GS2: an efficiently computable measure of GO-based similarity of gene sets

Motivation: The growing availability of genome-scale datasets has attracted increasing attention to the development of computational methods for automated inference of functional similarities among genes and their products. One class of such methods measures the functional similarity of genes based on their distance in the Gene Ontology (GO). To measure the functional relatedness of a gene set, these measures consider every pair of genes in the set, and the average of all pairwise distances is calculated. However, as more data becomes available and gene sets used for analysis become larger, such pair-based calculation becomes prohibitive

Neutral forces acting on intragenomic variability shape the Escherichia coli regulatory network topology

Cis-regulatory networks (CRNs) play a central role in cellular decision making. Like every other biological system, CRNs undergo evolution, which shapes their properties by a combination of adaptive and nonadaptive evolutionary forces. Teasing apart these forces is an important step toward functional analyses of the different components of CRNs, designing regulatory perturbation experiments, and constructing synthetic networks. Although tests of neutrality and selection based on molecular sequence data exist, no such tests are currently available based on CRNs. In this work, we present a unique genotype model of CRNs that is grounded in a genomic context and demonstrate its use in identifying portions of the CRN with properties explainable by neutral evolutionary forces at the system, subsystem, and operon levels.We leverage our model against experimentally derived data from Escherichia coli. The results of this analysis show statistically significant and substantial neutral trends in properties previously identified as adaptive in originﾗdegree distribution, clustering coefficient, and motifsﾗ within the E. coli CRN. Our model captures the tightly coupled genomeﾖ interactome of an organism and enables analyses of how evolutionary events acting at the genome level, such as mutation, and at the population level, such as genetic drift, give rise to neutral patterns that we can quantify in CRNs

Unusual features of long-range density fluctuations in glass-forming organic liquids : a Rayleigh and Rayleigh-Brillouin light scattering in study

A new feature of glass-forming liquids, i.e., long-range density fluctuations of the order of 100 nm, has been extensively characterized by means of static light scattering, photon correlation spectroscopy and Rayleigh-Brillouin spectroscopy in orthoterphenyl (OTP) and 1,1-di(4'-methoxy-5' methyl-phenyl)-cyclohexane (BMMPC). These long-range density fluctuations result in the following unusual features observed in a light scattering experiment. which are not described by the existing theories: (i) strong q-dependent isotropic excess Rayleigh intensity, (ii) additional slow component in the polarized photon correlation function, and (iii) high Landau-Placzek ratio. These unusual features are equilibrium properties of the glass-forming liquids and depend only on temperature, provided that the sample has been equilibrated long enough. The temperature-dependent equilibration times were measured for BMMPC and are about 11 orders of magnitude longer than the a process. It was found that the glass-forming liquid OTP may occur in two states: with and without long-range density fluctuations (''clusters"). We have characterized the two states by static and dynamic light scattering in the temperature range from T-g to T-g + 200 K. The relaxation times of the a process as well as the parameters of the Brillouin line are identical in both OTP with and without clusters. The a process (density fluctuations) in OTP was characterized by measuring either the polarized (VV) or depolarized (VH) correlation function, which are practically identical and a-independent. This feature, which is commonly observed in glass-forming liquids, is not fully explained by the existing theories

Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

<p>Abstract</p> <p>Background</p> <p>In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior.</p> <p>Results</p> <p>We introduce <it>PathwayOracle</it>, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates <it>PathwayOracle </it>from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, <it>PathwayOracle </it>includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model.</p> <p>Conclusion</p> <p><it>PathwayOracle </it>provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models. The application has been developed in Python and is designed to be easily extensible by groups interested in adding new or extending existing features. <it>PathwayOracle </it>is freely available for download and use.</p

Highly sensitive hydrogen sensor based on graphite-InP or graphite-GaN Schottky barrier with electrophoretically deposited Pd nanoparticles

Depositions on surfaces of semiconductor wafers of InP and GaN were performed from isooctane colloid solutions of palladium (Pd) nanoparticles (NPs) in AOT reverse micelles. Pd NPs in evaporated colloid and in layers deposited electrophoretically were monitored by SEM. Diodes were prepared by making Schottky contacts with colloidal graphite on semiconductor surfaces previously deposited with Pd NPs and ohmic contacts on blank surfaces. Forward and reverse current-voltage characteristics of the diodes showed high rectification ratio and high Schottky barrier heights, giving evidence of very small Fermi level pinning. A large increase of current was observed after exposing diodes to flow of gas blend hydrogen in nitrogen. Current change ratio about 700,000 with 0.1% hydrogen blend was achieved, which is more than two orders-of-magnitude improvement over the best result reported previously. Hydrogen detection limit of the diodes was estimated at 1 ppm H2/N2. The diodes, besides this extremely high sensitivity, have been temporally stable and of inexpensive production. Relatively more expensive GaN diodes have potential for functionality at high temperatures

PHY·FI: fast and easy online creation and manipulation of phylogeny color figures

