agents improve the robustness of the network while maintaining a similar number of links as the initial configuration by locally adding or removing some edges. © 2015 IEEE.
Using Graph Transformations and Graph Abstractions for Software Verification
Zambon, Eduardo; Rensink, Arend
In this paper we describe our intended approach for the verification of software written in imperative programming languages. We base our approach on model checking of graph transition systems, where each state is a graph and the transitions are specified by graph transformation rules. We believe
Robustness of random graphs based on graph spectra.
Wu, Jun; Barahona, Mauricio; Tan, Yue-Jin; Deng, Hong-Zhong
2012-12-01
It has been recently proposed that the robustness of complex networks can be efficiently characterized through the natural connectivity, a spectral property of the graph which corresponds to the average Estrada index. The natural connectivity corresponds to an average eigenvalue calculated from the graph spectrum and can also be interpreted as the Helmholtz free energy of the network. In this article, we explore the use of this index to characterize the robustness of Erdős-Rényi (ER) random graphs, random regular graphs, and regular ring lattices. We show both analytically and numerically that the natural connectivity of ER random graphs increases linearly with the average degree. It is also shown that ER random graphs are more robust than the corresponding random regular graphs with the same number of vertices and edges. However, the relative robustness of ER random graphs and regular ring lattices depends on the average degree and graph size: there is a critical graph size above which regular ring lattices are more robust than random graphs. We use our analytical results to derive this critical graph size as a function of the average degree.
Codes related to line graphs of triangular graphs and permutation ...
African Journals Online (AJOL)
For any prime p, we consider p-ary linear codes obtained from the row span of incidence matrices of line graphs of triangular graphs and adjacency matrices of their line graphs. We determine parameters of the codes, their automorphism groups and exhibit permutation decoding sets (PD-sets) for partial permutation ...
Information theory in systems biology. Part II: protein-protein interaction and signaling networks.
Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali
2016-03-01
By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. Copyright © 2015 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Paula G Ragone
Full Text Available Many infectious diseases arise from co-infections or re-infections with more than one genotype of the same pathogen. These mixed infections could alter host fitness, the severity of symptoms, success in pathogen transmission and the epidemiology of the disease. Trypanosoma cruzi, the etiological agent of Chagas disease, exhibits a high biological variability often correlated with its genetic diversity. Here, we developed an experimental approach in order to evaluate biological interaction between three T. cruzi isolates belonging to different Discrete Typing Units (DTUs TcIII, TcV and TcVI. These isolates were obtained from a restricted geographical area in the Chaco Region. Different mixed infections involving combinations of two isolates (TcIII + TcV, TcIII + TcVI and TcV + TcVI were studied in a mouse model. The parameters evaluated were number of parasites circulating in peripheral blood, histopathology and genetic characterization of each DTU in different tissues by DNA hybridization probes. We found a predominance of TcVI isolate in blood and tissues respect to TcIII and TcV; and a decrease of the inflammatory response in heart when the damage of mice infected with TcVI and TcIII + TcVI mixture were compared. In addition, simultaneous presence of two isolates in the same tissue was not detected. Our results show that biological interactions between isolates with different biological behaviors lead to changes in their biological properties. The occurrence of interactions among different genotypes of T. cruzi observed in our mouse model suggests that these phenomena could also occur in natural cycles in the Chaco Region.
Oliver, Joseph Steve; Hodges, Georgia W.; Moore, James N.; Cohen, Allan; Jang, Yoonsun; Brown, Scott A.; Kwon, Kyung A.; Jeong, Sophia; Raven, Sara P.; Jurkiewicz, Melissa; Robertson, Tom P.
2017-11-01
Research into the efficacy of modules featuring dynamic visualizations, case studies, and interactive learning environments is reported here. This quasi-experimental 2-year study examined the implementation of three interactive computer-based instructional modules within a curricular unit covering cellular biology concepts in an introductory high school biology course. The modules featured dynamic visualizations and focused on three processes that underlie much of cellular biology: diffusion, osmosis, and filtration. Pre-tests and post-tests were used to assess knowledge growth across the unit. A mixture Rasch model analysis of the post-test data revealed two groups of students. In both years of the study, a large proportion of the students were classified as low-achieving based on their pre-test scores. The use of the modules in the Cell Unit in year 2 was associated with a much larger proportion of the students having transitioned to the high-achieving group than in year 1. In year 2, the same teachers taught the same concepts as year 1 but incorporated the interactive computer-based modules into the cell biology unit of the curriculum. In year 2, 67% of students initially classified as low-achieving were classified as high-achieving at the end of the unit. Examination of responses to assessments embedded within the modules as well as post-test items linked transition to the high-achieving group with correct responses to items that both referenced the visualization and the contextualization of that visualization within the module. This study points to the importance of dynamic visualization within contextualized case studies as a means to support student knowledge acquisition in biology.
Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways
Directory of Open Access Journals (Sweden)
Carlos R. Rangel
2016-08-01
Full Text Available In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease, and the main cells in each community. We analyze our approach in two cases: TGF-ß and the Alzheimer Disease.
Visualizing automorphisms of graph algebras
DEFF Research Database (Denmark)
Avery, James Emil; Johansen, Rune; Szymanski, Wojciech
2018-01-01
Graph C*-algebras have been celebrated as C*-algebras that can be seen, because many important properties may be determined by looking at the underlying graph. This paper introduces the permutation graph for a permutative endomorphism of a graph C*-algebra as a labeled directed multigraph...... that gives a visual representation of the endomorphism and facilitates computations. Combinatorial criteria have previously been developed for deciding when such an endomorphism is an automorphism, but here the question is reformulated in terms of the permutation graph and new proofs are given. Furthermore......, it is shown how to use permutation graphs to efficiently generate exhaustive collections of permutative automorphisms. Permutation graphs provide a natural link to the textile systems representing induced endomorphisms on the edge shift of the given graph, and this allows the powerful tools of the theory...
Rensink, Arend; Schmidt, David
2004-01-01
Graphs are an intuitive model for states of a (software) system that include pointer structures | for instance, object-oriented programs. However, a naive encoding results in large individual states and large, or even unbounded, state spaces. As usual, some form of abstraction is necessary in order
Rensink, Arend; Schmidt, D.A.
2004-01-01
Abstract. Graphs are an intuitive model for states of a (software) system that include pointer structures — for instance, object-oriented programs. However, a naive encoding results in large individual states and large, or even unbounded, state spaces. As usual, some form of abstraction is necessary
Dujmović, Vida; Sidiropoulos, Anastasios; Wood, David R.
2015-01-01
Bourgain and Yehudayoff recently constructed $O(1)$-monotone bipartite expanders. By combining this result with a generalisation of the unraveling method of Kannan, we construct 3-monotone bipartite expanders, which is best possible. We then show that the same graphs admit 3-page book embeddings, 2-queue layouts, 4-track layouts, and have simple thickness 2. All these results are best possible.
S.M. Heditniemi (Sandra); R.C. Laskar (R.C.); H.M. Mulder (Martyn)
2012-01-01
textabstractLet $G = (V,E)$ be a graph. A partition $\\pi = \\{V_1, V_2, \\ldots, V_k \\}$ of the vertices $V$ of $G$ into $k$ {\\it color classes} $V_i$, with $1 \\leq i \\leq k$, is called a {\\it quorum coloring} if for every vertex $v \\in V$, at least half of the vertices in the closed neighborhood
Cooper, Carol
1975-01-01
Teachers of an integrated elementary classroom used cookie-sharing time as a learning experience for students. Responsible for dividing varying amounts of cookies daily, the students learned to translate their experiences to graphs of differing sophistication and analyses. Further interpretation and application were done by individual students…
Grabmayer, C.A.; van Oostrom, V.
2014-01-01
We report on work in progress on `nested term graphs' for formalizing higher-order terms (e.g. finite or infinite lambda-terms), including those expressing recursion (e.g. terms in the lambda-calculus with letrec). The idea is to represent the nested scope structure of a higher-order term by a
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 8; Issue 9. Decoding Codes on Graphs - Low Density Parity Check Codes. A S Madhu Aditya Nori. General Article Volume 8 Issue 9 September 2003 pp 49-59. Fulltext. Click here to view fulltext PDF. Permanent link:
Energy Technology Data Exchange (ETDEWEB)
Simmons, G.J.
1985-01-01
Given a graph G and an ordering phi of the vertices, V(G), we define a parsimonious proper coloring (PPC) of V(G) under phi to be a proper coloring of V(G) in the order phi, where a new color is introduced only when a vertex cannot be properly colored in its order with any of the colors already used.
On dominator colorings in graphs
Indian Academy of Sciences (India)
Graph coloring and domination are two major areas in graph theory that have been ... independent set if no two vertices in S are adjacent. ... independent set. The corona G1 ◦ G2 of two graphs G1 and G2 is defined to be the graph. G obtained by taking one copy of G1 and |V(G1)| copies of G2, and then joining the i-th.
Hamiltonian paths on Platonic graphs
Directory of Open Access Journals (Sweden)
Brian Hopkins
2004-07-01
Full Text Available We develop a combinatorial method to show that the dodecahedron graph has, up to rotation and reflection, a unique Hamiltonian cycle. Platonic graphs with this property are called topologically uniquely Hamiltonian. The same method is used to demonstrate topologically distinct Hamiltonian cycles on the icosahedron graph and to show that a regular graph embeddable on the 2-holed torus is topologically uniquely Hamiltonian.
Interaction of biological systems with static and ELF electric and magnetic fields
Energy Technology Data Exchange (ETDEWEB)
Anderson, L.E.; Kelman, B.J.; Weigel, R.J. (eds.)
1987-01-01
Although background levels of atmospheric electric and geomagnetic field levels are extremely low, over the past several decades, human beings and other life forms on this planet have been subjected to a dramatically changing electromagnetic milieu. An exponential increase in exposure to electromagnetic fields has occurred, largely because of such technological advances as the growth of electrical power generation and transmission systems, the increased use of wireless communications, and the use of radar. In addition, electromagnetic field generating devices have proliferated in industrial plants, office buildings, homes, public transportation systems, and elsewhere. Although significant increases have occurred in electromagnetic field strenghths spanning all frequency ranges, this symposium addresses only the impact of these fields at static and extremely low frequencies (ELF), primarily 50 and 60 Hz. This volume contains the proceedings of the symposium entitled /open quotes/Interaction of biological systems with static and ELF electric and magnetic fields/close quotes/. The purpose of the symposium was to provide a forum for discussions of all aspects of research on the interaction of static and ELF electromagnetic fields with biological systems. These systems include simple biophysical models, cell and organ preparations, whole animals, and man. Dosimetry, exposure system design, and artifacts in ELF bioeffects research were also addressed, along with current investigations that examine fundamental mechanisms of interactions between the fields and biological processes. Papers are indexed separately.
Energy Technology Data Exchange (ETDEWEB)
Winlaw, Manda [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); De Sterck, Hans [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoffrey [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-10-26
In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps to understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.
Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.
Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C
2010-09-13
Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.
Nullspace embeddings for outerplanar graphs
L. Lovász (László); A. Schrijver (Alexander)
2017-01-01
textabstractWe study relations between geometric embeddings of graphs and the spectrum of associated matrices, focusing on outerplanar embeddings of graphs. For a simple connected graph G=(V,E), we define a "good" G-matrix as a V×V matrix with negative entries corresponding to adjacent nodes, zero
Nullspace embeddings for outerplanar graphs
L. Lovász (László); A. Schrijver (Alexander); M. Loebl (Martin); J. Nešetřil (Jaroslav); R. Thomas (Robin)
2017-01-01
htmlabstractWe study relations between geometric embeddings of graphs and the spectrum of associated matrices, focusing on outerplanar embeddings of graphs. For a simple connected graph G = (V, E), we define a "good” G-matrix as a V × V matrix with negative
Nullspace embeddings for outerplanar graphs
Lovász, L.; Schrijver, A.; Loebl, M.; Nešetřil, J.; Thomas, R.
2017-01-01
We study relations between geometric embeddings of graphs and the spectrum of associated matrices, focusing on outerplanar embeddings of graphs. For a simple connected graph G = (V, E), we define a “good” G-matrix as a V × V matrix with negative entries corresponding to adjacent nodes, zero entries
Pattern-Based Graph Abstraction
Rensink, Arend; Zambon, Eduardo; Ehrig, H; Engels, G.; Kreowski, H.J.; Rozenberg, G.
We present a new abstraction technique for the exploration of graph transformation systems with infinite state spaces. This technique is based on patterns, simple graphs describing structures of interest that should be preserved by the abstraction. Patterns are collected into pattern graphs, layered
Generalised compositionality in graph transformation
Ghamarian, A.H.; Rensink, Arend; Ehrig, H; Engels, G.; Kreowski, H.J.; Rozenberg, G.
We present a notion of composition applying both to graphs and to rules, based on graph and rule interfaces along which they are glued. The current paper generalises a previous result in two different ways. Firstly, rules do not have to form pullbacks with their interfaces; this enables graph
Hopkins, Brian
2004-01-01
The interconnected world of actors and movies is a familiar, rich example for graph theory. This paper gives the history of the "Kevin Bacon Game" and makes extensive use of a Web site to analyze the underlying graph. The main content is the classroom development of the weighted average to determine the best choice of "center" for the graph. The…
Mining and Indexing Graph Databases
Yuan, Dayu
2013-01-01
Graphs are widely used to model structures and relationships of objects in various scientific and commercial fields. Chemical molecules, proteins, malware system-call dependencies and three-dimensional mechanical parts are all modeled as graphs. In this dissertation, we propose to mine and index those graph data to enable fast and scalable search.…
Graph transformation tool contest 2008
Rensink, Arend; van Gorp, Pieter
This special section is the outcome of the graph transformation tool contest organised during the Graph-Based Tools (GraBaTs) 2008 workshop, which took place as a satellite event of the International Conference on Graph Transformation (ICGT) 2008. The contest involved two parts: three “off-line case
Submanifolds weakly associated with graphs
Indian Academy of Sciences (India)
We establish an interesting link between differential geometry and graph theory by defining submanifolds weakly associated with graphs. We prove that, in a local sense, every submanifold satisfies such an association, and other general results. Finally, we study submanifolds associated with graphs either in low ...
Cosmic-ray interaction data for designing biological experiments in space
Straume, T.; Slaba, T. C.; Bhattacharya, S.; Braby, L. A.
2017-05-01
There is growing interest in flying biological experiments beyond low-Earth orbit (LEO) to measure biological responses potentially relevant to those expected during a human mission to Mars. Such experiments could be payloads onboard precursor missions, including unmanned private-public partnerships, as well as small low-cost spacecraft (satellites) designed specifically for biosentinel-type missions. It is the purpose of this paper to provide physical cosmic-ray interaction data and related information useful to biologists who may be planning such experiments. It is not the objective here to actually design such experiments or provide radiobiological response functions, which would be specific for each experiment and biological endpoint. Nuclide-specific flux and dose rates were calculated using OLTARIS and these results were used to determine particle traversal rates and doses in hypothetical biological targets. Comparisons are provided between GCR in interplanetary space and inside the ISS. Calculated probabilistic estimates of dose from solar particle events are also presented. Although the focus here is on biological experiments, the information provided may be useful for designing other payloads as well if the space radiation environment is a factor to be considered.
Asteroidal Quadruples in non Rooted Path Graphs
Directory of Open Access Journals (Sweden)
Gutierrez Marisa
2015-11-01
Full Text Available A directed path graph is the intersection graph of a family of directed subpaths of a directed tree. A rooted path graph is the intersection graph of a family of directed subpaths of a rooted tree. Rooted path graphs are directed path graphs. Several characterizations are known for directed path graphs: one by forbidden induced subgraphs and one by forbidden asteroids. It is an open problem to find such characterizations for rooted path graphs. For this purpose, we are studying in this paper directed path graphs that are non rooted path graphs. We prove that such graphs always contain an asteroidal quadruple.
Leonard, William H.
This study was designed to learn if students perceived an interactive computer/videodisc learning system to represent a viable alternative to (or extension of) the conventional laboratory for learning biology skills and concepts normally taught under classroom laboratory conditions. Data were collected by questionnaire for introductory biology classes at a large midwestern university where students were randomly assigned to two interactive videodisc/computer lessons titled Respiration and Climate and Life or traditional laboratory investigation with the same titles and concepts. The interactive videodisc system consisted of a TRS-80 Model III microcomputer interfaced to a Pioneer laser-disc player and a color TV monitor. Students indicated an overall level satisfaction with this strategy very similar to that of conventional laboratory instruction. Students frequently remarked that videodisc instruction gave them more experimental and procedural options and more efficient use of instructional time than did the conventional laboratory mode. These two results are consistent with past CAI research. Students also had a strong perception that the images on the videodisc were not real and this factor was perceived as having both advantages and disadvantages. Students found the two approaches to be equivalent to conventional laboratory instruction in the areas of general interest, understanding of basic principles, help on examinations, and attitude toward science. The student-opinion data in this study do not suggest that interactive videodisc technology serve as a substitute to the wet laboratory experience, but that this medium may enrich the spectrum of educational experiences usually not possible in typical classroom settings.
Prodanov, Dimiter; Delbeke, Jean
2016-01-01
Neural prostheses have already a long history and yet the cochlear implant remains the only success story about a longterm sensory function restoration. On the other hand, neural implants for deep brain stimulation are gaining acceptance for variety of disorders including Parkinsons disease and obsessive-compulsive disorder. It is anticipated that the progress in the field has been hampered by a combination of technological and biological factors, such as the limited understanding of the longterm behavior of implants, unreliability of devices, biocompatibility of the implants among others. While the field's understanding of the cell biology of interactions at the biotic-abiotic interface has improved, relatively little attention has been paid on the mechanical factors (stress, strain), and hence on the geometry that can modulate it. This focused review summarizes the recent progress in the understanding of the mechanisms of mechanical interaction between the implants and the brain. The review gives an overview of the factors by which the implants interact acutely and chronically with the tissue: blood-brain barrier (BBB) breach, vascular damage, micromotions, diffusion etc. We propose some design constraints to be considered in future studies. Aspects of the chronic cell-implant interaction will be discussed in view of the chronic local inflammation and the ways of modulating it.
Probability on graphs random processes on graphs and lattices
Grimmett, Geoffrey
2018-01-01
This introduction to some of the principal models in the theory of disordered systems leads the reader through the basics, to the very edge of contemporary research, with the minimum of technical fuss. Topics covered include random walk, percolation, self-avoiding walk, interacting particle systems, uniform spanning tree, random graphs, as well as the Ising, Potts, and random-cluster models for ferromagnetism, and the Lorentz model for motion in a random medium. This new edition features accounts of major recent progress, including the exact value of the connective constant of the hexagonal lattice, and the critical point of the random-cluster model on the square lattice. The choice of topics is strongly motivated by modern applications, and focuses on areas that merit further research. Accessible to a wide audience of mathematicians and physicists, this book can be used as a graduate course text. Each chapter ends with a range of exercises.
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Montaño-Machado, Vanessa, E-mail: vanessa.montano-machado.1@ulaval.ca [Laboratory for Biomaterials and Bioengineering, Dept. of Min-Met-Materials Eng., & University Hospital Research Center, Laval University, University Campus, PLT-1745G, Québec, Québec, G1 V 0A6 (Canada); ERRMECe, University of Cergy-Pontoise, Site Saint-Martin, 2 Avenue Adolphe Chauvin, 95302 Cergy-Pontoise Cedex (France); Noël, Céline, E-mail: celine.noel@unamur.be [Research Centre in Physics of Matter and Radiation (PMR), Université de Namur, 61 rue de Bruxelles, B-5000 Namur (Belgium); Chevallier, Pascale, E-mail: pascale.chevallier@crchudequebec.ulaval.ca [Laboratory for Biomaterials and Bioengineering, Dept. of Min-Met-Materials Eng., & University Hospital Research Center, Laval University, University Campus, PLT-1745G, Québec, Québec, G1 V 0A6 (Canada); Turgeon, Stéphane, E-mail: stephane.turgeon@crchudequebec.ulaval.ca [Laboratory for Biomaterials and Bioengineering, Dept. of Min-Met-Materials Eng., & University Hospital Research Center, Laval University, University Campus, PLT-1745G, Québec, Québec, G1 V 0A6 (Canada); Houssiau, Laurent, E-mail: laurent.houssiau@unamur.be [Research Centre in Physics of Matter and Radiation (PMR), Université de Namur, 61 rue de Bruxelles, B-5000 Namur (Belgium); Pauthe, Emmanuel, E-mail: emmanuel.pauthe@u-cergy.fr [ERRMECe, University of Cergy-Pontoise, Site Saint-Martin, 2 Avenue Adolphe Chauvin, 95302 Cergy-Pontoise Cedex (France); and others
2017-02-28
Highlights: • Fibronectin/phosphorylcholine coatings on plasma deposited fluorocarbon films were created. • The effect of several coating techniques on the surface biological performances was evaluated. • XPS, DWCA, immunostaining and ToF-SIMS (imaging and depth profiling) techniques were applied. • Potential for cardiovascular applications was showed by endothelial cell and blood interactions. - Abstract: Coating medical devices with several bioactive molecules is an interesting approach to achieve specific biological targets upon the interaction of the biomaterial with the living environment. In this work, a fluorocarbon polymer (CF{sub x}) was first deposited by plasma treatment on stainless steel (SS) substrate and thereafter, coatings containing fibronectin (FN) and phosphorylcholine (PRC) were created for cardiovascular applications. These two biomolecules were chosen to promote endothelialization and to avoid thrombus formation, respectively. Adsorption and grafting techniques were applied – and combined – to accomplish 4 different coatings containing both molecules. However, big challenge was found to characterize a small molecule (PRC: 184 g/mol) interacting with a protein (FN: 450 kD). For the first time XPS, dynamic water contact angle, immunostaining and ToF-SIMS (imaging and depth profiling) analyses were combined to accomplish the characterization of such a coating. The most encouraging biological performances were obtained for samples where FN was grafted to the CF{sub x} film followed by the adsorption of PRC: proliferation of endothelial cells and hemocompatibility properties were observed. Promising coatings for cardiovascular applications were developed. The relevance of characterizing the coatings with high sensitive techniques and the further correlation with their biological performances were evidenced.
Biological interactions in vitro of zinc oxide nanoparticles of different characteristics
Aula, Sangeetha; Lakkireddy, Samyuktha; AVN, Swamy; Kapley, Atya; Jamil, Kaiser; Rao Tata, Narasinga; Hembram, Kaliyan
2014-09-01
Zinc oxide nanoparticles (ZnO NPs) have recently received growing attention for various biomedical applications, including use as therapeutic or carrier for drug delivery and/or imaging. For the above applications, the NPs necessitate administration into the body leading to their systemic exposure. To better anticipate the safety, make risk assessment, and be able to interpret the future preclinical and clinical safety data, it is important to systematically understand the biological interaction of the NPs, the consequences of such interaction, and the mechanisms associated with the toxicity induction, with the important components with which the NPs are expected to be in contact after systemic exposure. In this context, we report here a detailed study on the biological interactions in vitro of the ZnO NPs with healthy human primary lymphocytes as these are the important immune components and the first systemic immune contact, and with the whole human blood. Additionally, the influence, if any, of the NPs shape (spheres and rods) on the biological interaction has been evaluated. The ZnO NPs caused toxicity (30% at 12.5 μg ml-1 spheres and 10.5 μg ml-1 rods; 50% at 22 μg ml-1 spheres and 19.5 μg ml-1 rods) to the lymphocytes at molecular and genetic level in a dose-dependent and shape-dependent manner, while the interaction consequences with the blood and blood components such as RBC, platelets was only dose-dependent and not shape-dependent. This is evident from the decreased RBC count due to increased %Hemolysis (5.3% in both the spheres- and rods-treated blood) and decreased platelet count due to increased %platelet aggregation (28% in spheres-treated and 33% in rods-treated platelet-rich plasma). Such in-depth understanding of the biological interaction of the NPs, the consequences, and the associated mechanisms in vitro could be expected to allow anticipating the NP safety for risk assessment and for interpretation of the preclinical and clinical safety
Reactome graph database: Efficient access to complex pathway data.
Fabregat, Antonio; Korninger, Florian; Viteri, Guilherme; Sidiropoulos, Konstantinos; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning
2018-01-01
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.
Reactome graph database: Efficient access to complex pathway data.
Directory of Open Access Journals (Sweden)
Antonio Fabregat
2018-01-01
Full Text Available Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j as well as the new ContentService (REST API that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.
Feltman, Vallery
Over the last decade growth in technologies available to teach students and enhance curriculum has become an important consideration in the educational system. The profile of today's secondary students have also been found to be quite different than those of the past. Their learning styles and preferences are issues that should be addressed by educators. With the growth and availability of new technologies students are increasingly expecting to use these as learning tools in their classrooms. This study investigates how interactive technology may impact student performance. This study specifically focuses on the use of the Apple Ipad in 4 Biology I classrooms. This study used an experimental mixed method design to examine how using Ipads for learning impacted student achievement, motivation to learn, and learning strategies. Qualitatively the study examined observed student behaviors and student perceptions regarding the use of interactive technologies. Data was analyzed using descriptive statistics, t-tests, 2-way ANOVAs, and qualitative analysis. Quantitatively the results revealed no significant difference between students who used the interactive technology to learn and those who did not. Qualitative data revealed behaviors indicative of being highly engaged with the subject matter and the development of critical thinking skills which may improve student performance. Student perceptions also revealed overall positive experiences with using interactive technology in the classroom. It is recommended that further studies be done to look at using interactive technologies for a longer period of time using multiple subjects areas. This would provide a more in-depth exploration of interactive technologies on student achievement.
Harary, Frank
2015-01-01
Presented in 1962-63 by experts at University College, London, these lectures offer a variety of perspectives on graph theory. Although the opening chapters form a coherent body of graph theoretic concepts, this volume is not a text on the subject but rather an introduction to the extensive literature of graph theory. The seminar's topics are geared toward advanced undergraduate students of mathematics.Lectures by this volume's editor, Frank Harary, include ""Some Theorems and Concepts of Graph Theory,"" ""Topological Concepts in Graph Theory,"" ""Graphical Reconstruction,"" and other introduc
Domination criticality in product graphs
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M.R. Chithra
2015-07-01
Full Text Available A connected dominating set is an important notion and has many applications in routing and management of networks. Graph products have turned out to be a good model of interconnection networks. This motivated us to study the Cartesian product of graphs G with connected domination number, γc(G=2,3 and characterize such graphs. Also, we characterize the k−γ-vertex (edge critical graphs and k−γc-vertex (edge critical graphs for k=2,3 where γ denotes the domination number of G. We also discuss the vertex criticality in grids.
Dynamic Representations of Sparse Graphs
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Fagerberg, Rolf
1999-01-01
We present a linear space data structure for maintaining graphs with bounded arboricity—a large class of sparse graphs containing e.g. planar graphs and graphs of bounded treewidth—under edge insertions, edge deletions, and adjacency queries. The data structure supports adjacency queries in worst...... case O(c) time, and edge insertions and edge deletions in amortized O(1) and O(c+log n) time, respectively, where n is the number of nodes in the graph, and c is the bound on the arboricity....
Electrical circuit modeling and analysis of microwave acoustic interaction with biological tissues.
Gao, Fei; Zheng, Qian; Zheng, Yuanjin
2014-05-01
Numerical study of microwave imaging and microwave-induced thermoacoustic imaging utilizes finite difference time domain (FDTD) analysis for simulation of microwave and acoustic interaction with biological tissues, which is time consuming due to complex grid-segmentation and numerous calculations, not straightforward due to no analytical solution and physical explanation, and incompatible with hardware development requiring circuit simulator such as SPICE. In this paper, instead of conventional FDTD numerical simulation, an equivalent electrical circuit model is proposed to model the microwave acoustic interaction with biological tissues for fast simulation and quantitative analysis in both one and two dimensions (2D). The equivalent circuit of ideal point-like tissue for microwave-acoustic interaction is proposed including transmission line, voltage-controlled current source, envelop detector, and resistor-inductor-capacitor (RLC) network, to model the microwave scattering, thermal expansion, and acoustic generation. Based on which, two-port network of the point-like tissue is built and characterized using pseudo S-parameters and transducer gain. Two dimensional circuit network including acoustic scatterer and acoustic channel is also constructed to model the 2D spatial information and acoustic scattering effect in heterogeneous medium. Both FDTD simulation, circuit simulation, and experimental measurement are performed to compare the results in terms of time domain, frequency domain, and pseudo S-parameters characterization. 2D circuit network simulation is also performed under different scenarios including different sizes of tumors and the effect of acoustic scatterer. The proposed circuit model of microwave acoustic interaction with biological tissue could give good agreement with FDTD simulated and experimental measured results. The pseudo S-parameters and characteristic gain could globally evaluate the performance of tumor detection. The 2D circuit network
Graph Sampling for Covariance Estimation
Chepuri, Sundeep Prabhakar
2017-04-25
In this paper the focus is on subsampling as well as reconstructing the second-order statistics of signals residing on nodes of arbitrary undirected graphs. Second-order stationary graph signals may be obtained by graph filtering zero-mean white noise and they admit a well-defined power spectrum whose shape is determined by the frequency response of the graph filter. Estimating the graph power spectrum forms an important component of stationary graph signal processing and related inference tasks such as Wiener prediction or inpainting on graphs. The central result of this paper is that by sampling a significantly smaller subset of vertices and using simple least squares, we can reconstruct the second-order statistics of the graph signal from the subsampled observations, and more importantly, without any spectral priors. To this end, both a nonparametric approach as well as parametric approaches including moving average and autoregressive models for the graph power spectrum are considered. The results specialize for undirected circulant graphs in that the graph nodes leading to the best compression rates are given by the so-called minimal sparse rulers. A near-optimal greedy algorithm is developed to design the subsampling scheme for the non-parametric and the moving average models, whereas a particular subsampling scheme that allows linear estimation for the autoregressive model is proposed. Numerical experiments on synthetic as well as real datasets related to climatology and processing handwritten digits are provided to demonstrate the developed theory.
Canonical Labelling of Site Graphs
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Nicolas Oury
2013-06-01
Full Text Available We investigate algorithms for canonical labelling of site graphs, i.e. graphs in which edges bind vertices on sites with locally unique names. We first show that the problem of canonical labelling of site graphs reduces to the problem of canonical labelling of graphs with edge colourings. We then present two canonical labelling algorithms based on edge enumeration, and a third based on an extension of Hopcroft's partition refinement algorithm. All run in quadratic worst case time individually. However, one of the edge enumeration algorithms runs in sub-quadratic time for graphs with "many" automorphisms, and the partition refinement algorithm runs in sub-quadratic time for graphs with "few" bisimulation equivalences. This suite of algorithms was chosen based on the expectation that graphs fall in one of those two categories. If that is the case, a combined algorithm runs in sub-quadratic worst case time. Whether this expectation is reasonable remains an interesting open problem.
Localization in random bipartite graphs: Numerical and empirical study
Slanina, František
2017-05-01
We investigate adjacency matrices of bipartite graphs with a power-law degree distribution. Motivation for this study is twofold: first, vibrational states in granular matter and jammed sphere packings; second, graphs encoding social interaction, especially electronic commerce. We establish the position of the mobility edge and show that it strongly depends on the power in the degree distribution and on the ratio of the sizes of the two parts of the bipartite graph. At the jamming threshold, where the two parts have the same size, localization vanishes. We found that the multifractal spectrum is nontrivial in the delocalized phase, but still near the mobility edge. We also study an empirical bipartite graph, namely, the Amazon reviewer-item network. We found that in this specific graph the mobility edge disappears, and we draw a conclusion from this fact regarding earlier empirical studies of the Amazon network.
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Burhan Selçuk
2017-06-01
Full Text Available Hypercube is a popular interconnection network. Due to the popularity of hypercube, more researchers pay a great effort to develop the different variants of hypercube. In this paper, we have proposed a variant of hypercube which is called as “Connected Cubic Network Graphs”, and have investigated the Hamilton-like properties of Connected Cubic Network Graphs (CCNG. Firstly, we defined CCNG and showed the characteristic analyses of CCNG. Then, we showed that the CCNG has the properties of Hamilton graph, and can be labeled using a Gray coding based recursive algorithm. Finally, we gave the comparison results, a routing algorithm and a bitonic sort algorithm for CCNG. In case of sparsity and cost, CCNG is better than Hypercube.
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Knox Sarah S
2010-04-01
Full Text Available Abstract Background Cancer is a complex disease that involves a sequence of gene-environment interactions in a progressive process that cannot occur without dysfunction in multiple systems, including DNA repair, apoptotic and immune functions. Epigenetic mechanisms, responding to numerous internal and external cues in a dynamic ongoing exchange, play a key role in mediating environmental influences on gene expression and tumor development. Hypothesis The hypothesis put forth in this paper addresses the limited success of treatment outcomes in clinical oncology. It states that improvement in treatment efficacy requires a new paradigm that focuses on reversing systemic dysfunction and tailoring treatments to specific stages in the process. It requires moving from a reductionist framework of seeking to destroy aberrant cells and pathways to a transdisciplinary systems biology approach aimed at reversing multiple levels of dysfunction. Conclusion Because there are many biological pathways and multiple epigenetic influences working simultaneously in the expression of cancer phenotypes, studying individual components in isolation does not allow an adequate understanding of phenotypic expression. A systems biology approach using new modeling techniques and nonlinear mathematics is needed to investigate gene-environment interactions and improve treatment efficacy. A broader array of study designs will also be required, including prospective molecular epidemiology, immune competent animal models and in vitro/in vivo translational research that more accurately reflects the complex process of tumor initiation and progression.
Detecting Biological Motion for Human–Robot Interaction: A Link between Perception and Action
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Alessia Vignolo
2017-06-01
Full Text Available One of the fundamental skills supporting safe and comfortable interaction between humans is their capability to understand intuitively each other’s actions and intentions. At the basis of this ability is a special-purpose visual processing that human brain has developed to comprehend human motion. Among the first “building blocks” enabling the bootstrapping of such visual processing is the ability to detect movements performed by biological agents in the scene, a skill mastered by human babies in the first days of their life. In this paper, we present a computational model based on the assumption that such visual ability must be based on local low-level visual motion features, which are independent of shape, such as the configuration of the body and perspective. Moreover, we implement it on the humanoid robot iCub, embedding it into a software architecture that leverages the regularities of biological motion also to control robot attention and oculomotor behaviors. In essence, we put forth a model in which the regularities of biological motion link perception and action enabling a robotic agent to follow a human-inspired sensory-motor behavior. We posit that this choice facilitates mutual understanding and goal prediction during collaboration, increasing the pleasantness and safety of the interaction.
Syed, M. Qasim; Lovatt, Ian
2014-01-01
This paper is an addition to the series of papers on the exponential function begun by Albert Bartlett. In particular, we ask how the graph of the exponential function y = e[superscript -t/t] would appear if y were plotted versus ln t rather than the normal practice of plotting ln y versus t. In answering this question, we find a new way to…
2010-12-02
evaluating the function ΘP (A) for any fixed A,P is equivalent to solving the so-called Quadratic Assignment Problem ( QAP ), and thus we can employ various...tractable linear programming, spectral, and SDP relaxations of QAP [40, 11, 33]. In particular we discuss recent work [14] on exploiting group...symmetry in SDP relaxations of QAP , which is useful for approximately computing elementary convex graph invariants in many interesting cases. Finally in
Zhou, Feng; de la Torre, Fernando
2015-11-19
Graph matching (GM) is a fundamental problem in computer science, and it plays a central role to solve correspondence problems in computer vision. GM problems that incorporate pairwise constraints can be formulated as a quadratic assignment problem (QAP). Although widely used, solving the correspondence problem through GM has two main limitations: (1) the QAP is NP-hard and difficult to approximate; (2) GM algorithms do not incorporate geometric constraints between nodes that are natural in computer vision problems. To address aforementioned problems, this paper proposes factorized graph matching (FGM). FGM factorizes the large pairwise affinity matrix into smaller matrices that encode the local structure of each graph and the pairwise affinity between edges. Four are the benefits that follow from this factorization: (1) There is no need to compute the costly (in space and time) pairwise affinity matrix; (2) The factorization allows the use of a path-following optimization algorithm, that leads to improved optimization strategies and matching performance; (3) Given the factorization, it becomes straight-forward to incorporate geometric transformations (rigid and non-rigid) to the GM problem. (4) Using a matrix formulation for the GM problem and the factorization, it is easy to reveal commonalities and differences between different GM methods. The factorization also provides a clean connection with other matching algorithms such as iterative closest point; Experimental results on synthetic and real databases illustrate how FGM outperforms state-of-the-art algorithms for GM. The code is available at http://humansensing.cs.cmu.edu/fgm.
The Promise of Systems Biology Approaches for Revealing Host Pathogen Interactions in Malaria
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Meghan Zuck
2017-11-01
Full Text Available Despite global eradication efforts over the past century, malaria remains a devastating public health burden, causing almost half a million deaths annually (WHO, 2016. A detailed understanding of the mechanisms that control malaria infection has been hindered by technical challenges of studying a complex parasite life cycle in multiple hosts. While many interventions targeting the parasite have been implemented, the complex biology of Plasmodium poses a major challenge, and must be addressed to enable eradication. New approaches for elucidating key host-parasite interactions, and predicting how the parasite will respond in a variety of biological settings, could dramatically enhance the efficacy and longevity of intervention strategies. The field of systems biology has developed methodologies and principles that are well poised to meet these challenges. In this review, we focus our attention on the Liver Stage of the Plasmodium lifecycle and issue a “call to arms” for using systems biology approaches to forge a new era in malaria research. These approaches will reveal insights into the complex interplay between host and pathogen, and could ultimately lead to novel intervention strategies that contribute to malaria eradication.
Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong
2017-09-20
Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.
Chen, Ran; Riviere, Jim E
2017-01-01
Quantitative analysis of the interactions between nanomaterials and their surrounding environment is crucial for safety evaluation in the application of nanotechnology as well as its development and standardization. In this chapter, we demonstrate the importance of the adsorption of surrounding molecules onto the surface of nanomaterials by forming biocorona and thus impact the bio-identity and fate of those materials. We illustrate the key factors including various physical forces in determining the interaction happening at bio-nano interfaces. We further discuss the mathematical endeavors in explaining and predicting the adsorption phenomena, and propose a new statistics-based surface adsorption model, the Biological Surface Adsorption Index (BSAI), to quantitatively analyze the interaction profile of surface adsorption of a large group of small organic molecules onto nanomaterials with varying surface physicochemical properties, first employing five descriptors representing the surface energy profile of the nanomaterials, then further incorporating traditional semi-empirical adsorption models to address concentration effects of solutes. These Advancements in surface adsorption modelling showed a promising development in the application of quantitative predictive models in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.
Investigation of natural lipid-phenolic interactions on biological properties of virgin olive oil.
Alu'datt, Muhammad H; Rababah, Taha; Ereifej, Khalil; Gammoh, Sana; Alhamad, Mohammad N; Mhaidat, Nizar; Kubow, Stan; Johargy, Ayman; Alnaiemi, Ola J
2014-12-10
There is limited knowledge regarding the impact of naturally occurring lipid-phenolic interactions on the biological properties of phenolics in virgin olive oil. Free and bound phenolics were isolated via sequential methanolic extraction at 30 and 60 °C, and were identified and quantified using reversed phase high performance liquid chromatography, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), and gas chromatography. Decreased oleic acid concentrations and increased concentrations of palmitoleic acid, stearic, linoleic, and linolenic acids were observed in virgin olive oil after removal of free and bound lipid phenolic compounds. The presence of p-hydroxybenzoic acid and tyrosol bound to glycerides was determined via LC-MS/MS, which indicates natural lipid-phenolic interactions in virgin olive oil. Both free and lipid bound phenolic extracts exerted antiproliferative activities against the CRC1 and CRC5 colorectal cancer cell lines. The present work indicates that naturally occurring lipid-phenolic interactions can affect the biological properties of phenolics in virgin olive oil.
Biokinetics of zinc oxide nanoparticles: toxicokinetics, biological fates, and protein interaction
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Choi SJ
2014-12-01
Full Text Available Soo-Jin Choi,1 Jin-Ho Choy2 1Department of Food Science and Technology, Seoul Women's University, 2Center for Intelligent Nano Bio Materials (CINBM, Department of Bioinspired Science and Department of Chemistry and Nanoscience, Ewha Womans University, Seoul, South Korea Abstract: Biokinetic studies of zinc oxide (ZnO nanoparticles involve systematic and quantitative analyses of absorption, distribution, metabolism, and excretion in plasma and tissues of whole animals after exposure. A full understanding of the biokinetics provides basic information about nanoparticle entry into systemic circulation, target organs of accumulation and toxicity, and elimination time, which is important for predicting the long-term toxic potential of nanoparticles. Biokinetic behaviors can be dependent on physicochemical properties, dissolution property in biological fluids, and nanoparticle–protein interaction. Moreover, the determination of biological fates of ZnO nanoparticles in the systemic circulation and tissues is critical in interpreting biokinetic behaviors and predicting toxicity potential as well as mechanism. This review focuses on physicochemical factors affecting the biokinetics of ZnO nanoparticles, in concert with understanding bioavailable fates and their interaction with proteins. Keywords: ZnO nanoparticles, biokinetics, distribution, excretion, fate, interaction
Laraia, Luca; McKenzie, Grahame; Spring, David R.; Venkitaraman, Ashok R.; Huggins, David J.
2015-01-01
Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs. PMID:26091166
What do interaction network metrics tell us about specialization and biological traits?