BACKGROUND: The need to depict a phylogeny, or some other kind of abstract tree, is very frequently experienced by researchers from a broad range of biological and computational disciplines. Thousands of papers and talks include phylogeny figures, and often during everyday work, one would like to quickly get a graphical display of, e.g., the phylogenetic relationship between a set of sequences as calculated by an alignment program such as ClustalW or the phylogenetic package Phylip. A wealth of software tools capable of tree drawing exists; most are comprehensive packages that also perform various types of analysis, and hence they are available only for download and installing. Some online tools exist, too. RESULTS: This paper presents an online tool, PHY·FI, which encompasses all the qualities of existing online programs and adds functionality to hopefully eliminate the need for post-processing the phylogeny figure in some other general-purpose graphics program. PHY·FI is versatile, easy-to-use and fast, and supports comprehensive graphical control, several download image formats, and the possibility of dynamically collapsing groups of nodes into named subtrees (e.g. "Primates"). The user can create a color figure from any phylogeny, or other kind of tree, represented in the widely used parenthesized Newick format. CONCLUSION: PHY·FI is fast and easy to use, yet still offers full color control, tree manipulation, and several image formats. It does not require any downloading and installing, and thus any internet user regardless of computer skills, and computer platform, can benefit from it. PHY·FI is free for all and is available from this web address

TreeDyn: towards dynamic graphics and annotations for analyses of trees

BACKGROUND: Analyses of biomolecules for biodiversity, phylogeny or structure/function studies often use graphical tree representations. Many powerful tree editors are now available, but existing tree visualization tools make little use of meta-information related to the entities under study such as taxonomic descriptions or gene functions that can hardly be encoded within the tree itself (if using popular tree formats). Consequently, a tedious manual analysis and post-processing of the tree graphics are required if one needs to use external information for displaying or investigating trees. RESULTS: We have developed TreeDyn, a tool using annotations and dynamic graphical methods for editing and analyzing multiple trees. The main features of TreeDyn are 1) the management of multiple windows and multiple trees per window, 2) the export of graphics to several standard file formats with or without HTML encapsulation and a new format called TGF, which enables saving and restoring graphical analysis, 3) the projection of texts or symbols facing leaf labels or linked to nodes, through manual pasting or by using annotation files, 4) the highlight of graphical elements after querying leaf labels (or annotations) or by selection of graphical elements and information extraction, 5) the highlight of targeted trees according to a source tree browsed by the user, 6) powerful scripts for automating repetitive graphical tasks, 7) a command line interpreter enabling the use of TreeDyn through CGI scripts for online building of trees, 8) the inclusion of a library of packages dedicated to specific research fields involving trees. CONCLUSION: TreeDyn is a tree visualization and annotation tool which includes tools for tree manipulation and annotation and uses meta-information through dynamic graphical operators or scripting to help analyses and annotations of single trees or tree collections

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods

Controlling the Outcome of the Toll-Like Receptor Signaling Pathways

The Toll-Like Receptors (TLRs) are proteins involved in the immune system that increase cytokine levels when triggered. While cytokines coordinate the response to infection, they appear to be detrimental to the host when reaching too high levels. Several studies have shown that the deletion of specific TLRs was beneficial for the host, as cytokine levels were decreased consequently. It is not clear, however, how targeting other components of the TLR pathways can improve the responses to infections. We applied the concept of Minimal Cut Sets (MCS) to the ihsTLR v1.0 model of the TLR pathways to determine sets of reactions whose knockouts disrupt these pathways. We decomposed the TLR network into 34 modules and determined signatures for each MCS, i.e. the list of targeted modules. We uncovered 2,669 MCS organized in 68 signatures. Very few MCS targeted directly the TLRs, indicating that they may not be efficient targets for controlling these pathways. We mapped the species of the TLR network to genes in human and mouse, and determined more than 10,000 Essential Gene Sets (EGS). Each EGS provides genes whose deletion suppresses the network's outputs

The mEPN scheme: an intuitive and flexible graphical system for rendering biological pathways

<p>Abstract</p> <p>Background</p> <p>There is general agreement amongst biologists about the need for good pathway diagrams and a need to formalize the way biological pathways are depicted. However, implementing and agreeing how best to do this is currently the subject of some debate.</p> <p>Results</p> <p>The modified Edinburgh Pathway Notation (mEPN) scheme is founded on a notation system originally devised a number of years ago and through use has now been refined extensively. This process has been primarily driven by the author's attempts to produce process diagrams for a diverse range of biological pathways, particularly with respect to immune signaling in mammals. Here we provide a specification of the mEPN notation, its symbols, rules for its use and a comparison to the proposed Systems Biology Graphical Notation (SBGN) scheme.</p> <p>Conclusions</p> <p>We hope this work will contribute to the on-going community effort to develop a standard for depicting pathways and will provide a coherent guide to those planning to construct pathway diagrams of their biological systems of interest.</p