Blüthgen, Nico; Fründ, Jochen; Vázquez, Diego P; Menzel, Florian
2008-12-01
The structure of ecological interaction networks is often interpreted as a product of meaningful ecological and evolutionary mechanisms that shape the degree of specialization in community associations. However, here we show that both unweighted network metrics (connectance, nestedness, and degree distribution) and weighted network metrics (interaction evenness, interaction strength asymmetry) are strongly constrained and biased by the number of observations. Rarely observed species are inevitably regarded as "specialists," irrespective of their actual associations, leading to biased estimates of specialization. Consequently, a skewed distribution of species observation records (such as the lognormal), combined with a relatively low sampling density typical for ecological data, already generates a "nested" and poorly "connected" network with "asymmetric interaction strengths" when interactions are neutral. This is confirmed by null model simulations of bipartite networks, assuming that partners associate randomly in the absence of any specialization and any variation in the correspondence of biological traits between associated species (trait matching). Variation in the skewness of the frequency distribution fundamentally changes the outcome of network metrics. Therefore, interpretation of network metrics in terms of fundamental specialization and trait matching requires an appropriate control for such severe constraints imposed by information deficits. When using an alternative approach that controls for these effects, most natural networks of mutualistic or antagonistic systems show a significantly higher degree of reciprocal specialization (exclusiveness) than expected under neutral conditions. A higher exclusiveness is coherent with a tighter coevolution and suggests a lower ecological redundancy than implied by nested networks.
Source-sink interaction: a century old concept under the light of modern molecular systems biology.
Chang, Tian-Gen; Zhu, Xin-Guang; Raines, Christine
2017-07-20
Many approaches to engineer source strength have been proposed to enhance crop yield potential. However, a well-co-ordinated source-sink relationship is required finally to realize the promised increase in crop yield potential in the farmer's field. Source-sink interaction has been intensively studied for decades, and a vast amount of knowledge about the interaction in different crops and under different environments has been accumulated. In this review, we first introduce the basic concepts of source, sink and their interactions, then summarize current understanding of how source and sink can be manipulated through both environmental control and genetic manipulations. We show that the source-sink interaction underlies the diverse responses of crops to the same perturbations and argue that development of a molecular systems model of source-sink interaction is required towards a rational manipulation of the source-sink relationship for increased yield. We finally discuss both bottom-up and top-down routes to develop such a model and emphasize that a community effort is needed for development of this model. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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Ikuhiro Yamaguchi
Full Text Available Time delay is known to induce sustained oscillations in many biological systems such as electroencephalogram (EEG activities and gene regulations. Furthermore, interactions among delay-induced oscillations can generate complex collective rhythms, which play important functional roles. However, due to their intrinsic infinite dimensionality, theoretical analysis of interacting delay-induced oscillations has been limited. Here, we show that the two primary methods for finite-dimensional limit cycles, namely, the center manifold reduction in the vicinity of the Hopf bifurcation and the phase reduction for weak interactions, can successfully be applied to interacting infinite-dimensional delay-induced oscillations. We systematically derive the complex Ginzburg-Landau equation and the phase equation without delay for general interaction networks. Based on the reduced low-dimensional equations, we demonstrate that diffusive (linearly attractive coupling between a pair of delay-induced oscillations can exhibit nontrivial amplitude death and multimodal phase locking. Our analysis provides unique insights into experimentally observed EEG activities such as sudden transitions among different phase-locked states and occurrence of epileptic seizures.
Zon, J R
1979-01-01
Observed semiconductor properties of biological material in vitro indicate possible involvement of semiconduction in biological processes. Since in inorganic semiconductors solid-state plasma occurs, it is hypothesized that in organic semiconductors solid-state plasma similarly occurs. Some results of experimental investigation of resonant effects of microwaves in biological systems are considered in the light of that hypothesis. The conditions necessary for the existence of physical plasma in biological solid structures are discussed, and certain parameters of physical plasma in these structures are evaluated. Its is proposed that microwave radiation may support or damp plasma oscillations, thereby stimulating or suppressing biological functions.
Graph Drawing Aesthetics-Created by Users, Not Algorithms.
Purchase, H C; Pilcher, C; Plimmer, B
2012-01-01
Prior empirical work on layout aesthetics for graph drawing algorithms has concentrated on the interpretation of existing graph drawings. We report on experiments which focus on the creation and layout of graph drawings: participants were asked to draw graphs based on adjacency lists, and to lay them out "nicely." Two interaction methods were used for creating the drawings: a sketch interface which allows for easy, natural hand movements, and a formal point-and-click interface similar to a typical graph editing system. We find, in common with many other studies, that removing edge crossings is the most significant aesthetic, but also discover that aligning nodes and edges to an underlying grid is important. We observe that the aesthetics favored by participants during creation of a graph drawing are often not evident in the final product and that the participants did not make a clear distinction between the processes of creation and layout. Our results suggest that graph drawing systems should integrate automatic layout with the user's manual editing process, and provide facilities to support grid-based graph creation.
Video tracking based on sequential particle filtering on graphs.
Pan, Pan; Schonfeld, Dan
2011-06-01
In this paper, we develop a novel solution for particle filtering on general graphs. We provide an exact solution for particle filtering on directed cycle-free graphs. The proposed approach relies on a partial-order relation in an antichain decomposition that forms a high-order Markov chain over the partitioned graph. We subsequently derive a closed-form sequential updating scheme for conditional density propagation using particle filtering on directed cycle-free graphs. We also provide an approximate solution for particle filtering on general graphs by splitting graphs with cycles into multiple directed cycle-free subgraphs. We then use the sequential updating scheme by alternating among the directed cycle-free subgraphs to obtain an estimate of the density propagation. We rely on the proposed method for particle filtering on general graphs for two video tracking applications: 1) object tracking using high-order Markov chains; and 2) distributed multiple object tracking based on multi-object graphical interaction models. Experimental results demonstrate the improved performance of the proposed approach to particle filtering on graphs compared with existing methods for video tracking.
ESL students learning biology: The role of language and social interactions
Jaipal, Kamini
This study explored three aspects related to ESL students in a mainstream grade 11 biology classroom: (1) the nature of students' participation in classroom activities, (2) the factors that enhanced or constrained ESL students' engagement in social interactions, and (3) the role of language in the learning of science. Ten ESL students were observed over an eight-month period in this biology classroom. Data were collected using qualitative research methods such as participant observation, audio-recordings of lessons, field notes, semi-structured interviews, short lesson recall interviews and students' written work. The study was framed within sociocultural perspectives, particularly the social constructivist perspectives of Vygotsky (1962, 1978) and Wertsch (1991). Data were analysed with respect to the three research aspects. Firstly, the findings showed that ESL students' preferred and exhibited a variety of participation practices that ranged from personal-individual to socio-interactive in nature. Both personal-individual and socio-interactive practices appeared to support science and language learning. Secondly, the findings indicated that ESL students' engagement in classroom social interactions was most likely influenced by the complex interactions between a number of competing factors at the individual, interpersonal and community/cultural levels (Rogoff, Radziszewska, & Masiello, 1995). In this study, six factors that appeared to enhance or constrain ESL students' engagement in classroom social interactions were identified. These factors were socio-cultural factors, prior classroom practice, teaching practices, affective factors, English language proficiency, and participation in the research project. Thirdly, the findings indicated that language played a significant mediational role in ESL students' learning of science. The data revealed that the learning of science terms and concepts can be explained by a functional model of language that includes: (1
Kanzaki, Nana; Miwa, Kazuhisa
2012-08-01
The comprehension of graphs is achieved through interaction between bottom-up and top-down processing. This study experimentally investigated the interaction between the graph representations determining bottom-up processing and the reader's perspective relating to top-down processing. Different representations on graphs generated from an identical data set elicited different interpretations of the graphs. We call this the "representation effect" on graph comprehension. In Experiment 1, we confirmed the characteristic of the bottom-up process of graph comprehension by using a set of line graphs which were identical in perceptual characteristics. In Experiments 2A and 2B, the participants were given a perspective for reading the graphs, and then they interpreted the graphs. The results showed that this perspective affected their comprehension of the graphs. Previous studies have shown that top-down processing may not be compatible with bottom-up processing in graph comprehension. However, our result indicated that top-down processing controlled by a perspective for reading the graph was not inconsistent with bottom-up processing, and therefore does not violate bottom-up processing.
Directory of Open Access Journals (Sweden)
Divyaswetha Peddinti
Full Text Available BACKGROUND: Oocytes are the female gametes which establish the program of life after fertilization. Interactions between oocyte and the surrounding cumulus cells at germinal vesicle (GV stage are considered essential for proper maturation or 'programming' of oocytes, which is crucial for normal fertilization and embryonic development. However, despite its importance, little is known about the molecular events and pathways involved in this bidirectional communication. METHODOLOGY/PRINCIPAL FINDINGS: We used differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT on bovine GV oocyte and cumulus cells and identified 811 and 1247 proteins in GV oocyte and cumulus cells, respectively; 371 proteins were significantly differentially expressed between each cell type. Systems biology modeling, which included Gene Ontology (GO and canonical genetic pathway analysis, showed that cumulus cells have higher expression of proteins involved in cell communication, generation of precursor metabolites and energy, as well as transport than GV oocytes. Our data also suggests a hypothesis that oocytes may depend on the presence of cumulus cells to generate specific cellular signals to coordinate their growth and maturation. CONCLUSIONS/SIGNIFICANCE: Systems biology modeling of bovine oocytes and cumulus cells in the context of GO and protein interaction networks identified the signaling pathways associated with the proteins involved in cell-to-cell signaling biological process that may have implications in oocyte competence and maturation. This first comprehensive systems biology modeling of bovine oocytes and cumulus cell proteomes not only provides a foundation for signaling and cell physiology at the GV stage of oocyte development, but are also valuable for comparative studies of other stages of oocyte development at the molecular level.
Graph theoretical model of a sensorimotor connectome in zebrafish.
Directory of Open Access Journals (Sweden)
Michael Stobb
Full Text Available Mapping the detailed connectivity patterns (connectomes of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line sensorimotor pathway in zebrafish. The model includes 2,616 neurons and 167,114 synaptic connections. Model neurons represent known cell types in zebrafish larvae, and connections were set stochastically following rules based on biological literature. Thus, our model is a uniquely detailed computational representation of a vertebrate connectome. The connectome has low overall connection density, with 2.45% of all possible connections, a value within the physiological range. We used graph theoretical tools to compare the zebrafish connectome graph to small-world, random and structured random graphs of the same size. For each type of graph, 100 randomly generated instantiations were considered. Degree distribution (the number of connections per neuron varied more in the zebrafish graph than in same size graphs with less biological detail. There was high local clustering and a short average path length between nodes, implying a small-world structure similar to other neural connectomes and complex networks. The graph was found not to be scale-free, in agreement with some other neural connectomes. An experimental lesion was performed that targeted three model brain neurons, including the Mauthner neuron, known to control fast escape turns. The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome.
Doostparast Torshizi, Abolfazl; Petzold, Linda R
2018-01-01
Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects of different biological data types can boost learning capabilities and lead to a better understanding of the underlying interactions among molecular levels. In this paper we present a graph-based semi-supervised classification algorithm that incorporates latent biological knowledge in the form of biological pathways with gene expression and DNA methylation data. The process of graph construction from biological pathways is based on detecting condition-responsive genes, where 3 sets of genes are finally extracted: all condition responsive genes, high-frequency condition-responsive genes, and P-value-filtered genes. The proposed approach is applied to ovarian cancer data downloaded from the Human Genome Atlas. Extensive numerical experiments demonstrate superior performance of the proposed approach compared to other state-of-the-art algorithms, including the latest graph-based classification techniques. Simulation results demonstrate that integrating various data types enhances classification performance and leads to a better understanding of interrelations between diverse omics data types. The proposed approach outperforms many of the state-of-the-art data integration algorithms. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Graphs cospectral with a friendship graph or its complement
Directory of Open Access Journals (Sweden)
Alireza Abdollahi
2013-12-01
Full Text Available Let $n$ be any positive integer and let $F_n$ be the friendship (or Dutch windmill graph with $2n+1$ vertices and $3n$ edges. Here we study graphs with the same adjacency spectrum as the $F_n$. Two graphs are called cospectral if the eigenvalues multiset of their adjacency matrices are the same. Let $G$ be a graph cospectral with $F_n$. Here we prove that if $G$ has no cycle of length $4$ or $5$, then $Gcong F_n$. Moreover if $G$ is connected and planar then $Gcong F_n$.All but one of connected components of $G$ are isomorphic to $K_2$.The complement $overline{F_n}$ of the friendship graph is determined by its adjacency eigenvalues, that is, if $overline{F_n}$ is cospectral with a graph $H$, then $Hcong overline{F_n}$.
Baenziger, John E; daCosta, Corrie J B
2013-03-01
Lipids are potent modulators of the Torpedo nicotinic acetylcholine receptor. Lipids influence nicotinic receptor function by allosteric mechanisms, stabilizing varying proportions of pre-existing resting, open, desensitized, and uncoupled conformations. Recent structures reveal that lipids could alter function by modulating transmembrane α-helix/α-helix packing, which in turn could alter the conformation of the allosteric interface that links the agonist-binding and transmembrane pore domains-this interface is essential in the coupling of agonist binding to channel gating. We discuss potential mechanisms by which lipids stabilize different conformational states in the context of the hypothesis that lipid-nicotinic receptor interactions modulate receptor function at biological synapses.
Setchell, Joanna M; Fairet, Emilie; Shutt, Kathryn; Waters, Siân; Bell, Sandra
2017-01-01
Biodiversity conservation is one of the grand challenges facing society. Many people interested in biodiversity conservation have a background in wildlife biology. However, the diverse social, cultural, political, and historical factors that influence the lives of people and wildlife can be investigated fully only by incorporating social science methods, ideally within an interdisciplinary framework. Cultural hierarchies of knowledge and the hegemony of the natural sciences create a barrier to interdisciplinary understandings. Here, we review three different projects that confront this difficulty, integrating biological and ethnographic methods to study conservation problems. The first project involved wildlife foraging on crops around a newly established national park in Gabon. Biological methods revealed the extent of crop loss, the species responsible, and an effect of field isolation, while ethnography revealed institutional and social vulnerability to foraging wildlife. The second project concerned great ape tourism in the Central African Republic. Biological methods revealed that gorilla tourism poses risks to gorillas, while ethnography revealed why people seek close proximity to gorillas. The third project focused on humans and other primates living alongside one another in Morocco. Incorporating shepherds in the coproduction of ecological knowledge about primates built trust and altered attitudes to the primates. These three case studies demonstrate how the integration of biological and social methods can help us to understand the sustainability of human-wildlife interactions, and thus promote coexistence. In each case, an integrated biosocial approach incorporating ethnographic data produced results that would not otherwise have come to light. Research that transcends conventional academic boundaries requires the openness and flexibility to move beyond one's comfort zone to understand and acknowledge the legitimacy of "other" kinds of knowledge. It is
Social-Biological Interactions in Oral Disease: A 'Cells to Society' View.
Directory of Open Access Journals (Sweden)
Noha Gomaa
Full Text Available Oral diseases constitute a major worldwide public health problem, with their burden concentrating in socially disadvantaged and less affluent groups of the population, resulting in significant oral health inequalities. Biomedical and behavioural approaches have proven relatively ineffective in reducing these inequalities, and have potentially increased the health gap between social groups. Some suggest this stems from a lack of understanding of how the social and psychosocial contexts in which behavioural and biological changes occur influence oral disease. To unravel the pathways through which social factors affect oral health outcomes, a better understanding is thus needed of how the social 'gets under the skin,' or becomes embodied, to alter the biological. In this paper, we present the current knowledge on the interplay between social and biological factors in oral disease. We first provide an overview of the process of embodiment in chronic disease and then evaluate the evidence on embodiment in oral disease by reviewing published studies in this area. Results show that, in periodontal disease, income, education and perceived stress are correlated with elevated levels of stress hormones, disrupted immune biomarkers and increased allostatic load. Similarly, socioeconomic position and increased financial stress are related to increased stress hormones and cariogenic bacterial counts in dental caries. Based on these results, we propose a dynamic model depicting social-biological interactions that illustrates potential interdependencies between social and biological factors that lead to poor oral health. This work and the proposed model may aid in developing a better understanding of the causes of oral health inequalities and implicate the importance of addressing the social determinants of oral health in innovating public health interventions.
Social-Biological Interactions in Oral Disease: A 'Cells to Society' View.
Gomaa, Noha; Glogauer, Michael; Tenenbaum, Howard; Siddiqi, Arjumand; Quiñonez, Carlos
2016-01-01
Oral diseases constitute a major worldwide public health problem, with their burden concentrating in socially disadvantaged and less affluent groups of the population, resulting in significant oral health inequalities. Biomedical and behavioural approaches have proven relatively ineffective in reducing these inequalities, and have potentially increased the health gap between social groups. Some suggest this stems from a lack of understanding of how the social and psychosocial contexts in which behavioural and biological changes occur influence oral disease. To unravel the pathways through which social factors affect oral health outcomes, a better understanding is thus needed of how the social 'gets under the skin,' or becomes embodied, to alter the biological. In this paper, we present the current knowledge on the interplay between social and biological factors in oral disease. We first provide an overview of the process of embodiment in chronic disease and then evaluate the evidence on embodiment in oral disease by reviewing published studies in this area. Results show that, in periodontal disease, income, education and perceived stress are correlated with elevated levels of stress hormones, disrupted immune biomarkers and increased allostatic load. Similarly, socioeconomic position and increased financial stress are related to increased stress hormones and cariogenic bacterial counts in dental caries. Based on these results, we propose a dynamic model depicting social-biological interactions that illustrates potential interdependencies between social and biological factors that lead to poor oral health. This work and the proposed model may aid in developing a better understanding of the causes of oral health inequalities and implicate the importance of addressing the social determinants of oral health in innovating public health interventions.
X-Graphs: Language and Algorithms for Heterogeneous Graph Streams
2017-09-01
parallel implementations for many key graph algorithms, conversions between tables and graphs and Python language bindings. SNAP is widely deployed...1. We have used Delite to develop a suite of DSLs for data analysis (query processing, machine learning , and graph processing). Approved for Public...range of users, interested in network analysis: support for Python - a major programming language for data scientists, documentation, tutorials, and
Energy Technology Data Exchange (ETDEWEB)
Graves, David Barry [Univ. California, Berkeley, CA (United States); Oehrlein, Gottlieb [Univ. of Maryland, College Park, MD (United States)
2014-09-01
Low temperature plasma (LTP) treatment of biological tissue is a promising path toward sterilization of bacteria due to its versatility and ability to operate under well-controlled and relatively mild conditions. The present collaborative research of an interdisciplinary team of investigators at University of Maryland, College Park (UMD), and University of California, Berkeley (UCB) focused on establishing our knowledge based with regard to low temperature plasma-induced chemical modifications in biomolecules that result in inactivation due to various plasma species, including ions, reactive radicals, and UV/VUV photons. The overall goals of the project were to identify and quantify the mechanisms by which low and atmospheric pressure plasma deactivates endotoxic biomolecules. Additionally, we wanted to understand the mechanism by which atmospheric pressure plasmas (APP) modify surfaces and how these modifications depend on the interaction of APP with the environment. Various low pressure plasma sources, a vacuum beam system and several atmospheric pressure plasma sources were used to accomplish this. In our work we elucidated for the first time the role of ions, VUV photons and radicals in biological deactivation of representative biomolecules, both in a UHV beam system and an inductively coupled, low pressure plasma system, and established the associated atomistic biomolecule changes. While we showed that both ions and VUV photons can be very efficient in deactivation of biomolecules, significant etching and/or deep modification (~200 nm) accompanied these biological effects. One of the most important findings in this work is the significant radical-induced deactivation and surface modification can occur with minimal etching. However, if radical fluxes and corresponding etch rates are relatively high, for example at atmospheric pressure, endotoxic biomolecule film inactivation may require near-complete removal of the film. These findings motivated further work at
Estimating the Effects of Habitat and Biological Interactions in an Avian Community.
Directory of Open Access Journals (Sweden)
Robert M Dorazio
Full Text Available We used repeated sightings of individual birds encountered in community-level surveys to investigate the relative roles of habitat and biological interactions in determining the distribution and abundance of each species. To analyze these data, we developed a multispecies N-mixture model that allowed estimation of both positive and negative correlations between abundances of different species while also estimating the effects of habitat and the effects of errors in detection of each species. Using a combination of single- and multispecies N-mixture modeling, we examined for each species whether our measures of habitat were sufficient to account for the variation in encounter histories of individual birds or whether other habitat variables or interactions with other species needed to be considered. In the community that we studied, habitat appeared to be more influential than biological interactions in determining the distribution and abundance of most avian species. Our results lend support to the hypothesis that abundances of forest specialists are negatively affected by forest fragmentation. Our results also suggest that many species were associated with particular types of vegetation as measured by structural attributes of the forests. The abundances of 6 of the 73 species observed in our study were strongly correlated. These species included large birds (American Crow (Corvus brachyrhynchos and Red-winged Blackbird (Agelaius phoeniceus that forage on the ground in open habitats and small birds (Red-eyed Vireo (Vireo olivaceus, House Wren (Troglodytes aedon, Hooded Warbler (Setophaga citrina, and Prairie Warbler (Setophaga discolor that are associated with dense shrub cover. Species abundances were positively correlated within each size group and negatively correlated between groups. Except for the American Crow, which preys on eggs and nestlings of small song birds, none of the other 5 species is known to display direct interactions, so we
Nanoparticle-nanoparticle interactions in biological media by Atomic Force Microscopy
Pyrgiotakis, Georgios; Blattmann, Christoph O.; Pratsinis, Sotiris; Demokritou, Philip
2015-01-01
Particle-particle interactions in physiological media are important determinants for nanoparticle fate and transport. Herein, such interactions are assessed by a novel Atomic Force Microscopy (AFM) based platform. Industry-relevant CeO2, Fe2O3, and SiO2 nanoparticles of various diameters were made by the flame spray pyrolysis (FSP) based Harvard Versatile Engineering Nanomaterials Generation System (Harvard VENGES). The nanoparticles were fully characterized structurally and morphologically and their properties in water and biological media were also assessed. The nanoparticles were attached on AFM tips and deposited on Si substrates to measure particle–particle interactions. The corresponding force was measured in air, water and biological media that are widely used in toxicological studies. The presented AFM based approach can be used to assess the agglomeration potential of nanoparticles in physiological fluids. The agglomeration potential of CeO2 nanoparticles in water and RPMI 1640 (Roswell Park Memorial Institute formulation 1640) was inversely proportional to their primary particle (PP) diameter, but for Fe2O3 nanoparticles, that potential is independent of PP diameter in these media. Moreover, in RPMI+10% Fetal Bovine Serum (FBS) the corona thickness and dispersibility of the CeO2 is independent of PP diameter while for Fe2O3, the corona thickness and dispersibility were inversely proportional to PP diameter. The present method can be combined with (dynamic light scattering (DLS), proteomics, and computer simulations to understand the nano-bio interactions, with emphasis on the agglomeration potential of nanoparticles and their transport in physiological media. PMID:23978039
Estimating the effects of habitat and biological interactions in an avian community
Dorazio, Robert M.; Connor, Edward F.; Askins, Robert A.
2015-01-01
We used repeated sightings of individual birds encountered in community-level surveys to investigate the relative roles of habitat and biological interactions in determining the distribution and abundance of each species. To analyze these data, we developed a multispecies N-mixture model that allowed estimation of both positive and negative correlations between abundances of different species while also estimating the effects of habitat and the effects of errors in detection of each species. Using a combination of single- and multispecies N-mixture modeling, we examined for each species whether our measures of habitat were sufficient to account for the variation in encounter histories of individual birds or whether other habitat variables or interactions with other species needed to be considered. In the community that we studied, habitat appeared to be more influential than biological interactions in determining the distribution and abundance of most avian species. Our results lend support to the hypothesis that abundances of forest specialists are negatively affected by forest fragmentation. Our results also suggest that many species were associated with particular types of vegetation as measured by structural attributes of the forests. The abundances of 6 of the 73 species observed in our study were strongly correlated. These species included large birds (American Crow and Red-winged Blackbird) that forage on the ground in open habitats and small birds (Red-eyed Vireo, House Wren, Hooded Warbler, and Prairie Warbler) that are associated with dense shrub cover. Species abundances were positively correlated within each size group and negatively correlated between groups. Except for the American Crow, which preys on eggs and nestlings of small song birds, none of the other 5 species is known to display direct interactions, so we suspect that the correlations may have been associated with species-specific responses to habitat components not adequately measured by
Riggins-Caspers, Kristin M; Cadoret, Remi J; Knutson, John F; Langbehn, Douglas
2003-05-01
Using an adoption paradigm, the Bioecological Model of development proposed by Bronfenbrenner and Ceci in 1994 was tested by concurrently modeling for biology-environment interaction and evocative biology-environment correlation. A sample of 150 adult adoptees (ages, 18-45 years) provided retrospective reports of harsh adoptive parent discipline, which served as the environmental independent variables. Birth parent psychopathology served as the biological predictor. The dependent variables were retrospective adoptee and adoptive parent reports on adolescent aggressive and conduct-disordered behaviors. Finally, adoptees were classified as experiencing contextual environmental risk using the presence of two or more adverse factors in the adoptive home (e.g., adoptive parent psychopathology) as the cutoff. The contextual environment was found to moderate the biological process of evocative biology-environment correlation, providing empirical support for the Bronfenbrenner and Ceci (1994) Bioecological Model.
Entanglement of bosonic modes in symmetric graphs
International Nuclear Information System (INIS)
Asoudeh, M.; Karimipour, V.
2005-01-01
The ground and thermal states of a quadratic Hamiltonian representing the interaction of bosonic modes or particles are always Gaussian states. We investigate the entanglement properties of these states for the case where the interactions are represented by harmonic forces acting along the edges of symmetric graphs - i.e., one-, two-, and three-dimensional rectangular lattices, mean-field clusters, and platonic solids. We determine the entanglement of formation (EOF) as a function of the interaction strength, calculate the maximum EOF in each case, and compare these values with the bounds found previously for quadratic Hamiltonians
Cryptohermitian Hamiltonians on Graphs. II. Hermitizations
Czech Academy of Sciences Publication Activity Database
Znojil, Miloslav
2011-01-01
Roč. 50, č. 5 (2011), s. 1614-1627 ISSN 0020-7748 R&D Projects: GA MŠk LC06002; GA ČR GAP203/11/1433 Institutional research plan: CEZ:AV0Z10480505 Keywords : Quantum graphs * Non-Hermitian interactions * Pseudometrics and metrics Subject RIV: BE - Theoretical Physics Impact factor: 0.845, year: 2011
Cantor spectra of magnetic chain graphs
Czech Academy of Sciences Publication Activity Database
Exner, Pavel; Vašata, D.
2017-01-01
Roč. 50, č. 16 (2017), č. článku 165201. ISSN 1751-8113 R&D Projects: GA ČR GA17-01706S Institutional support: RVO:61389005 Keywords : quantum chain graph * magnetic field * almost Mathieu operator * Cantor spectrum Subject RIV: BE - Theoretical Physics OBOR OECD: Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect) Impact factor: 1.857, year: 2016
Caruso, Francesco; Darnowski, James W; Opazo, Cristian; Goldberg, Alexander; Kishore, Nina; Agoston, Elin S; Rossi, Miriam
2010-01-28
The taurine amino-acid derivative, taurolidine, bis-(1,1-dioxoperhydro-1,2,4-thiabiazinyl-4)methane, shows broad antibacterial action against gram-positive and gram-negative bacteria, mycobacteria and some clinically relevant fungi. It inhibits, in vitro, the adherence of Escherichia coli and Staphylococcus aureus to human epithelial and fibroblast cells. Taurolidine is unstable in aqueous solution and breaks down into derivatives which are thought to be responsible for the biological activity. To understand the taurolidine antibacterial mechanism of action, we provide the experimental single crystal X-ray diffraction results together with theoretical methods to characterize the hydrolysis/decomposition reactions of taurolidine. The crystal structure features two independent molecules linked through intermolecular H-bonds with one of them somewhat positively charged. Taurolidine in a biological environment exists in equilibrium with taurultam derivatives and this is described theoretically as a 2-step process without an energy barrier: formation of cationic taurolidine followed by a nucleophilic attack of O(hydroxyl) on the exocyclic C(methylene). A concerted mechanism describes the further hydrolysis of the taurolidine derivative methylol-taurultam. The interaction of methylol-taurultam with the diaminopimelic NH(2) group in the E. coli bacteria cell wall (peptidoglycan) has a negative DeltaG value (-38.2 kcal/mol) but a high energy barrier (45.8 kcal/mol) suggesting no reactivity. On the contrary, taurolidine docking into E. coli fimbriae protein, responsible for bacteria adhesion to the bladder epithelium, shows it has higher affinity than mannose (the natural substrate), whereas methylol-taurultam and taurultam are less tightly bound. Since taurolidine is readily available because it is administered in high doses after peritonitis surgery, it may successfully compete with mannose explaining its effectiveness against bacterial infections at laparoscopic lesions.
Directory of Open Access Journals (Sweden)
Francesco Caruso
Full Text Available The taurine amino-acid derivative, taurolidine, bis-(1,1-dioxoperhydro-1,2,4-thiabiazinyl-4methane, shows broad antibacterial action against gram-positive and gram-negative bacteria, mycobacteria and some clinically relevant fungi. It inhibits, in vitro, the adherence of Escherichia coli and Staphylococcus aureus to human epithelial and fibroblast cells. Taurolidine is unstable in aqueous solution and breaks down into derivatives which are thought to be responsible for the biological activity. To understand the taurolidine antibacterial mechanism of action, we provide the experimental single crystal X-ray diffraction results together with theoretical methods to characterize the hydrolysis/decomposition reactions of taurolidine. The crystal structure features two independent molecules linked through intermolecular H-bonds with one of them somewhat positively charged. Taurolidine in a biological environment exists in equilibrium with taurultam derivatives and this is described theoretically as a 2-step process without an energy barrier: formation of cationic taurolidine followed by a nucleophilic attack of O(hydroxyl on the exocyclic C(methylene. A concerted mechanism describes the further hydrolysis of the taurolidine derivative methylol-taurultam. The interaction of methylol-taurultam with the diaminopimelic NH(2 group in the E. coli bacteria cell wall (peptidoglycan has a negative DeltaG value (-38.2 kcal/mol but a high energy barrier (45.8 kcal/mol suggesting no reactivity. On the contrary, taurolidine docking into E. coli fimbriae protein, responsible for bacteria adhesion to the bladder epithelium, shows it has higher affinity than mannose (the natural substrate, whereas methylol-taurultam and taurultam are less tightly bound. Since taurolidine is readily available because it is administered in high doses after peritonitis surgery, it may successfully compete with mannose explaining its effectiveness against bacterial infections at
Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
Directory of Open Access Journals (Sweden)
Mihai V. Putz
2016-07-01
Full Text Available Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding and quantitative (for predicting mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD as the revived precursor for comparative molecular field analyses (CoMFA and comparative molecular similarity indices analysis (CoMSIA; all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy-methyl]-6-(phenylthiothymine congeners’ (HEPT ligands antiviral activity against Human Immunodeficiency Virus of first type (HIV-1 and new pharmacophores in treating severe genetic disorders (like depression and psychosis, respectively, all involving 3D pharmacophore interactions.
The One Universal Graph — a free and open graph database
Ng, Liang S.; Champion, Corbin
2016-02-01
Recent developments in graph database mostly are huge projects involving big organizations, big operations and big capital, as the name Big Data attests. We proposed the concept of One Universal Graph (OUG) which states that all observable and known objects and concepts (physical, conceptual or digitally represented) can be connected with only one single graph; furthermore the OUG can be implemented with a very simple text file format with free software, capable of being executed on Android or smaller devices. As such the One Universal Graph Data Exchange (GOUDEX) modules can potentially be installed on hundreds of millions of Android devices and Intel compatible computers shipped annually. Coupled with its open nature and ability to connect to existing leading search engines and databases currently in operation, GOUDEX has the potential to become the largest and a better interface for users and programmers to interact with the data on the Internet. With a Web User Interface for users to use and program in native Linux environment, Free Crowdware implemented in GOUDEX can help inexperienced users learn programming with better organized documentation for free software, and is able to manage programmer's contribution down to a single line of code or a single variable in software projects. It can become the first practically realizable “Internet brain” on which a global artificial intelligence system can be implemented. Being practically free and open, One Universal Graph can have significant applications in robotics, artificial intelligence as well as social networks.
The One Universal Graph — a free and open graph database
International Nuclear Information System (INIS)
Ng, Liang S.; Champion, Corbin
2016-01-01
Recent developments in graph database mostly are huge projects involving big organizations, big operations and big capital, as the name Big Data attests. We proposed the concept of One Universal Graph (OUG) which states that all observable and known objects and concepts (physical, conceptual or digitally represented) can be connected with only one single graph; furthermore the OUG can be implemented with a very simple text file format with free software, capable of being executed on Android or smaller devices. As such the One Universal Graph Data Exchange (GOUDEX) modules can potentially be installed on hundreds of millions of Android devices and Intel compatible computers shipped annually. Coupled with its open nature and ability to connect to existing leading search engines and databases currently in operation, GOUDEX has the potential to become the largest and a better interface for users and programmers to interact with the data on the Internet. With a Web User Interface for users to use and program in native Linux environment, Free Crowdware implemented in GOUDEX can help inexperienced users learn programming with better organized documentation for free software, and is able to manage programmer's contribution down to a single line of code or a single variable in software projects. It can become the first practically realizable “Internet brain” on which a global artificial intelligence system can be implemented. Being practically free and open, One Universal Graph can have significant applications in robotics, artificial intelligence as well as social networks. (paper)
Burleigh, Scott C.
2011-01-01
Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic
Graphs Theory and Applications
Fournier, Jean-Claude
2008-01-01
This book provides a pedagogical and comprehensive introduction to graph theory and its applications. It contains all the standard basic material and develops significant topics and applications, such as: colorings and the timetabling problem, matchings and the optimal assignment problem, and Hamiltonian cycles and the traveling salesman problem, to name but a few. Exercises at various levels are given at the end of each chapter, and a final chapter presents a few general problems with hints for solutions, thus providing the reader with the opportunity to test and refine their knowledge on the
Kapus, András; Janmey, Paul
2013-07-01
From a biophysical standpoint, the interface between the cell membrane and the cytoskeleton is an intriguing site where a "two-dimensional fluid" interacts with an exceedingly complex three-dimensional protein meshwork. The membrane is a key regulator of the cytoskeleton, which not only provides docking sites for cytoskeletal elements through transmembrane proteins, lipid binding-based, and electrostatic interactions, but also serves as the source of the signaling events and molecules that control cytoskeletal organization and remolding. Conversely, the cytoskeleton is a key determinant of the biophysical and biochemical properties of the membrane, including its shape, tension, movement, composition, as well as the mobility, partitioning, and recycling of its constituents. From a cell biological standpoint, the membrane-cytoskeleton interplay underlies--as a central executor and/or regulator--a multitude of complex processes including chemical and mechanical signal transduction, motility/migration, endo-/exo-/phagocytosis, and other forms of membrane traffic, cell-cell, and cell-matrix adhesion. The aim of this article is to provide an overview of the tight structural and functional coupling between the membrane and the cytoskeleton. As biophysical approaches, both theoretical and experimental, proved to be instrumental for our understanding of the membrane/cytoskeleton interplay, this review will "oscillate" between the cell biological phenomena and the corresponding biophysical principles and considerations. After describing the types of connections between the membrane and the cytoskeleton, we will focus on a few key physical parameters and processes (force generation, curvature, tension, and surface charge) and will discuss how these contribute to a variety of fundamental cell biological functions. © 2013 American Physiological Society.
Nested Dynamic Condition Response Graphs
DEFF Research Database (Denmark)
Hildebrandt, Thomas; Mukkamala, Raghava Rao; Slaats, Tijs
2012-01-01
We present an extension of the recently introduced declarative process model Dynamic Condition Response Graphs ( DCR Graphs) to allow nested subgraphs and a new milestone relation between events. The extension was developed during a case study carried out jointly with our industrial partner...... Exformatics, a danish provider of case and workflow management systems. We formalize the semantics by giving first a map from Nested to (flat) DCR Graphs with milestones, and then extending the previously given mapping from DCR Graphs to Buchi-automata to include the milestone relation....
Graphs for information security control in software defined networks
Grusho, Alexander A.; Abaev, Pavel O.; Shorgin, Sergey Ya.; Timonina, Elena E.
2017-07-01
Information security control in software defined networks (SDN) is connected with execution of the security policy rules regulating information accesses and protection against distribution of the malicious code and harmful influences. The paper offers a representation of a security policy in the form of hierarchical structure which in case of distribution of resources for the solution of tasks defines graphs of admissible interactions in a networks. These graphs define commutation tables of switches via the SDN controller.
Quantum graphs with the Bethe-Sommerfeld property
Czech Academy of Sciences Publication Activity Database
Exner, Pavel; Turek, Ondřej
2017-01-01
Roč. 8, č. 3 (2017), s. 305-309 ISSN 2220-8054 R&D Projects: GA ČR GA17-01706S Institutional support: RVO:61389005 Keywords : periodic quantum graphs * gap number * delta-coupling * rectangular lattice graph * scale-invariant coupling * Bethe-Sommerfeld conjecture * golden mean Subject RIV: BE - Theoretical Physics OBOR OECD: Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect)
Energy Technology Data Exchange (ETDEWEB)
Maunz, Peter Lukas Wilhelm [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sterk, Jonathan David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lobser, Daniel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Parekh, Ojas D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ryan-Anderson, Ciaran [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-01-01
In recent years, advanced network analytics have become increasingly important to na- tional security with applications ranging from cyber security to detection and disruption of ter- rorist networks. While classical computing solutions have received considerable investment, the development of quantum algorithms to address problems, such as data mining of attributed relational graphs, is a largely unexplored space. Recent theoretical work has shown that quan- tum algorithms for graph analysis can be more efficient than their classical counterparts. Here, we have implemented a trapped-ion-based two-qubit quantum information proces- sor to address these goals. Building on Sandia's microfabricated silicon surface ion traps, we have designed, realized and characterized a quantum information processor using the hyperfine qubits encoded in two 171 Yb + ions. We have implemented single qubit gates using resonant microwave radiation and have employed Gate set tomography (GST) to characterize the quan- tum process. For the first time, we were able to prove that the quantum process surpasses the fault tolerance thresholds of some quantum codes by demonstrating a diamond norm distance of less than 1 . 9 x 10 [?] 4 . We used Raman transitions in order to manipulate the trapped ions' motion and realize two-qubit gates. We characterized the implemented motion sensitive and insensitive single qubit processes and achieved a maximal process infidelity of 6 . 5 x 10 [?] 5 . We implemented the two-qubit gate proposed by Molmer and Sorensen and achieved a fidelity of more than 97 . 7%.
ILIGRA : An Efficient Inverse Line Graph Algorithm
Liu, D.; Trajanovski, S.; Van Mieghem, P.
2014-01-01
This paper presents a new and efficient algorithm, ILIGRA, for inverse line graph construction. Given a line graph H, ILIGRA constructs its root graph G with the time complexity being linear in the number of nodes in H. If ILIGRA does not know whether the given graph H is a line graph, it firstly
On Graph Rewriting, Reduction and Evaluation
DEFF Research Database (Denmark)
Zerny, Ian
2010-01-01
We inter-derive two prototypical styles of graph reduction: reduction machines à la Turner and graph rewriting systems à la Barendregt et al. To this end, we adapt Danvy et al.'s mechanical program derivations from the world of terms to the world of graphs. We also outline how to inter......-derive a third style of graph reduction: a graph evaluator....
ON BIPOLAR SINGLE VALUED NEUTROSOPHIC GRAPHS
Broumi, Said; Talea, Mohamed; Bakali, Assia; Smarandache, Florentin
2016-01-01
In this article, we combine the concept of bipolar neutrosophic set and graph theory. We introduce the notions of bipolar single valued neutrosophic graphs, strong bipolar single valued neutrosophic graphs, complete bipolar single valued neutrosophic graphs, regular bipolar single valued neutrosophic graphs and investigate some of their related properties.
Using Graph Transformations and Graph Abstractions for Software Verification
Zambon, Eduardo; Ehrig, Hartmut; Rensink, Arend; Rozenberg, Grzegorz; Schurr, Andy
In this abstract we present an overview of our intended approach for the verification of software written in imperative programming languages. This approach is based on model checking of graph transition systems (GTS), where each program state is modeled as a graph and the exploration engine is
Kirchhoff index of graphs and some graph operations
Indian Academy of Sciences (India)
We define the -repetition of to be the graph obtained by joining y i to x j for each i ∈ V ( T ) and each child of . In this paper, we compute the Kirchhoff index of the -repetition of in terms of parameters of and . Also we study how K f ( G ) behaves under some graph operations such as joining vertices or ...
RANGI: a fast list-colored graph motif finding algorithm.
Rudi, Ali Gholami; Shahrivari, Saeed; Jalili, Saeed; Moghadam Kashani, Zahra Razaghi
2013-01-01
Given a multiset of colors as the query and a list-colored graph, i.e., an undirected graph with a set of colors assigned to each of its vertices, in the NP-hard list-colored graph motif problem the goal is to find the largest connected subgraph such that one can select a color from the set of colors assigned to each of its vertices to obtain a subset of the query. This problem was introduced to find functional motifs in biological networks. We present a branch-and-bound algorithm named RANGI for finding and enumerating list-colored graph motifs. As our experimental results show, RANGI's pruning methods and heuristics make it quite fast in practice compared to the algorithms presented in the literature. We also present a parallel version of RANGI that achieves acceptable scalability.
Mallick, Pankajini; Taneja, Guncha; Moorthy, Bhagavatula; Ghose, Romi
2017-06-01
Drug-metabolizing enzymes (DMEs) are primarily down-regulated during infectious and inflammatory diseases, leading to disruption in the metabolism of small molecule drugs (smds), which are increasingly being prescribed therapeutically in combination with biologics for a number of chronic diseases. The biologics may exert pro- or anti-inflammatory effect, which may in turn affect the expression/activity of DMEs. Thus, patients with infectious/inflammatory diseases undergoing biologic/smd treatment can have complex changes in DMEs due to combined effects of the disease and treatment. Areas covered: We will discuss clinical biologics-SMD interaction and regulation of DMEs during infection and inflammatory diseases. Mechanistic studies will be discussed and consequences on biologic-small molecule combination therapy on disease outcome due to changes in drug metabolism will be highlighted. Expert opinion: The involvement of immunomodulatory mediators in biologic-SMDs is well known. Regulatory guidelines recommend appropriate in vitro or in vivo assessments for possible interactions. The role of cytokines in biologic-SMDs has been documented. However, the mechanisms of drug-drug interactions is much more complex, and is probably multi-factorial. Studies aimed at understanding the mechanism by which biologics effect the DMEs during inflammation/infection are clinically important.
Graph Theory. 2. Vertex Descriptors and Graph Coloring
Directory of Open Access Journals (Sweden)
Lorentz JÄNTSCHI
2002-12-01
Full Text Available This original work presents the construction of a set of ten sequence matrices and their applications for ordering vertices in graphs. For every sequence matrix three ordering criteria are applied: lexicographic ordering, based on strings of numbers, corresponding to every vertex, extracted as rows from sequence matrices; ordering by the sum of path lengths from a given vertex; and ordering by the sum of paths, starting from a given vertex. We also examine a graph that has different orderings for the above criteria. We then proceed to demonstrate that every criterion induced its own partition of graph vertex. We propose the following theoretical result: both LAVS and LVDS criteria generate identical partitioning of vertices in any graph. Finally, a coloring of graph vertices according to introduced ordering criteria was proposed.
Klein, Thomas; Kukkonen, Jaakko; Dahl, Aslög; Bossioli, Elissavet; Baklanov, Alexander; Vik, Aasmund Fahre; Agnew, Paul; Karatzas, Kostas D; Sofiev, Mikhail
2012-12-01
This article reviews interactions and health impacts of physical, chemical, and biological weather. Interactions and synergistic effects between the three types of weather call for integrated assessment, forecasting, and communication of air quality. Today's air quality legislation falls short of addressing air quality degradation by biological weather, despite increasing evidence for the feasibility of both mitigation and adaptation policy options. In comparison with the existing capabilities for physical and chemical weather, the monitoring of biological weather is lacking stable operational agreements and resources. Furthermore, integrated effects of physical, chemical, and biological weather suggest a critical review of air quality management practices. Additional research is required to improve the coupled modeling of physical, chemical, and biological weather as well as the assessment and communication of integrated air quality. Findings from several recent COST Actions underline the importance of an increased dialog between scientists from the fields of meteorology, air quality, aerobiology, health, and policy makers.
Cui, Ya; Chen, Xiaowei; Luo, Huaxia; Fan, Zhen; Luo, Jianjun; He, Shunmin; Yue, Haiyan; Zhang, Peng; Chen, Runsheng
2016-06-01
We here present BioCircos.js, an interactive and lightweight JavaScript library especially for biological data interactive visualization. BioCircos.js facilitates the development of web-based applications for circular visualization of various biological data, such as genomic features, genetic variations, gene expression and biomolecular interactions. BioCircos.js and its manual are freely available online at http://bioinfo.ibp.ac.cn/biocircos/ rschen@ibp.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Indian Academy of Sciences (India)
I am particularly happy that the Academy is bringing out this document by Professor M S. Valiathan on Ayurvedic Biology. It is an effort to place before the scientific community, especially that of India, the unique scientific opportunities that arise out of viewing Ayurveda from the perspective of contemporary science, its tools ...
Chordal Graphs and Semidefinite Optimization
DEFF Research Database (Denmark)
Vandenberghe, Lieven; Andersen, Martin Skovgaard
2015-01-01
Chordal graphs play a central role in techniques for exploiting sparsity in large semidefinite optimization problems and in related con-vex optimization problems involving sparse positive semidefinite matrices. Chordal graph properties are also fundamental to several classical results in combinat...
DYNAMICALLY MAINTAINING THE VISIBILITY GRAPH
VEGTER, G
1991-01-01
An algorithm is presented to maintain the visibility graph of a set of N line segments in the plane in O(log2 N + K log N) time, where K is the total number of arcs of the visibility graph that are destroyed or created upon insertion or deletion of a line segment. The line segments should be
A cluster algorithm for graphs
S. van Dongen
2000-01-01
textabstractA cluster algorithm for graphs called the emph{Markov Cluster algorithm (MCL~algorithm) is introduced. The algorithm provides basically an interface to an algebraic process defined on stochastic matrices, called the MCL~process. The graphs may be both weighted (with nonnegative weight)
The planar cubic Cayley graphs
Georgakopoulos, Agelos
2018-01-01
The author obtains a complete description of the planar cubic Cayley graphs, providing an explicit presentation and embedding for each of them. This turns out to be a rich class, comprising several infinite families. He obtains counterexamples to conjectures of Mohar, Bonnington and Watkins. The author's analysis makes the involved graphs accessible to computation, corroborating a conjecture of Droms.
The planar cubic cayley graphs
Georgakopoulos, Agelos
2018-01-01
The author obtains a complete description of the planar cubic Cayley graphs, providing an explicit presentation and embedding for each of them. This turns out to be a rich class, comprising several infinite families. He obtains counterexamples to conjectures of Mohar, Bonnington and Watkins. The author's analysis makes the involved graphs accessible to computation, corroborating a conjecture of Droms.
Hoede, C.; Liu, X
1998-01-01
In continuation of the paper of Hoede and Li on word graphs for a set of prepositions, word graphs are given for adjectives, adverbs and Chinese classifier words. It is argued that these three classes of words belong to a general class of words that may be called adwords. These words express the
2005-06-01
relationship, trust, etc.) between people. • User Psychology : Clickstream graphs are bipartite graphs connecting Internet users to the websites they visit...document groups (say, science fiction novels and thrillers ), based on the word groups that occur most frequently in them. A user who prefers one
Bell inequalities for graph states
International Nuclear Information System (INIS)
Toth, G.; Hyllus, P.; Briegel, H.J.; Guehne, O.
2005-01-01
Full text: In the last years graph states have attracted an increasing interest in the field of quantum information theory. Graph states form a family of multi-qubit states which comprises many popular states such as the GHZ states and the cluster states. They also play an important role in applications. For instance, measurement based quantum computation uses graph states as resources. From a theoretical point of view, it is remarkable that graph states allow for a simple description in terms of stabilizing operators. In this contribution, we investigate the non-local properties of graph states. We derive a family of Bell inequalities which require three measurement settings for each party and are maximally violated by graph states. In turn, any graph state violates at least one of the inequalities. We show that for certain types of graph states the violation of these inequalities increases exponentially with the number of qubits. We also discuss connections to other entanglement properties such as the positively of the partial transpose or the geometric measure of entanglement. (author)
Submanifolds weakly associated with graphs
Indian Academy of Sciences (India)
theory by defining submanifolds weakly associated with graphs. We prove that, in a local sense, every submanifold satisfies such an association, and other general results. Finally, we study submanifolds associated with graphs either in low dimensions or belonging to some special families. Keywords. Almost Hermitian ...
Subgraph Enumeration in Massive Graphs
DEFF Research Database (Denmark)
Silvestri, Francesco
We consider the problem of enumerating all instances of a given sample graph in a large data graph. Our focus is on determining the input/output (I/O) complexity of this problem. Let $E$ be the number of edges in the data graph, $k=\\BO{1}$ be the number of vertexes in the sample graph, $B......$ be the block length, and $M$ be the main memory size. The main result of the paper is a randomized algorithm that enumerates all instances of the sample graph in $\\BO{E^{k/2}/\\left(BM^{k/2-1}\\right)}$ expected I/Os if the maximum vertex degree of the data graph is $\\sqrt{EM}$. Under some assumptions, the same...... bound also applies with high probability. Our algorithm is I/O optimal, in the worst-case, when the sample graph belongs to the Alon class, which includes cliques, cycles and every graph with a perfect matching: indeed, we show that any algorithm enumerating $T$ instances must always use $\\BOM...
Mechanisms of interaction and biological effects of extremely-low-frequency electromagnetic fields
Energy Technology Data Exchange (ETDEWEB)
Tenforde, T.S.
1994-07-01
Evidence is mounting, that environmental electric and magnetic fields in the extremely-low-frequency (ELF) band below 300 Hz can influence biological functions by mechanisms that are only poorly understood at the present time. The primary objectives of this paper are to review the physical properties of ELF fields, their interactions with living systems at the tissue, cellular, and subcellular levels, and the key role of cell membranes in the transduction of signals from imposed ELF fields. Topics of discussion include signal-to-noise ratios for single cells and cell aggregates, resonance phenomena involving a combination of static and ELF magnetic fields, and the possible influence of ELF fields on molecular signaling pathways that involve membrane receptors and cytoplasmic second messengers. The implications of these findings for promotion of tumor growth by ELF fields are also reviewed.
Lin, Yao; Ying, Yi-Lun; Gao, Rui; Long, Yi-Tao
2018-03-25
The nanopore can generate an electrochemical confinement for single-molecule sensing which help understand the fundamental chemical principle in nanoscale dimensions. By observing the generated ionic current, individual bond-making and bond-breaking steps, single biomolecule dynamic conformational changes and electron transfer processes that occur within pore can be monitored with high temporal and current resolution. These single-molecule studies in nanopore confinement are revealing information about the fundamental chemical and biological processes that cannot be extracted from ensemble measurements. In this concept, we introduce and discuss the electrochemical confinement effects on single-molecule covalent reactions, conformational dynamics of individual molecules and host-guest interactions in protein nanopores. Then, we extend the concept of nanopore confinement effects to confine electrochemical redox reactions in solid-state nanopores for developing new sensing mechanisms. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Collection of Features for Semantic Graphs
Energy Technology Data Exchange (ETDEWEB)
Eliassi-Rad, T; Fodor, I K; Gallagher, B
2007-05-02
Semantic graphs are commonly used to represent data from one or more data sources. Such graphs extend traditional graphs by imposing types on both nodes and links. This type information defines permissible links among specified nodes and can be represented as a graph commonly referred to as an ontology or schema graph. Figure 1 depicts an ontology graph for data from National Association of Securities Dealers. Each node type and link type may also have a list of attributes. To capture the increased complexity of semantic graphs, concepts derived for standard graphs have to be extended. This document explains briefly features commonly used to characterize graphs, and their extensions to semantic graphs. This document is divided into two sections. Section 2 contains the feature descriptions for static graphs. Section 3 extends the features for semantic graphs that vary over time.
Directory of Open Access Journals (Sweden)
Marco Raberto
Full Text Available In this paper, we outline a model of graph (or network dynamics based on two ingredients. The first ingredient is a Markov chain on the space of possible graphs. The second ingredient is a semi-Markov counting process of renewal type. The model consists in subordinating the Markov chain to the semi-Markov counting process. In simple words, this means that the chain transitions occur at random time instants called epochs. The model is quite rich and its possible connections with algebraic geometry are briefly discussed. Moreover, for the sake of simplicity, we focus on the space of undirected graphs with a fixed number of nodes. However, in an example, we present an interbank market model where it is meaningful to use directed graphs or even weighted graphs.
Quantum chaos on discrete graphs
Energy Technology Data Exchange (ETDEWEB)
Smilansky, Uzy [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Isaac Newton Institute for Mathematical Sciences, 20 Clarkson Road, Cambridge CB3 0EH (United Kingdom)
2007-07-06
Adapting a method developed for the study of quantum chaos on quantum (metric) graphs (Kottos and Smilansky 1997 Phys. Rev. Lett. 79 4794, Kottos and Smilansky 1999 Ann. Phys., NY 274 76), spectral {zeta} functions and trace formulae for discrete Laplacians on graphs are derived. This is achieved by expressing the spectral secular equation in terms of the periodic orbits of the graph and obtaining functions which belong to the class of {zeta} functions proposed originally by Ihara (1966 J. Mat. Soc. Japan 18 219) and expanded by subsequent authors (Stark and Terras 1996 Adv. Math. 121 124, Kotani and Sunada 2000 J. Math. Sci. Univ. Tokyo 7 7). Finally, a model of 'classical dynamics' on the discrete graph is proposed. It is analogous to the corresponding classical dynamics derived for quantum graphs (Kottos and Smilansky 1997 Phys. Rev. Lett. 79 4794, Kottos and Smilansky 1999 Ann. Phys., NY 274 76). (fast track communication)
International Nuclear Information System (INIS)
Geard, C.R.; Loucas, B.D.
1995-01-01
Chromosomal DNA breaks were evaluated in normal human fibroblasts after irradiation of non-cycling G1 phase cells with 90 keV·μm -1 α particles and 250 kV p X rays. Yields were measured using the premature chromosome condensation technique in interphase cells, straight after and 24 h after irradiation, and by mitotic scoring of terminal deletions following cellular release at 24 h and progression through the cell cycle. Yields were related to the frequencies of energy deposition events per cell nucleus estimated microdosimetrically for X rays and by relating fluence to nuclear cross-sectional areas for the α particles. Linear relationships were found for both radiations and at all three times post-irradiation. Initial break yields of 1.3 x 10 o and 1.6 x 10 -2 per energy deposition event for α particles and X rays respectively, changed to residual yields (24 h) of 4.0 x 10 -1 and 1.3 x 10 -3 , and for terminal deletions at mitosis to 6.0 x 10 -3 and 4.0 x 10 -5 per energy deposition event. That is, one 90 keV·μm -1 α particle is about 100 times more biologically effective than an electron track from 250 kV p X rays and greater than 99% of initially induced chromosomal DNA breaks are repaired/misrepaired before the next mitosis. Misrepair will involve illegitimate interactions and combinations of pairs of lesions, entities which pre-dominate at mitosis, while a failure to repair/misrepair resulting in relic DNA double strand breaks is likely to be of minimal consequence. Lesion interaction, proximity dependent, and largely irrespective of LET dependent lesion severity will then be the principal basis for the unwanted biological sequelae from ionising radiations. (Author)
Firman, Keith; Evans, Luke; Youell, James
2012-07-16
This review describes a European-funded project in the area of Synthetic Biology. The project seeks to demonstrate the application of engineering techniques and methodologies to the design and construction of a biosensor for detecting drug-target interactions at the single-molecule level. Production of the proteins required for the system followed the principle of previously described "bioparts" concepts (a system where a database of biological parts - promoters, genes, terminators, linking tags and cleavage sequences - is used to construct novel gene assemblies) and cassette-type assembly of gene expression systems (the concept of linking different "bioparts" to produce functional "cassettes"), but problems were quickly identified with these approaches. DNA substrates for the device were also constructed using a cassette-system. Finally, micro-engineering was used to build a magnetoresistive Magnetic Tweezer device for detection of single molecule DNA modifying enzymes (motors), while the possibility of constructing a Hall Effect version of this device was explored. The device is currently being used to study helicases from Plasmodium as potential targets for anti-malarial drugs, but we also suggest other potential uses for the device. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham
2016-03-15
People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.
Yousefi, Bardia; Loo, Chu Kiong
2014-01-01
Following the study on computational neuroscience through functional magnetic resonance imaging claimed that human action recognition in the brain of mammalian pursues two separated streams, that is, dorsal and ventral streams. It follows up by two pathways in the bioinspired model, which are specialized for motion and form information analysis (Giese and Poggio 2003). Active basis model is used to form information which is different from orientations and scales of Gabor wavelets to form a dictionary regarding object recognition (human). Also biologically movement optic-flow patterns utilized. As motion information guides share sketch algorithm in form pathway for adjustment plus it helps to prevent wrong recognition. A synergetic neural network is utilized to generate prototype templates, representing general characteristic form of every class. Having predefined templates, classifying performs based on multitemplate matching. As every human action has one action prototype, there are some overlapping and consistency among these templates. Using fuzzy optical flow division scoring can prevent motivation for misrecognition. We successfully apply proposed model on the human action video obtained from KTH human action database. Proposed approach follows the interaction between dorsal and ventral processing streams in the original model of the biological movement recognition. The attained results indicate promising outcome and improvement in robustness using proposed approach.
What will result from the interaction between functional and evolutionary biology?
Morange, Michel
2011-03-01
The modern synthesis has been considered to be wrongly called a "synthesis", since it had completely excluded embryology, and many other disciplines. The recent developments of Evo-Devo have been seen as a step in the right direction, as complementing the modern synthesis, and probably leading to a "new synthesis". My argument is that the absence of embryology from the modern synthesis was the visible sign of a more profound lack: the absence of functional biology in the evolutionary synthesis. I will consider the reasons for this absence, as well as the recent transformations which favoured a closer interaction between these two branches of biology. Then I will describe two examples of recent work in which functional and evolutionary questioning were tightly linked. The most significant part of the paper will be devoted to the transformation of evolutionary theory that can be expected from this encounter: a deep transformation, or simply an experimental confirmation of this theory? I will not choose between these two different possibilities, but will discuss some of the difficulties which make the choice problematic. Copyright © 2010 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
I. Sahul Hamid
2016-07-01
Full Text Available A set D of vertices of a graph G is called a dominating set of G if every vertex in V(G−D is adjacent to a vertex in D. A dominating set S such that the subgraph 〈S〉 induced by S has at least one isolated vertex is called an isolate dominating set. An isolate dominating set none of whose proper subset is an isolate dominating set is a minimal isolate dominating set. The minimum and maximum cardinality of a minimal isolate dominating set are called the isolate domination number γ0 and the upper isolate domination number Γ0 respectively. In this paper we initiate a study on these parameters.
Directory of Open Access Journals (Sweden)
Jean Stawiaski
2011-05-01
Full Text Available In this paper, we discuss the use of graph-cuts to merge the regions of the watershed transform optimally. Watershed is a simple, intuitive and efficient way of segmenting an image. Unfortunately it presents a few limitations such as over-segmentation and poor detection of low boundaries. Our segmentation process merges regions of the watershed over-segmentation by minimizing a specific criterion using graph-cuts optimization. Two methods will be introduced in this paper. The first is based on regions histogram and dissimilarity measures between adjacent regions. The second method deals with efficient approximation of minimal surfaces and geodesics. Experimental results show that these techniques can efficiently be used for large images segmentation when a pre-computed low level segmentation is available. We will present these methods in the context of interactive medical image segmentation.
On characterizing terrain visibility graphs
Directory of Open Access Journals (Sweden)
William Evans
2015-06-01
Full Text Available A terrain is an $x$-monotone polygonal line in the $xy$-plane. Two vertices of a terrain are mutually visible if and only if there is no terrain vertex on or above the open line segment connecting them. A graph whose vertices represent terrain vertices and whose edges represent mutually visible pairs of terrain vertices is called a terrain visibility graph. We would like to find properties that are both necessary and sufficient for a graph to be a terrain visibility graph; that is, we would like to characterize terrain visibility graphs.Abello et al. [Discrete and Computational Geometry, 14(3:331--358, 1995] showed that all terrain visibility graphs are “persistent”. They showed that the visibility information of a terrain point set implies some ordering requirements on the slopes of the lines connecting pairs of points in any realization, and as a step towards showing sufficiency, they proved that for any persistent graph $M$ there is a total order on the slopes of the (pseudo lines in a generalized configuration of points whose visibility graph is $M$.We give a much simpler proof of this result by establishing an orientation to every triple of vertices, reflecting some slope ordering requirements that are consistent with $M$ being the visibility graph, and prove that these requirements form a partial order. We give a faster algorithm to construct a total order on the slopes. Our approach attempts to clarify the implications of the graph theoretic properties on the ordering of the slopes, and may be interpreted as defining properties on an underlying oriented matroid that we show is a restricted type of $3$-signotope.
Graph embedding with rich information through heterogeneous graph
Sun, Guolei
2017-11-12
Graph embedding, aiming to learn low-dimensional representations for nodes in graphs, has attracted increasing attention due to its critical application including node classification, link prediction and clustering in social network analysis. Most existing algorithms for graph embedding only rely on the topology information and fail to use the copious information in nodes as well as edges. As a result, their performance for many tasks may not be satisfactory. In this thesis, we proposed a novel and general framework for graph embedding with rich text information (GERI) through constructing a heterogeneous network, in which we integrate node and edge content information with graph topology. Specially, we designed a novel biased random walk to explore the constructed heterogeneous network with the notion of flexible neighborhood. Our sampling strategy can compromise between BFS and DFS local search on heterogeneous graph. To further improve our algorithm, we proposed semi-supervised GERI (SGERI), which learns graph embedding in an discriminative manner through heterogeneous network with label information. The efficacy of our method is demonstrated by extensive comparison experiments with 9 baselines over multi-label and multi-class classification on various datasets including Citeseer, Cora, DBLP and Wiki. It shows that GERI improves the Micro-F1 and Macro-F1 of node classification up to 10%, and SGERI improves GERI by 5% in Wiki.
A graph spectrum based geometric biclustering algorithm.
Wang, Doris Z; Yan, Hong
2013-01-21
Biclustering is capable of performing simultaneous clustering on two dimensions of a data matrix and has many applications in pattern classification. For example, in microarray experiments, a subset of genes is co-expressed in a subset of conditions, and biclustering algorithms can be used to detect the coherent patterns in the data for further analysis of function. In this paper, we present a graph spectrum based geometric biclustering (GSGBC) algorithm. In the geometrical view, biclusters can be seen as different linear geometrical patterns in high dimensional spaces. Based on this, the modified Hough transform is used to find the Hough vector (HV) corresponding to sub-bicluster patterns in 2D spaces. A graph can be built regarding each HV as a node. The graph spectrum is utilized to identify the eigengroups in which the sub-biclusters are grouped naturally to produce larger biclusters. Through a comparative study, we find that the GSGBC achieves as good a result as GBC and outperforms other kinds of biclustering algorithms. Also, compared with the original geometrical biclustering algorithm, it reduces the computing time complexity significantly. We also show that biologically meaningful biclusters can be identified by our method from real microarray gene expression data. Copyright © 2012 Elsevier Ltd. All rights reserved.
Wardle, Karen Marie
The relationship between learning communities and student interaction and retention in community college general biology courses was investigated in this study. The purposes of the study were to discover the students' perceptions of factors influencing their desire to study science, and to examine the use of learning communities as a method of enculturation into the field of science. The learning community in the CCD science courses involved an entry-level science course that was linked with a tutorial enrichment of the underlying principles in scientific research. The coordination between the class and the learning community involved an extensive research project that incorporated important scientific principles. The project goals for student research included an understanding of the scientific method, and an increased engagement in scientific inquiry. Collaboration and communication among students was an additional goal of the leaning communities. A quasi-experiment with pre- and post-measures of student attitudes and perceptions of success in first and second semester biology courses. A premeasure was followed by a quasi experiment in which entry level biology courses were conducted using either learning communities or traditional lecture. Results show the factors students perceived as important to their success in entry-level science courses included their professors and peers. Discriminant results revealed that the factors predicted completion of the courses 75% of the time. Qualitative tests reveal that students in learning communities show a slight increase in community interactions and willingness to explore the content material beyond the material needed for the class, however these results were not significantly higher than the control courses. Future studies include collecting data on the learning communities for longer than a one-year period. The incorporation of the research projects into the courses has lasting value in terms of encouraging new
CUBu: Universal Real-Time Bundling for Large Graphs.
van der Zwan, Matthew; Codreanu, Valeriu; Telea, Alexandru
2016-12-01
Visualizing very large graphs by edge bundling is a promising method, yet subject to several challenges: speed, clutter, level-of-detail, and parameter control. We present CUBu, a framework that addresses the above problems in an integrated way. Fully GPU-based, CUBu bundles graphs of up to a million edges at interactive framerates, being over 50 times faster than comparable state-of-the-art methods, and has a simple and intuitive control of bundling parameters. CUBu extends and unifies existing bundling techniques, offering ways to control bundle shapes, separate bundles by edge direction, and shade bundles to create a level-of-detail visualization that shows both the graph core structure and its details. We demonstrate CUBu on several large graphs extracted from real-life application domains.
Drewnowski, Adam; Kawachi, Ichiro
2015-09-01
Health is shaped by both personal choices and features of the food environment. Food-choice decisions depend on complex interactions between biology and behavior, and are further modulated by the built environment and community structure. That lower-income families have lower-quality diets is well established. Yet, diet quality also varies across small geographic neighborhoods and can be influenced by transportation, retail, and ease of access to healthy foods, as well as by attitudes, beliefs, and social interactions. The learnings from the Seattle Obesity Study (SOS II) can be usefully applied to the much larger, more complex, and far more socially and ethnically diverse urban environment of New York City. The Kavli HUMAN Project (KHP) is ideally positioned to advance the understanding of health disparities by exploring the multiple underpinnings of food decision making. By combining geo-localized food shopping and consumption data with health behaviors, diet quality measures, and biomarkers, also coded by geographic location, the KHP will create the first-of-its-kind bio-behavioral, economic, and cultural atlas of diet quality and health for New York City.
Urgent Biophilia: Human-Nature Interactions and Biological Attractions in Disaster Resilience
Directory of Open Access Journals (Sweden)
Keith G. Tidball
2012-06-01
Full Text Available This contribution builds upon contemporary work on principles of biological attraction as well as earlier work on biophilia while synthesizing literatures on restorative environments, community-based ecological restoration, and both community and social-ecological disaster resilience. It suggests that when humans, faced with a disaster, as individuals and as communities and populations, seek engagement with nature to further their efforts to summon and demonstrate resilience in the face of a crisis, they exemplify an urgent biophilia. This urgent biophilia represents an important set of human-nature interactions in SES characterized by hazard, disaster, or vulnerability, often appearing in the 'backloop' of the adaptive cycle. The relationships that human-nature interactions have to other components within interdependent systems at many different scales may be one critical source of resilience in disaster and related contexts. In other words, the affinity we humans have for the rest of nature, the process of remembering that attraction, and the urge to express it through creation of restorative environments, which may also restore or increase ecological function, may confer resilience across multiple scales. In making this argument, the paper also represents a novel contribution to further theorizing alternatives to anthropocentric understandings of human-nature relations, and strongly makes the case for humans as part of, not separate from, ecosystems.
Biological Processes that Prepare Mammalian Spermatozoa to Interact with an Egg and Fertilize It
Directory of Open Access Journals (Sweden)
Daulat R. P. Tulsiani
2012-01-01
Full Text Available In the mouse and other mammals studied, including man, ejaculated spermatozoa cannot immediately fertilize an egg. They require a certain period of residence in the female genital tract to become functionally competent cells. As spermatozoa traverse through the female genital tract, they undergo multiple biochemical and physiological changes collectively referred to as capacitation. Only capacitated spermatozoa interact with the extracellular egg coat, the zona pellucida. The tight irreversible binding of the opposite gametes triggers a Ca2+-dependent signal transduction cascade. The net result is the fusion of the sperm plasma membrane and the underlying outer acrosomal membrane at multiple sites that causes the release of acrosomal contents at the site of sperm-egg adhesion. The hydrolytic action of the acrosomal enzymes released, along with the hyperactivated beat pattern of the bound spermatozoon, is important factor that directs the sperm to penetrate the egg coat and fertilize the egg. The sperm capacitation and the induction of the acrosomal reaction are Ca2+-dependent signaling events that have been of wide interest to reproductive biologists for over half a century. In this paper, we intend to discuss data from this and other laboratories that highlight the biological processes which prepare spermatozoa to interact with an egg and fertilize it.
Energy Technology Data Exchange (ETDEWEB)
Windisch, W. [Center of Life and Food Sciences, Technische Univ. Muenchen, Freising (Germany)
2002-02-01
Variations in the chemical speciation of dietary trace elements can result in the provision of different amounts of these micronutrients to the organism and might thus induce interactions with trace-element metabolism. The chemical species of Zn, Fe, Cu, and Mn can interact with other components of the diet even before reaching the site of absorption, e.g. by formation of poorly soluble complexes with phytic acid. This might considerably modify the amount of metabolically available trace elements; differences between absorptive capacity per se toward dietary species seems to be less important. Homeostasis usually limits the quantities of Zn, Fe, Cu, and Mn transported from the gut into the organism, and differences between dietary species are largely eliminated at this step. There is no homeostatic control of absorption of Se and I, and organisms seem to be passively exposed to influx of these micronutrients irrespective of dietary speciation. Inside the organism the trace elements are usually converted into a metabolically recognizable form, channeled into their biological functions, or submitted to homeostatically controlled excretion. Some dietary species can, however, be absorbed as intact compounds. As long as the respective quantities of trace elements are not released from their carriers, they are not recognized properly by trace element metabolism and might induce tissue accumulation, irrespective of homeostatic control. (orig.)
Zhong, Xiao; Sun, Peide; Song, Yingqi; Wang, Ruyi; Fang, Zhiguo
2010-11-01
Based on the fully coupled activated sludge model (FCASM), the novel model Tubificidae -Fully Coupled Activated Sludge Model-hydraulic (T-FCASM-Hydro), has been developed in our previous work. T-FCASM-Hydro not only describe the interactive system between Tubificidae and functional microorganisms for the sludge reduction and nutrient removal simultaneously, but also considere the interaction between biological and hydraulic field, After calibration and validation of T-FCASM-Hydro at Zhuji Feida-hongyu Wastewater treatment plant (WWTP) in Zhejiang province, T-FCASM-Hydro was applied for determining optimal operating condition in the WWTP. Simulation results showed that nitrogen and phosphorus could be removed efficiently, and the efficiency of NH4+-N removal enhanced with increase of DO concentration. At a certain low level of DO concentration in the aerobic stage, shortcut nitrification-denitrification dominated in the process of denitrification in the novel system. However, overhigh agitation (>6 mgṡL-1) could result in the unfavorable feeding behavior of Tubificidae because of the strong flow disturbance, which might lead to low rate of sludge reduction. High sludge reduction rate and high removal rate of nitrogen and phosphorus could be obtained in the new-style oxidation ditch when DO concentration at the aerobic stage with Tubificidae was maintained at 3.6 gṡm-3.
On some properties of doughnut graphs
Directory of Open Access Journals (Sweden)
Md. Rezaul Karim
2016-08-01
Full Text Available The class of doughnut graphs is a subclass of 5-connected planar graphs. It is known that a doughnut graph admits a straight-line grid drawing with linear area, the outerplanarity of a doughnut graph is 3, and a doughnut graph is k-partitionable. In this paper we show that a doughnut graph exhibits a recursive structure. We also give an efficient algorithm for finding a shortest path between any pair of vertices in a doughnut graph. We also propose a nice application of a doughnut graph based on its properties.
Completeness and regularity of generalized fuzzy graphs.
Samanta, Sovan; Sarkar, Biswajit; Shin, Dongmin; Pal, Madhumangal
2016-01-01
Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems. Generalized fuzzy graphs are appropriate to avoid such restrictions. In this study generalized fuzzy graphs are introduced. In this study, matrix representation of generalized fuzzy graphs is described. Completeness and regularity are two important parameters of graph theory. Here, regular and complete generalized fuzzy graphs are introduced. Some properties of them are discussed. After that, effective regular graphs are exemplified.
Comparison and Enumeration of Chemical Graphs
Akutsu, Tatsuya; Nagamochi, Hiroshi
2013-01-01
Chemical compounds are usually represented as graph structured data in computers. In this review article, we overview several graph classes relevant to chemical compounds and the computational complexities of several fundamental problems for these graph classes. In particular, we consider the following problems: determining whether two chemical graphs are identical, determining whether one input chemical graph is a part of the other input chemical graph, finding a maximum common part of two input graphs, finding a reaction atom mapping, enumerating possible chemical graphs, and enumerating stereoisomers. We also discuss the relationship between the fifth problem and kernel functions for chemical compounds. PMID:24688697
Mango: combining and analyzing heterogeneous biological networks.
Chang, Jennifer; Cho, Hyejin; Chou, Hui-Hsien
2016-01-01
Heterogeneous biological data such as sequence matches, gene expression correlations, protein-protein interactions, and biochemical pathways can be merged and analyzed via graphs, or networks. Existing software for network analysis has limited scalability to large data sets or is only accessible to software developers as libraries. In addition, the polymorphic nature of the data sets requires a more standardized method for integration and exploration. Mango facilitates large network analyses with its Graph Exploration Language, automatic graph attribute handling, and real-time 3-dimensional visualization. On a personal computer Mango can load, merge, and analyze networks with millions of links and can connect to online databases to fetch and merge biological pathways. Mango is written in C++ and runs on Mac OS, Windows, and Linux. The stand-alone distributions, including the Graph Exploration Language integrated development environment, are freely available for download from http://www.complex.iastate.edu/download/Mango. The Mango User Guide listing all features can be found at http://www.gitbook.com/book/j23414/mango-user-guide.
Ahmed, Shaimaa; Vepuri, Suresh B; Kalhapure, Rahul S; Govender, Thirumala
2016-07-21
Dendrimers have emerged as novel and efficient materials that can be used as therapeutic agents/drugs or as drug delivery carriers to enhance therapeutic outcomes. Molecular dendrimer interactions are central to their applications and realising their potential. The molecular interactions of dendrimers with drugs or other materials in drug delivery systems or drug conjugates have been extensively reported in the literature. However, despite the growing application of dendrimers as biologically active materials, research focusing on the mechanistic analysis of dendrimer interactions with therapeutic biological targets is currently lacking in the literature. This comprehensive review on dendrimers over the last 15 years therefore attempts to identify the reasons behind the apparent lack of dendrimer-receptor research and proposes approaches to address this issue. The structure, hierarchy and applications of dendrimers are briefly highlighted, followed by a review of their various applications, specifically as biologically active materials, with a focus on their interactions at the target site. It concludes with a technical guide to assist researchers on how to employ various molecular modelling and computational approaches for research on dendrimer interactions with biological targets at a molecular level. This review highlights the impact of a mechanistic analysis of dendrimer interactions on a molecular level, serves to guide and optimise their discovery as medicinal agents, and hopes to stimulate multidisciplinary research between scientific, experimental and molecular modelling research teams.
Ling, Hong; Samarasinghe, Sandhya; Kulasiri, Don
2013-12-01
Understanding the control of cellular networks consisting of gene and protein interactions and their emergent properties is a central activity of Systems Biology research. For this, continuous, discrete, hybrid, and stochastic methods have been proposed. Currently, the most common approach to modelling accurate temporal dynamics of networks is ordinary differential equations (ODE). However, critical limitations of ODE models are difficulty in kinetic parameter estimation and numerical solution of a large number of equations, making them more suited to smaller systems. In this article, we introduce a novel recurrent artificial neural network (RNN) that addresses above limitations and produces a continuous model that easily estimates parameters from data, can handle a large number of molecular interactions and quantifies temporal dynamics and emergent systems properties. This RNN is based on a system of ODEs representing molecular interactions in a signalling network. Each neuron represents concentration change of one molecule represented by an ODE. Weights of the RNN correspond to kinetic parameters in the system and can be adjusted incrementally during network training. The method is applied to the p53-Mdm2 oscillation system - a crucial component of the DNA damage response pathways activated by a damage signal. Simulation results indicate that the proposed RNN can successfully represent the behaviour of the p53-Mdm2 oscillation system and solve the parameter estimation problem with high accuracy. Furthermore, we presented a modified form of the RNN that estimates parameters and captures systems dynamics from sparse data collected over relatively large time steps. We also investigate the robustness of the p53-Mdm2 system using the trained RNN under various levels of parameter perturbation to gain a greater understanding of the control of the p53-Mdm2 system. Its outcomes on robustness are consistent with the current biological knowledge of this system. As more
Mello, Antonietta; Balestrini, Raffaella
2018-01-01
The roots of most terrestrial plants are colonized by mycorrhizal fungi. They play a key role in terrestrial environments influencing soil structure and ecosystem functionality. Around them a peculiar region, the mycorrhizosphere, develops. This is a very dynamic environment where plants, soil and microorganisms interact. Interest in this fascinating environment has increased over the years. For a long period the knowledge of the microbial populations in the rhizosphere has been limited, because they have always been studied by traditional culture-based techniques. These methods, which only allow the study of cultured microorganisms, do not allow the characterization of most organisms existing in nature. The introduction in the last few years of methodologies that are independent of culture techniques has bypassed this limitation. This together with the development of high-throughput molecular tools has given new insights into the biology, evolution, and biodiversity of mycorrhizal associations, as well as, the molecular dialog between plants and fungi. The genomes of many mycorrhizal fungal species have been sequenced so far allowing to better understanding the lifestyle of these fungi, their sexual reproduction modalities and metabolic functions. The possibility to detect the mycelium and the mycorrhizae of heterothallic fungi has also allowed to follow the spatial and temporal distributional patterns of strains of different mating types. On the other hand, the availability of the genome sequencing from several mycorrhizal fungi with a different lifestyle, or belonging to different groups, allowed to verify the common feature of the mycorrhizal symbiosis as well as the differences on how different mycorrhizal species interact and dialog with the plant. Here, we will consider the aspects described before, mainly focusing on ectomycorrhizal fungi and their interactions with plants and other soil microorganisms.
Recent Insights on Biological and Ecological Aspects of Ectomycorrhizal Fungi and Their Interactions
Directory of Open Access Journals (Sweden)
Antonietta Mello
2018-02-01
Full Text Available The roots of most terrestrial plants are colonized by mycorrhizal fungi. They play a key role in terrestrial environments influencing soil structure and ecosystem functionality. Around them a peculiar region, the mycorrhizosphere, develops. This is a very dynamic environment where plants, soil and microorganisms interact. Interest in this fascinating environment has increased over the years. For a long period the knowledge of the microbial populations in the rhizosphere has been limited, because they have always been studied by traditional culture-based techniques. These methods, which only allow the study of cultured microorganisms, do not allow the characterization of most organisms existing in nature. The introduction in the last few years of methodologies that are independent of culture techniques has bypassed this limitation. This together with the development of high-throughput molecular tools has given new insights into the biology, evolution, and biodiversity of mycorrhizal associations, as well as, the molecular dialog between plants and fungi. The genomes of many mycorrhizal fungal species have been sequenced so far allowing to better understanding the lifestyle of these fungi, their sexual reproduction modalities and metabolic functions. The possibility to detect the mycelium and the mycorrhizae of heterothallic fungi has also allowed to follow the spatial and temporal distributional patterns of strains of different mating types. On the other hand, the availability of the genome sequencing from several mycorrhizal fungi with a different lifestyle, or belonging to different groups, allowed to verify the common feature of the mycorrhizal symbiosis as well as the differences on how different mycorrhizal species interact and dialog with the plant. Here, we will consider the aspects described before, mainly focusing on ectomycorrhizal fungi and their interactions with plants and other soil microorganisms.
Energy Technology Data Exchange (ETDEWEB)
Mittal, Ashutosh [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Himmel, Michael E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kumar, Rajeev [University of California, Riverside; Oak Ridge National Laboratory;
2018-01-23
It has been previously shown that cellulose-lignin droplets' strong interactions, resulting from lignin coalescence and redisposition on cellulose surface during thermochemical pretreatments, increase cellulose recalcitrance to biological conversion, especially at commercially viable low enzyme loadings. However, information on the impact of cellulose-hemicellulose interactions on cellulose recalcitrance following relevant pretreatment conditions are scarce. Here, to investigate the effects of plausible hemicellulose precipitation and re-association with cellulose on cellulose conversion, different pretreatments were applied to pure Avicel(R) PH101 cellulose alone and Avicel mixed with model hemicellulose compounds followed by enzymatic hydrolysis of resulting solids at both low and high enzyme loadings. Solids produced by pretreatment of Avicel mixed with hemicelluloses (AMH) were found to contain about 2 to 14.6% of exogenous, precipitated hemicelluloses and showed a remarkably much lower digestibility (up to 60%) than their respective controls. However, the exogenous hemicellulosic residues that associated with Avicel following high temperature pretreatments resulted in greater losses in cellulose conversion than those formed at low temperatures, suggesting that temperature plays a strong role in the strength of cellulose-hemicellulose association. Molecular dynamics simulations of hemicellulosic xylan and cellulose were found to further support this temperature effect as the xylan-cellulose interactions were found to substantially increase at elevated temperatures. Furthermore, exogenous, precipitated hemicelluloses in pretreated AMH solids resulted in a larger drop in cellulose conversion than the delignified lignocellulosic biomass containing comparably much higher natural hemicellulose amounts. Increased cellulase loadings or supplementation of cellulase with xylanases enhanced cellulose conversion for most pretreated AMH solids; however, this approach
Interactive exploration of integrated biological datasets using context-sensitive workflows.
Horn, Fabian; Rittweger, Martin; Taubert, Jan; Lysenko, Artem; Rawlings, Christopher; Guthke, Reinhard
2014-01-01
Network inference utilizes experimental high-throughput data for the reconstruction of molecular interaction networks where new relationships between the network entities can be predicted. Despite the increasing amount of experimental data, the parameters of each modeling technique cannot be optimized based on the experimental data alone, but needs to be qualitatively assessed if the components of the resulting network describe the experimental setting. Candidate list prioritization and validation builds upon data integration and data visualization. The application of tools supporting this procedure is limited to the exploration of smaller information networks because the display and interpretation of large amounts of information is challenging regarding the computational effort and the users' experience. The Ondex software framework was extended with customizable context-sensitive menus which allow additional integration and data analysis options for a selected set of candidates during interactive data exploration. We provide new functionalities for on-the-fly data integration using InterProScan, PubMed Central literature search, and sequence-based homology search. We applied the Ondex system to the integration of publicly available data for Aspergillus nidulans and analyzed transcriptome data. We demonstrate the advantages of our approach by proposing new hypotheses for the functional annotation of specific genes of differentially expressed fungal gene clusters. Our extension of the Ondex framework makes it possible to overcome the separation between data integration and interactive analysis. More specifically, computationally demanding calculations can be performed on selected sub-networks without losing any information from the whole network. Furthermore, our extensions allow for direct access to online biological databases which helps to keep the integrated information up-to-date.
International Nuclear Information System (INIS)
Yu, Wangshu; Shi, Lei; Hui, Guangquan; Cui, Fengling
2013-01-01
The synthesis of a new biological active reagent, 2-((1,4-dihydroxy)-9,10-anthraquinone) aldehyde thiosemicarbazone (DHAQTS), was designed. The interaction between DHAQTS and HSA was studied by fluorescence spectroscopy in combination with molecular modeling under simulation of physiological conditions. According to the results of fluorescence measurements, the quenching mechanism was suggested to be static. The thermodynamic parameters are calculated by van't Hoff equation, which demonstrated that hydrophobic interactions are the predominant intermolecular forces stabilizing the complex. The number of binding sites (n) was calculated. Through the site marker competitive experiment, DHAQTS was confirmed to be located in site I of HSA. The binding distance r=2.83 nm between the donor HSA and acceptor DHAQTS was obtained according to Förster's non-radiative energy transfer theory. The three-dimensional fluorescence spectral results showed the conformation and microenvironment of HSA changed in the presence of DHAQTS. The effects of common ions on the binding of DHAQTS to HSA were also evaluated. The experimental results were in agreement with the results obtained via a molecular docking study. - Highlights: ► 2-((1,4-dihydroxy)-9,10-anthraquinone)aldehyde thiosemicarbazone (DHAQTS) was synthesized. ► DHAQTS can quench the fluorescence of human serum albumin (HSA) by static quenching mechanism. ► Hydrophobic interactions were the predominant intermolecular forces. ► The competitive experiment was carried out to identify the DHAQTS binding site on HSA. ► Three-dimensional spectra confirmed DHAQTS caused the conformational change of HSA.
Bipartite graphs as models of population structures in evolutionary multiplayer games.
Peña, Jorge; Rochat, Yannick
2012-01-01
By combining evolutionary game theory and graph theory, "games on graphs" study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner's dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner's dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.
Colored graphs and matrix integrals
International Nuclear Information System (INIS)
Artamkin, I.V.
2007-12-01
In this article we discuss two different asymptotic expansions of matrix integrals. The original approach using the so-called Feynman diagram techniques leads to sums over isomorphism classes of ribbon graphs. Asymptotic expansions of more general Gaussian integrals are sums over isomorphism classes of colored graphs without ribbon structure. Here we derive the former expansion from the latter one. This provides an independent proof for the expansion used by Kontsevich. It might be very interesting to compare the algebra arising in these two approaches. The asymptotic expansion using ribbon graphs leads to the tau function of the KDV hierarchy while the sums over colored graphs satisfy simple partial differential equations which generalize the Burgers equation. We describe the general approach using colored graphs in the second section. In the third section we specialize the results of the second section for the matrix integral. In this section we also derive the expansion over ribbon graphs. The proof is based on simple topological considerations which are contained in section 5. In the last section we give an explicit calculation of the first term of the expansion using colored graphs
Hierarchy of modular graph identities
Energy Technology Data Exchange (ETDEWEB)
D’Hoker, Eric; Kaidi, Justin [Mani L. Bhaumik Institute for Theoretical Physics, Department of Physics and Astronomy,University of California,Los Angeles, CA 90095 (United States)
2016-11-09
The low energy expansion of Type II superstring amplitudes at genus one is organized in terms of modular graph functions associated with Feynman graphs of a conformal scalar field on the torus. In earlier work, surprising identities between two-loop graphs at all weights, and between higher-loop graphs of weights four and five were constructed. In the present paper, these results are generalized in two complementary directions. First, all identities at weight six and all dihedral identities at weight seven are obtained and proven. Whenever the Laurent polynomial at the cusp is available, the form of these identities confirms the pattern by which the vanishing of the Laurent polynomial governs the full modular identity. Second, the family of modular graph functions is extended to include all graphs with derivative couplings and worldsheet fermions. These extended families of modular graph functions are shown to obey a hierarchy of inhomogeneous Laplace eigenvalue equations. The eigenvalues are calculated analytically for the simplest infinite sub-families and obtained by Maple for successively more complicated sub-families. The spectrum is shown to consist solely of eigenvalues s(s−1) for positive integers s bounded by the weight, with multiplicities which exhibit rich representation-theoretic patterns.
Identifying vertex covers in graphs
DEFF Research Database (Denmark)
Henning, Michael A.; Yeo, Anders
2012-01-01
An identifying vertex cover in a graph G is a subset T of vertices in G that has a nonempty intersection with every edge of G such that T distinguishes the edges, that is, e∩T ≠ 0 for every edge e in G and e∩T ≠ f∩T for every two distinct edges e and f in G. The identifying vertex cover number TD......(G) of G is the minimum size of an identifying vertex cover in G. We observe that TD(G)+ρ(G) = |V (G)|, where ρ(G) denotes the packing number of G. We conjecture that if G is a graph of order n and size m with maximum degree Δ, then TD(G) ≤(Δ(Δ-1)/ Δ2+1)n + (2/Δ2+1) m. If the conjecture is true......, then the bound is best possible for all Δ ≥ 1. We prove this conjecture when Δ ≥ 1 and G is a Δ-regular graph. The three known Moore graphs of diameter 2, namely the 5-cycle, the Petersen graph and the Hoffman-Singleton graph, are examples of regular graphs that achieves equality in the upper bound. We also...
Bounds for percolation thresholds on directed and undirected graphs
Hamilton, Kathleen; Pryadko, Leonid
2015-03-01
Percolation theory is an efficient approach to problems with strong disorder, e.g., in quantum or classical transport, composite materials, and diluted magnets. Recently, the growing role of big data in scientific and industrial applications has led to a renewed interest in graph theory as a tool for describing complex connections in various kinds of networks: social, biological, technological, etc. In particular, percolation on graphs has been used to describe internet stability, spread of contagious diseases and computer viruses; related models describe market crashes and viral spread in social networks. We consider site-dependent percolation on directed and undirected graphs, and present several exact bounds for location of the percolation transition in terms of the eigenvalues of matrices associated with graphs, including the adjacency matrix and the Hashimoto matrix used to enumerate non-backtracking walks. These bounds correspond t0 a mean field approximation and become asymptotically exact for graphs with no short cycles. We illustrate this convergence numerically by simulating percolation on several families of graphs with different cycle lengths. This research was supported in part by the NSF Grant PHY-1416578 and by the ARO Grant W911NF-11-1-0027.
XML Graphs in Program Analysis
DEFF Research Database (Denmark)
Møller, Anders; Schwartzbach, Michael I.
2011-01-01
XML graphs have shown to be a simple and effective formalism for representing sets of XML documents in program analysis. It has evolved through a six year period with variants tailored for a range of applications. We present a unified definition, outline the key properties including validation...... of XML graphs against different XML schema languages, and provide a software package that enables others to make use of these ideas. We also survey the use of XML graphs for program analysis with four very different languages: XACT (XML in Java), Java Servlets (Web application programming), XSugar...... (transformations between XML and non-XML data), and XSLT (stylesheets for transforming XML documents)....
Large networks and graph limits
Lovász, László
2012-01-01
Recently, it became apparent that a large number of the most interesting structures and phenomena of the world can be described by networks. Developing a mathematical theory of very large networks is an important challenge. This book describes one recent approach to this theory, the limit theory of graphs, which has emerged over the last decade. The theory has rich connections with other approaches to the study of large networks, such as "property testing" in computer science and regularity partition in graph theory. It has several applications in extremal graph theory, including the exact for
Directory of Open Access Journals (Sweden)
Vassilis Stavrakas
Full Text Available Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.
Kirchhoff index of graphs and some graph operations
Indian Academy of Sciences (India)
Abstract. Let T be a rooted tree, G a connected graph, x,y ∈ V(G) be fixed and Gi's be |V(T )| disjoint copies of G with xi and yi denoting the corresponding copies of x and y in Gi, respectively. We define the T -repetition of G to be the graph obtained by joining yi to xj for each i ∈ V(T ) and each child j of i. In this paper, we ...
A Graph Based Framework to Model Virus Integration Sites
Directory of Open Access Journals (Sweden)
Raffaele Fronza
2016-01-01
Here, we addressed the challenge to: 1 define the notion of CIS on graph models, 2 demonstrate that the structure of CIS enters in the category of scale-free networks and 3 show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD as a testing dataset.
Alturki, Uthman T.
The goal of this research was to research, design, and develop a hypertext program for students who study biology. The Ecology Hypertext Program was developed using Research and Development (R&D) methodology. The purpose of this study was to place the final "product", a CD-ROM for learning biology concepts, in the hands of teachers and students to help them in learning and teaching process. The product was created through a cycle of literature review, needs assessment, development, and a cycle of field tests and revisions. I applied the ten steps of R&D process suggested by Borg and Gall (1989) which, consisted of: (1) Literature review, (2) Needs assessment, (3) Planning, (4) Develop preliminary product, (5) Preliminary field-testing, (6) Preliminary revision, (7) Main field-testing, (8) Main revision, (9) Final field-testing, and (10) Final product revision. The literature review and needs assessment provided a support and foundation for designing the preliminary product---the Ecology Hypertext Program. Participants in the needs assessment joined a focus group discussion. They were a group of graduate students in education who suggested the importance for designing this product. For the preliminary field test, the participants were a group of high school students studying biology. They were the potential user of the product. They reviewed the preliminary product and then filled out a questionnaire. Their feedback and suggestions were used to develop and improve the product in a step called preliminary revision. The second round of field tasting was the main field test in which the participants joined a focus group discussion. They were the same group who participated in needs assessment task. They reviewed the revised product and then provided ideas and suggestions to improve the product. Their feedback were categorized and implemented to develop the product as in the main revision task. Finally, a group of science teachers participated in this study by reviewing
Stella, Aaron
their surface which could be useful for nanomedicine purposes or biosensing applications. The changes in lymphocyte gene expression at different doses indicate that these TiO2 nanoparticles are capable of disrupting nuclear activity. The use of multiple screening methods provided an effective approach to evaluate nano-bio interactions. The use of a biologically-relevant matrix combined with specific detection methods yielded results which accurately predict biological adversity.
Graph theory and combinatorial optimization
Marcotte, Odile; Avis, David
2006-01-01
A current treatment of cutting-edge topics in Graph Theory and Combinatorial Optimization by leading researchersIncludes heuristic advances and novel approaches to solving combinatorial optimization problems.
Open Graphs and Computational Reasoning
Directory of Open Access Journals (Sweden)
Lucas Dixon
2010-06-01
Full Text Available We present a form of algebraic reasoning for computational objects which are expressed as graphs. Edges describe the flow of data between primitive operations which are represented by vertices. These graphs have an interface made of half-edges (edges which are drawn with an unconnected end and enjoy rich compositional principles by connecting graphs along these half-edges. In particular, this allows equations and rewrite rules to be specified between graphs. Particular computational models can then be encoded as an axiomatic set of such rules. Further rules can be derived graphically and rewriting can be used to simulate the dynamics of a computational system, e.g. evaluating a program on an input. Examples of models which can be formalised in this way include traditional electronic circuits as well as recent categorical accounts of quantum information.
Graph Model Based Indoor Tracking
DEFF Research Database (Denmark)
Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin
2009-01-01
The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...... infrastructure for different symbolic positioning technologies, e.g., Bluetooth and RFID. More specifically, the paper proposes a model of indoor space that comprises a base graph and mappings that represent the topology of indoor space at different levels. The resulting model can be used for one or several...... indoor positioning technologies. Focusing on RFID-based positioning, an RFID specific reader deployment graph model is built from the base graph model. This model is then used in several algorithms for constructing and refining trajectories from raw RFID readings. Empirical studies with implementations...
Generating random networks and graphs
Coolen, Ton; Roberts, Ekaterina
2017-01-01
This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation, as well as discussions of the main strengths and weaknesses of each approach. It includes extensive references for readers wishing to go further. The material is carefully structured to be accessible to researchers from all disciplines while also containing rigorous mathematical analysis (largely based on the techniques of statistical mechanics) to support those wishing to further develop or implement the theory of rand...
Submanifolds weakly associated with graphs
Indian Academy of Sciences (India)
Leuven: Katholieke Universiteit Leuven). (1990). [5] Etayo F, On quasi-slant submanifolds of an almost Hermitian manifold, Publ. Math. Debrecen 53 (1998) 217–223. [6] Harary F, Graph Theory (Reading: Addison-Wesley) (1972). [7] Papaghiuc N ...
Graph anomalies in cyber communications
Energy Technology Data Exchange (ETDEWEB)
Vander Wiel, Scott A [Los Alamos National Laboratory; Storlie, Curtis B [Los Alamos National Laboratory; Sandine, Gary [Los Alamos National Laboratory; Hagberg, Aric A [Los Alamos National Laboratory; Fisk, Michael [Los Alamos National Laboratory
2011-01-11
Enterprises monitor cyber traffic for viruses, intruders and stolen information. Detection methods look for known signatures of malicious traffic or search for anomalies with respect to a nominal reference model. Traditional anomaly detection focuses on aggregate traffic at central nodes or on user-level monitoring. More recently, however, traffic is being viewed more holistically as a dynamic communication graph. Attention to the graph nature of the traffic has expanded the types of anomalies that are being sought. We give an overview of several cyber data streams collected at Los Alamos National Laboratory and discuss current work in modeling the graph dynamics of traffic over the network. We consider global properties and local properties within the communication graph. A method for monitoring relative entropy on multiple correlated properties is discussed in detail.
A contribution to queens graphs
DEFF Research Database (Denmark)
Barat, Janos
A graph $G$ is a queens graph if the vertices of $G$ can be mapped to queens on the chessboard such that two vertices are adjacent if and only if the corresponding queens attack each other, i.e. they are in horizontal, vertical or diagonal position. We prove a conjecture of Beineke, Broere...... and Henning that the Cartesian product of an odd cycle and a path is a queens graph. We show that the same does not hold for two odd cycles. % is not representable in the same way. The representation of the Cartesian product of an odd cycle and an even cycle remains an open problem. We also prove...... constructively that any finite subgraph of the grid or the hexagonal grid is a queens graph....
A 15-minute interactive, computerized condom use intervention with biological endpoints.
Grimley, Diane M; Hook, Edward W
2009-02-01
Brief face-to-face-behavioral interventions have been shown to be efficacious, but are costly to sustain and to widely disseminate. This study evaluated the efficacy of a 15-minute theory-based behavioral intervention designed to increase condom use and reduce new cases of Neisseria gonorrhoeae and Chlamydia trachomatis. Participants were randomly assigned via the computer to the intervention or the comparison group stratified by gender and their baseline stage of change (motivational readiness) for using condoms consistently (100%) with their main partners. Behavioral data and biologic specimens for testing of Neisseria gonorrhoeae and Chlamydia trachomatis were obtained at baseline and at 6 months post intervention. The intervention was delivered via an audio, multimedia, computerized application that provided individualized interventions to patients based on their responses to assessment items; comparison patients interacted with a 15-minute, computerized, multiple health risk assessment with no intervention. The majority of the sample (N = 430) was black (88%); 54.5% women; with a mean age = 24.5. Assuming all participants who did not return to the clinic at 6 months were not using condoms consistently, 32% of the treatment group versus 23% in the comparison group reported consistent condom use (P = 0.03). The combined Neisseria gonorrhoeae and Chlamydia trachomatis incidence declined to 6% in the intervention group versus 13% in the comparison group (P = 0.04). Results from a regression analysis revealed that the only statically significant predictor of sexually transmitted diseases infection at the follow-up was group assignment (OR = 1.91, 95% confidence index = 1.09-3.34; P = 0.043). These findings suggest that brief, interactive, computer-delivered interventions provided at the evaluation visit increase condom use and reduce sexually transmitted diseases without putting additional burden on clinicians or staff.
Directory of Open Access Journals (Sweden)
Vishwas D. Suryawanshi
2016-02-01
Full Text Available A biologically active antibacterial reagent, 2–amino-6-hydroxy–4–(4-N, N-dimethylaminophenyl-pyrimidine-5-carbonitrile (AHDMAPPC, was synthesized. It was employed to investigate the binding interaction with the bovine serum albumin (BSA in detail using different spectroscopic methods. It exhibited antibacterial activity against Escherichia coli and Staphylococcus aureus which are common food poisoning bacteria. The experimental results showed that the fluorescence quenching of model carrier protein BSA by AHDMAPPC was due to static quenching. The site binding constants and number of binding sites (n≈1 were determined at three different temperatures based on fluorescence quenching results. The thermodynamic parameters, enthalpy change (ΔH, free energy (ΔG and entropy change (ΔS for the reaction were calculated to be 15.15 kJ/mol, –36.11 kJ/mol and 51.26 J/mol K according to van't Hoff equation, respectively. The results indicated that the reaction was an endothermic and spontaneous process, and hydrophobic interactions played a major role in the binding between drug and BSA. The distance between donor and acceptor is 2.79 nm according to Förster's theory. The alterations of the BSA secondary structure in the presence of AHDMAPPC were confirmed by UV–visible, synchronous fluorescence, circular dichroism (CD and three-dimensional fluorescence spectra. All these results indicated that AHDMAPPC can bind to BSA and be effectively transported and eliminated in the body. It can be a useful guideline for further drug design.
SOUR graphs for efficient completion
Lynch, Christopher; Strogova, Polina
1998-01-01
International audience; We introduce a data structure called \\emphSOUR graphs and present an efficient Knuth-Bendix completion procedure based on it. \\emphSOUR graphs allow for a maximal structure sharing of terms in rewriting systems. The term representation is a dag representation, except that edges are labelled with equational constraints and variable renamings. The rewrite rules correspond to rewrite edges, the unification problems to unification edges. The Critical Pair and Simplificatio...
Rectilinear Graphs and Angular Resolution
Bodlaender, H.L.; Tel, G.
2003-01-01
In this note we show that a planar graph with angular resolution at least π/2 can be drawn with all angles an integer multiple of π/2, that is, in a rectilinear manner. Moreover, we show that for d ≠ 4, d › 2, having an angular resolution of 2π/d does not imply that the graph can be drawn with all
Graph theory and its applications
Gross, Jonathan L
2006-01-01
Gross and Yellen take a comprehensive approach to graph theory that integrates careful exposition of classical developments with emerging methods, models, and practical needs. Their unparalleled treatment provides a text ideal for a two-semester course and a variety of one-semester classes, from an introductory one-semester course to courses slanted toward classical graph theory, operations research, data structures and algorithms, or algebra and topology.
On dominator colorings in graphs
Indian Academy of Sciences (India)
A dominator coloring of a graph G is a proper coloring of G in which every vertex dominates every vertex of at least one color class. The minimum number of colors required for a dominator coloring of G is called the dominator chromatic number of G and is denoted by χd(G). In this paper we present several results on graphs ...
a generalization of total graphs
Indian Academy of Sciences (India)
8
Abstract. Let R be a commutative ring with nonzero identity, Ln(R) be the set of all lower triangular n × n matrices, and U be a triangular subset of. Rn i.e. the product of any lower triangular matrix with the transpose of any element of U, belongs to U. The graph GTn. U (Rn) is a simple graph whose ver- tices consists of all ...
Port-Hamiltonian Systems on Open Graphs
Schaft, A.J. van der; Maschke, B.M.
2010-01-01
In this talk we discuss how to define in an intrinsic manner port-Hamiltonian dynamics on open graphs. Open graphs are graphs where some of the vertices are boundary vertices (terminals), which allow interconnection with other systems. We show that a directed graph carries two natural Dirac
A Modal-Logic Based Graph Abstraction
Bauer, J.; Boneva, I.B.; Kurban, M.E.; Rensink, Arend; Ehrig, H; Heckel, R.; Rozenberg, G.; Taentzer, G.
2008-01-01
Infinite or very large state spaces often prohibit the successful verification of graph transformation systems. Abstract graph transformation is an approach that tackles this problem by abstracting graphs to abstract graphs of bounded size and by lifting application of productions to abstract
Summary 2: Graph Grammar Verification through Abstraction
Baldan, P.; Koenig, B.; Rensink, A.; Rensink, Arend; König, B.; Montanari, U.; Gardner, P.
2005-01-01
Until now there have been few contributions concerning the verification of graph grammars, specifically of infinite-state graph grammars. This paper compares two existing approaches, based on abstractions of graph transformation systems. While in the unfolding approach graph grammars are
On Graph Rewriting, Reduction and Evaluation
DEFF Research Database (Denmark)
Zerny, Ian
2009-01-01
We inter-derive two prototypical styles of graph reduction: reduction machines à la Turner and graph rewriting systems à la Barendregt. To this end, we adapt Danvy et al.'s mechanical program derivations from the world of terms to the world of graphs. We also inter-derive a graph evaluator....
Graphs with branchwidth at most three
Bodlaender, H.L.; Thilikos, D.M.
1997-01-01
In this paper we investigate both the structure of graphs with branchwidth at most three, as well as algorithms to recognise such graphs. We show that a graph has branchwidth at most three, if and only if it has treewidth at most three and does not contain the three-dimensional binary cube graph
A faithful functor among algebras and graphs
Falcón Ganfornina, Óscar Jesús; Falcón Ganfornina, Raúl Manuel; Núñez Valdés, Juan; Pacheco Martínez, Ana María; Villar Liñán, María Trinidad; Vigo Aguiar, Jesús (Coordinador)
2016-01-01
The problem of identifying a functor between the categories of algebras and graphs is currently open. Based on a known algorithm that identifies isomorphisms of Latin squares with isomorphism of vertex-colored graphs, we describe here a pair of graphs that enable us to find a faithful functor between finite-dimensional algebras over finite fields and these graphs.
Constructing Dense Graphs with Unique Hamiltonian Cycles
Lynch, Mark A. M.
2012-01-01
It is not difficult to construct dense graphs containing Hamiltonian cycles, but it is difficult to generate dense graphs that are guaranteed to contain a unique Hamiltonian cycle. This article presents an algorithm for generating arbitrarily large simple graphs containing "unique" Hamiltonian cycles. These graphs can be turned into dense graphs…
Hard graphs for the maximum clique problem
Hoede, C.
1988-01-01
The maximum clique problem is one of the NP-complete problems. There are graphs for which a reduction technique exists that transforms the problem for these graphs into one for graphs with specific properties in polynomial time. The resulting graphs do not grow exponentially in order and number.
Coordinates and intervals in graph-based reference genomes.
Rand, Knut D; Grytten, Ivar; Nederbragt, Alexander J; Storvik, Geir O; Glad, Ingrid K; Sandve, Geir K
2017-05-18
It has been proposed that future reference genomes should be graph structures in order to better represent the sequence diversity present in a species. However, there is currently no standard method to represent genomic intervals, such as the positions of genes or transcription factor binding sites, on graph-based reference genomes. We formalize offset-based coordinate systems on graph-based reference genomes and introduce methods for representing intervals on these reference structures. We show the advantage of our methods by representing genes on a graph-based representation of the newest assembly of the human genome (GRCh38) and its alternative loci for regions that are highly variable. More complex reference genomes, containing alternative loci, require methods to represent genomic data on these structures. Our proposed notation for genomic intervals makes it possible to fully utilize the alternative loci of the GRCh38 assembly and potential future graph-based reference genomes. We have made a Python package for representing such intervals on offset-based coordinate systems, available at https://github.com/uio-cels/offsetbasedgraph . An interactive web-tool using this Python package to visualize genes on a graph created from GRCh38 is available at https://github.com/uio-cels/genomicgraphcoords .
PieceStack: Toward Better Understanding of Stacked Graphs.
Wu, Tongshuang; Wu, Yingcai; Shi, Conglei; Qu, Huamin; Cui, Weiwei
2016-02-24
Stacked graphs have been widely adopted in various fields, because they are capable of hierarchically visualizing a set of temporal sequences as well as their aggregation. However, because of visual illusion issues, connections between overly-detailed individual layers and overly-generalized aggregation are intercepted. Consequently, information in this area has yet to be fully excavated. Thus, we present PieceStack in this paper, to reveal the relevance of stacked graphs in understanding intrinsic details of their displayed shapes. This new visual analytic design interprets the ways through which aggregations are generated with individual layers by interactively splitting and re-constructing the stacked graphs. A clustering algorithm is designed to partition stacked graphs into sub-aggregated pieces based on trend similarities of layers. We then visualize the pieces with augmented encoding to help analysts decompose and explore the graphs with respect to their interests. Case studies and a user study are conducted to demonstrate the usefulness of our technique in understanding the formation of stacked graphs.
Podder, Avijit; Jatana, Nidhi; Latha, N
2014-09-21
Dopamine receptors (DR) are one of the major neurotransmitter receptors present in human brain. Malfunctioning of these receptors is well established to trigger many neurological and psychiatric disorders. Taking into consideration that proteins function collectively in a network for most of the biological processes, the present study is aimed to depict the interactions between all dopamine receptors following a systems biology approach. To capture comprehensive interactions of candidate proteins associated with human dopamine receptors, we performed a protein-protein interaction network (PPIN) analysis of all five receptors and their protein partners by mapping them into human interactome and constructed a human Dopamine Receptors Interaction Network (DRIN). We explored the topology of dopamine receptors as molecular network, revealing their characteristics and the role of central network elements. More to the point, a sub-network analysis was done to determine major functional clusters in human DRIN that govern key neurological pathways. Besides, interacting proteins in a pathway were characterized and prioritized based on their affinity for utmost drug molecules. The vulnerability of different networks to the dysfunction of diverse combination of components was estimated under random and direct attack scenarios. To the best of our knowledge, the current study is unique to put all five dopamine receptors together in a common interaction network and to understand the functionality of interacting proteins collectively. Our study pinpointed distinctive topological and functional properties of human dopamine receptors that have helped in identifying potential therapeutic drug targets in the dopamine interaction network. Copyright © 2014 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Bruno Maia Carvalho
2008-01-01
Full Text Available The formation of the Brazilian Amazonian population has historically involved three main ethnic groups, Amerindian, African and European. This has resulted in genetic investigations having been carried out using classical polymorphisms and molecular markers. To better understand the genetic variability and the micro-evolutionary processes acting in human groups in the Brazilian Amazon region we used mitochondrial DNA to investigate 159 maternally unrelated individuals from five Amazonian African-descendant communities. The mitochondrial lineage distribution indicated a contribution of 50.2% from Africans (L0, L1, L2, and L3, 46.6% from Amerindians (haplogroups A, B, C and D and a small European contribution of 1.3%. These results indicated high genetic diversity in the Amerindian and African lineage groups, suggesting that the Brazilian Amazonian African-descendant populations reflect a possible population amalgamation of Amerindian women from different Amazonian indigenous tribes and African women from different geographic regions of Africa who had been brought to Brazil as slaves. The present study partially mapped the historical biological and social interactions that had occurred during the formation and expansion of Amazonian African-descendant communities.
Dao, David; Fraser, Adam N; Hung, Jane; Ljosa, Vebjorn; Singh, Shantanu; Carpenter, Anne E
2016-10-15
CellProfiler Analyst allows the exploration and visualization of image-based data, together with the classification of complex biological phenotypes, via an interactive user interface designed for biologists and data scientists. CellProfiler Analyst 2.0, completely rewritten in Python, builds on these features and adds enhanced supervised machine learning capabilities (Classifier), as well as visualization tools to overview an experiment (Plate Viewer and Image Gallery). CellProfiler Analyst 2.0 is free and open source, available at http://www.cellprofiler.org and from GitHub (https://github.com/CellProfiler/CellProfiler-Analyst) under the BSD license. It is available as a packaged application for Mac OS X and Microsoft Windows and can be compiled for Linux. We implemented an automatic build process that supports nightly updates and regular release cycles for the software. anne@broadinstitute.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
Dynamic Programming on Nominal Graphs
Directory of Open Access Journals (Sweden)
Nicklas Hoch
2015-04-01
Full Text Available Many optimization problems can be naturally represented as (hyper graphs, where vertices correspond to variables and edges to tasks, whose cost depends on the values of the adjacent variables. Capitalizing on the structure of the graph, suitable dynamic programming strategies can select certain orders of evaluation of the variables which guarantee to reach both an optimal solution and a minimal size of the tables computed in the optimization process. In this paper we introduce a simple algebraic specification with parallel composition and restriction whose terms up to structural axioms are the graphs mentioned above. In addition, free (unrestricted vertices are labelled with variables, and the specification includes operations of name permutation with finite support. We show a correspondence between the well-known tree decompositions of graphs and our terms. If an axiom of scope extension is dropped, several (hierarchical terms actually correspond to the same graph. A suitable graphical structure can be found, corresponding to every hierarchical term. Evaluating such a graphical structure in some target algebra yields a dynamic programming strategy. If the target algebra satisfies the scope extension axiom, then the result does not depend on the particular structure, but only on the original graph. We apply our approach to the parking optimization problem developed in the ASCENS e-mobility case study, in collaboration with Volkswagen. Dynamic programming evaluations are particularly interesting for autonomic systems, where actual behavior often consists of propagating local knowledge to obtain global knowledge and getting it back for local decisions.
Chromatic polynomials of random graphs
International Nuclear Information System (INIS)
Van Bussel, Frank; Fliegner, Denny; Timme, Marc; Ehrlich, Christoph; Stolzenberg, Sebastian
2010-01-01
Chromatic polynomials and related graph invariants are central objects in both graph theory and statistical physics. Computational difficulties, however, have so far restricted studies of such polynomials to graphs that were either very small, very sparse or highly structured. Recent algorithmic advances (Timme et al 2009 New J. Phys. 11 023001) now make it possible to compute chromatic polynomials for moderately sized graphs of arbitrary structure and number of edges. Here we present chromatic polynomials of ensembles of random graphs with up to 30 vertices, over the entire range of edge density. We specifically focus on the locations of the zeros of the polynomial in the complex plane. The results indicate that the chromatic zeros of random graphs have a very consistent layout. In particular, the crossing point, the point at which the chromatic zeros with non-zero imaginary part approach the real axis, scales linearly with the average degree over most of the density range. While the scaling laws obtained are purely empirical, if they continue to hold in general there are significant implications: the crossing points of chromatic zeros in the thermodynamic limit separate systems with zero ground state entropy from systems with positive ground state entropy, the latter an exception to the third law of thermodynamics.
Graph Quasicontinuous Functions and Densely Continuous Forms
Directory of Open Access Journals (Sweden)
Lubica Hola
2017-07-01
Full Text Available Let $X, Y$ be topological spaces. A function $f: X \\to Y$ is said to be graph quasicontinuous if there is a quasicontinuous function $g: X \\to Y$ with the graph of $g$ contained in the closure of the graph of $f$. There is a close relation between the notions of graph quasicontinuous functions and minimal usco maps as well as the notions of graph quasicontinuous functions and densely continuous forms. Every function with values in a compact Hausdorff space is graph quasicontinuous; more generally every locally compact function is graph quasicontinuous.
On P-transitive graphs and applications
Directory of Open Access Journals (Sweden)
Giacomo Lenzi
2011-06-01
Full Text Available We introduce a new class of graphs which we call P-transitive graphs, lying between transitive and 3-transitive graphs. First we show that the analogue of de Jongh-Sambin Theorem is false for wellfounded P-transitive graphs; then we show that the mu-calculus fixpoint hierarchy is infinite for P-transitive graphs. Both results contrast with the case of transitive graphs. We give also an undecidability result for an enriched mu-calculus on P-transitive graphs. Finally, we consider a polynomial time reduction from the model checking problem on arbitrary graphs to the model checking problem on P-transitive graphs. All these results carry over to 3-transitive graphs.
Phage, Itumeleng B.; Lemmer, Miriam; Hitge, Mariette
2017-01-01
Students' graph comprehension may be affected by the background of the students who are the readers or interpreters of the graph, their knowledge of the context in which the graph is set, and the inferential processes required by the graph operation. This research study investigated these aspects of graph comprehension for 152 first year…
Yang, Kai-Ti; Wang, Tzu-Hua; Chiu, Mei-Hung
2015-01-01
This research investigates the effectiveness of integrating Interactive Whiteboard (IWB) into the junior high school biology teaching. This research adopts a quasi-experimental design and divides the participating students into the conventional ICT-integrated learning environment and IWB-integrated learning environment. Before teaching, students…
Harvey, Ben P; Gwynn-Jones, Dylan; Moore, Pippa J
2013-01-01
Ocean acidification and warming are considered two of the greatest threats to marine biodiversity, yet the combined effect of these stressors on marine organisms remains largely unclear. Using a meta-analytical approach, we assessed the biological responses of marine organisms to the effects of ocean acidification and warming in isolation and combination. As expected biological responses varied across taxonomic groups, life-history stages, and trophic levels, but importantly, combining stressors generally exhibited a stronger biological (either positive or negative) effect. Using a subset of orthogonal studies, we show that four of five of the biological responses measured (calcification, photosynthesis, reproduction, and survival, but not growth) interacted synergistically when warming and acidification were combined. The observed synergisms between interacting stressors suggest that care must be made in making inferences from single-stressor studies. Our findings clearly have implications for the development of adaptive management strategies particularly given that the frequency of stressors interacting in marine systems will be likely to intensify in the future. There is now an urgent need to move toward more robust, holistic, and ecologically realistic climate change experiments that incorporate interactions. Without them accurate predictions about the likely deleterious impacts to marine biodiversity and ecosystem functioning over the next century will not be possible. PMID:23610641
Invasive plants are one of the strongest drivers of species extinctions. Weed biological control offers a sustainable and safe means of long-term population reduction of their target. Herbivores introduced for the control of invasive plants interact with the native community in addition to the top-d...
Network graph analysis and visualization with Gephi
Cherven, Ken
2013-01-01
A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.
GRMDA: Graph Regression for MiRNA-Disease Association Prediction
Directory of Open Access Journals (Sweden)
Xing Chen
2018-02-01
Full Text Available Nowadays, as more and more associations between microRNAs (miRNAs and diseases have been discovered, miRNA has gradually become a hot topic in the biological field. Because of the high consumption of time and money on carrying out biological experiments, computational method which can help scientists choose the most likely associations between miRNAs and diseases for further experimental studies is desperately needed. In this study, we proposed a method of Graph Regression for MiRNA-Disease Association prediction (GRMDA which combines known miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity. We used Gaussian interaction profile kernel similarity to supplement the shortage of miRNA functional similarity and disease semantic similarity. Furthermore, the graph regression was synchronously performed in three latent spaces, including association space, miRNA similarity space, and disease similarity space, by using two matrix factorization approaches called Singular Value Decomposition and Partial Least-Squares to extract important related attributes and filter the noise. In the leave-one-out cross validation and five-fold cross validation, GRMDA obtained the AUCs of 0.8272 and 0.8080 ± 0.0024, respectively. Thus, its performance is better than some previous models. In the case study of Lymphoma using the recorded miRNA-disease associations in HMDD V2.0 database, 88% of top 50 predicted miRNAs were verified by experimental literatures. In order to test the performance of GRMDA on new diseases with no known related miRNAs, we took Breast Neoplasms as an example by regarding all the known related miRNAs as unknown ones. We found that 100% of top 50 predicted miRNAs were verified. Moreover, 84% of top 50 predicted miRNAs in case study for Esophageal Neoplasms based on HMDD V1.0 were verified to have known associations. In conclusion, GRMDA is an effective and practical
GRMDA: Graph Regression for MiRNA-Disease Association Prediction.
Chen, Xing; Yang, Jing-Ru; Guan, Na-Na; Li, Jian-Qiang
2018-01-01
Nowadays, as more and more associations between microRNAs (miRNAs) and diseases have been discovered, miRNA has gradually become a hot topic in the biological field. Because of the high consumption of time and money on carrying out biological experiments, computational method which can help scientists choose the most likely associations between miRNAs and diseases for further experimental studies is desperately needed. In this study, we proposed a method of Graph Regression for MiRNA-Disease Association prediction (GRMDA) which combines known miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity. We used Gaussian interaction profile kernel similarity to supplement the shortage of miRNA functional similarity and disease semantic similarity. Furthermore, the graph regression was synchronously performed in three latent spaces, including association space, miRNA similarity space, and disease similarity space, by using two matrix factorization approaches called Singular Value Decomposition and Partial Least-Squares to extract important related attributes and filter the noise. In the leave-one-out cross validation and five-fold cross validation, GRMDA obtained the AUCs of 0.8272 and 0.8080 ± 0.0024, respectively. Thus, its performance is better than some previous models. In the case study of Lymphoma using the recorded miRNA-disease associations in HMDD V2.0 database, 88% of top 50 predicted miRNAs were verified by experimental literatures. In order to test the performance of GRMDA on new diseases with no known related miRNAs, we took Breast Neoplasms as an example by regarding all the known related miRNAs as unknown ones. We found that 100% of top 50 predicted miRNAs were verified. Moreover, 84% of top 50 predicted miRNAs in case study for Esophageal Neoplasms based on HMDD V1.0 were verified to have known associations. In conclusion, GRMDA is an effective and practical method for mi
Directory of Open Access Journals (Sweden)
Dániel Bánky
Full Text Available Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks that compensates for the low degree (non-hub vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well, but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus, and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures
Bánky, Dániel; Iván, Gábor; Grolmusz, Vince
2013-01-01
Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks) that compensates for the low degree (non-hub) vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges) of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well), but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus), and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures importance in the
Geometry of Graph Edit Distance Spaces
Jain, Brijnesh J.
2015-01-01
In this paper we study the geometry of graph spaces endowed with a special class of graph edit distances. The focus is on geometrical results useful for statistical pattern recognition. The main result is the Graph Representation Theorem. It states that a graph is a point in some geometrical space, called orbit space. Orbit spaces are well investigated and easier to explore than the original graph space. We derive a number of geometrical results from the orbit space representation, translate ...
GraphMeta: Managing HPC Rich Metadata in Graphs
Energy Technology Data Exchange (ETDEWEB)
Dai, Dong; Chen, Yong; Carns, Philip; Jenkins, John; Zhang, Wei; Ross, Robert
2016-01-01
High-performance computing (HPC) systems face increasingly critical metadata management challenges, especially in the approaching exascale era. These challenges arise not only from exploding metadata volumes, but also from increasingly diverse metadata, which contains data provenance and arbitrary user-defined attributes in addition to traditional POSIX metadata. This ‘rich’ metadata is becoming critical to supporting advanced data management functionality such as data auditing and validation. In our prior work, we identified a graph-based model as a promising solution to uniformly manage HPC rich metadata due to its flexibility and generality. However, at the same time, graph-based HPC rich metadata anagement also introduces significant challenges to the underlying infrastructure. In this study, we first identify the challenges on the underlying infrastructure to support scalable, high-performance rich metadata management. Based on that, we introduce GraphMeta, a graphbased engine designed for this use case. It achieves performance scalability by introducing a new graph partitioning algorithm and a write-optimal storage engine. We evaluate GraphMeta under both synthetic and real HPC metadata workloads, compare it with other approaches, and demonstrate its advantages in terms of efficiency and usability for rich metadata management in HPC systems.
PRIVATE GRAPHS – ACCESS RIGHTS ON GRAPHS FOR SEAMLESS NAVIGATION
Directory of Open Access Journals (Sweden)
W. Dorner
2016-06-01
Full Text Available After the success of GNSS (Global Navigational Satellite Systems and navigation services for public streets, indoor seems to be the next big development in navigational services, relying on RTLS – Real Time Locating Services (e.g. WIFI and allowing seamless navigation. In contrast to navigation and routing services on public streets, seamless navigation will cause an additional challenge: how to make routing data accessible to defined users or restrict access rights for defined areas or only to parts of the graph to a defined user group? The paper will present case studies and data from literature, where seamless and especially indoor navigation solutions are presented (hospitals, industrial complexes, building sites, but the problem of restricted access rights was only touched from a real world, but not a technical perspective. The analysis of case studies will show, that the objective of navigation and the different target groups for navigation solutions will demand well defined access rights and require solutions, how to make only parts of a graph to a user or application available to solve a navigational task. The paper will therefore introduce the concept of private graphs, which is defined as a graph for navigational purposes covering the street, road or floor network of an area behind a public street and suggest different approaches how to make graph data for navigational purposes available considering access rights and data protection, privacy and security issues as well.
de Bono, B; Safaei, S; Grenon, P; Hunter, P
2018-02-06
We introduce, and provide examples of, the application of the bond graph formalism to explicitly represent biophysical processes between and within modular biological compartments in ApiNATOMY. In particular, we focus on modelling scenarios from acid-base physiology to link distinct process modalities as bond graphs over an ApiNATOMY circuit of multiscale compartments. The embedding of bond graphs onto ApiNATOMY compartments provides a semantically and mathematically explicit basis for the coherent representation, integration and visualisation of multiscale physiology processes together with the compartmental topology of those biological structures that convey these processes.
Flasiński, Michał; Hąc-Wydro, Katarzyna
2014-08-01
Analysis of the interactions between two representatives of plant hormones: synthetic (1-naphthaleneacetic acid, NAA) as well as natural (indole-3-acetic acid, IAA) and phospholipids occurring in biological membrane of both plant and animal cells was the subject of present studies. The aim of undertaken experiments was to elucidate the problem of direct influence of these plant growth regulators on phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs) in monolayers at the air/water solution interface. The studied phospholipids differ not only as regards the structure of polar head-groups but also in the length of hydrophobic chains as well as their saturation degree. These differences result also in the main properties and functions of these phospholipids in biomembranes. The analysis of the results was based on the characteristics of the surface pressure (π)--area (A) isotherms registered for monolayers spread on the subphase containing plant hormone and as a reference on the surface of pure water. Moreover, as a complementary technique, Brewster angle microscopy was applied for the direct visualization of the investigated surface films. The obtained results revealed that auxins effectively influence phospholipids monolayers, regardless of the lipid structure, at the concentration of 10(-4)M. It was found that for this concentration, the influence of auxins was visibly larger in the case of PCs as compared to PEs. On the other hand, in the case of auxins solution of ≤ 10(-5)M, the observed trend was opposite. Generally, our studies showed that the natural plant hormone (IAA) interacts with the investigated lipid monolayers stronger than its synthetic derivative (NAA). The reason of these differences connects with the steric properties of both auxins; namely, the naphthalene ring of NAA molecule occupies larger space than the indole system of IAA. Therefore molecules of the latter compound penetrate easier into the region of phospholipids׳ polar head
Kase, Sue E.; Vanni, Michelle; Knight, Joanne A.; Su, Yu; Yan, Xifeng
2016-05-01
Within operational environments decisions must be made quickly based on the information available. Identifying an appropriate knowledge base and accurately formulating a search query are critical tasks for decision-making effectiveness in dynamic situations. The spreading of graph data management tools to access large graph databases is a rapidly emerging research area of potential benefit to the intelligence community. A graph representation provides a natural way of modeling data in a wide variety of domains. Graph structures use nodes, edges, and properties to represent and store data. This research investigates the advantages of information search by graph query initiated by the analyst and interactively refined within the contextual dimensions of the answer space toward a solution. The paper introduces SLQ, a user-friendly graph querying system enabling the visual formulation of schemaless and structureless graph queries. SLQ is demonstrated with an intelligence analyst information search scenario focused on identifying individuals responsible for manufacturing a mosquito-hosted deadly virus. The scenario highlights the interactive construction of graph queries without prior training in complex query languages or graph databases, intuitive navigation through the problem space, and visualization of results in graphical format.