Assembly rules for protein networks derived from phylogenetic-statistical analysis of whole genomes

Background: We report an analysis of a protein network of functionally linked proteins, identified from a phylogenetic statistical analysis of complete eukaryotic genomes. Phylogenetic methods identify pairs of proteins that co-evolve on a phylogenetic tree, and have been shown to have a high probability of correctly identifying known functional links. Results: The eukaryotic correlated evolution network we derive displays the familiar power law scaling of connectivity. We introduce the use of explicit phylogenetic methods to reconstruct the ancestral presence or absence of proteins at the interior nodes of a phylogeny of eukaryote species. We find that the connectivity distribution of proteins at the point they arise on the tree and join the network follows a power law, as does the connectivity distribution of proteins at the time they are lost from the network. Proteins resident in the network acquire connections over time, but we find no evidence that 'preferential attachment' - the phenomenon of newly acquired connections in the network being more likely to be made to proteins with large numbers of connections - influences the network structure. We derive a 'variable rate of attachment' model in which proteins vary in their propensity to form network interactions independently of how many connections they have or of the total number of connections in the network, and show how this model can produce apparent power-law scaling without preferential attachment. Conclusion: A few simple rules can explain the topological structure and evolutionary changes to protein-interaction networks: most change is concentrated in satellite proteins of low connectivity and small phenotypic effect, and proteins differ in their propensity to form attachments. Given these rules of assembly, power law scaled networks naturally emerge from simple principles of selection, yielding protein interaction networks that retain a high-degree of robustness on short time scales and evolvability on longer evolutionary time scales.

Inference on microsatellite mutation processes in the invasive mite, Varroa destructor, using reversible jump Markov chain Monte Carlo

Varroa destructor is a parasitic mite of the Eastern honeybee Apis cerana. Fifty years ago, two distinct evolutionary lineages (Korean and Japanese) invaded the Western honeybee Apis mellifera. This haplo-diploid parasite species reproduces mainly through brother sister matings, a system which largely favors the fixation of new mutations. In a worldwide sample of 225 individuals from 21 locations collected on Western honeybees and analyzed at 19 microsatellite loci, a series of de novo mutations was observed. Using historical data concerning the invasion, this original biological system has been exploited to compare three mutation models with allele size constraints for microsatellite markers: stepwise (SMM) and generalized (GSM) mutation models, and a model with mutation rate increasing exponentially with microsatellite length (ESM). Posterior probabilities of the three models have been estimated for each locus individually using reversible jump Markov Chain Monte Carlo. The relative support of each model varies widely among loci, but the GSM is the only model that always receives at least 9% support, whatever the locus. The analysis also provides robust estimates of mutation parameters for each locus and of the divergence time of the two invasive lineages (67,000 generations with a 90% credibility interval of 35,000-174,000). With an average of 10 generations per year, this divergence time fits with the last post-glacial Korea Japan land separation. (c) 2005 Elsevier Inc. All rights reserved.

GeneMCL in microarray analysis

Accurately and reliably identifying the actual number of clusters present with a dataset of gene expression profiles, when no additional information on cluster structure is available, is a problem addressed by few algorithms. GeneMCL transforms microarray analysis data into a graph consisting of nodes connected by edges, where the nodes represent genes, and the edges represent the similarity in expression of those genes, as given by a proximity measurement. This measurement is taken to be the Pearson correlation coefficient combined with a local non-linear rescaling step. The resulting graph is input to the Markov Cluster (MCL) algorithm, which is an elegant, deterministic, non-specific and scalable method, which models stochastic flow through the graph. The algorithm is inherently affected by any cluster structure present, and rapidly decomposes a graph into cohesive clusters. The potential of the GeneMCL algorithm is demonstrated with a 5730 gene subset (IGS) of the Van't Veer breast cancer database, for which the clusterings are shown to reflect underlying biological mechanisms. (c) 2005 Elsevier Ltd. All rights reserved.

Population subdivision and molecular sequence variation: Theory and analysis of Drosophila ananassae data

Population subdivision complicates analysis of molecular variation. Even if neutrality is assumed, three evolutionary forces need to be considered: migration, mutation, and drift. Simplification can be achieved by assuming that the process of migration among and drift within subpopulations is occurring fast compared to Mutation and drift in the entire population. This allows a two-step approach in the analysis: (i) analysis of population subdivision and (ii) analysis of molecular variation in the migrant pool. We model population subdivision using an infinite island model, where we allow the migration/drift parameter Theta to vary among populations. Thus, central and peripheral populations can be differentiated. For inference of Theta, we use a coalescence approach, implemented via a Markov chain Monte Carlo (MCMC) integration method that allows estimation of allele frequencies in the migrant pool. The second step of this approach (analysis of molecular variation in the migrant pool) uses the estimated allele frequencies in the migrant pool for the study of molecular variation. We apply this method to a Drosophila ananassae sequence data set. We find little indication of isolation by distance, but large differences in the migration parameter among populations. The population as a whole seems to be expanding. A population from Bogor (Java, Indonesia) shows the highest variation and seems closest to the species center.

A novel cation induced polymeric chain in Na-8[{Cu(gly)(2)}(2)]{H-2(H2W12O42)}] center dot 24H(2)O: hydrothermal synthesis, spectroscopic characterization and X-ray structure analysis

A novel bis(glycinato) copper(II) paradodecatungstate Na-8[{Cu(gly)(2)}(2)]-{H-2(H2W12O42)}] center dot 24H(2)O (1) has been synthesized under hydrothermal conditions. The crystal structure of 1 reveals an infinite one-dimensional chain along the [100] direction and is built from paradodecatungstate (H2W12O42)(10-) clusters joined through [Cu(gly)(2)] moieties. Parallel chains are interlinked by NaO6 octahedra to generate a two-dimensional network.

Synthesis, structural analysis, and magnetic behaviour of three fumarate bridged coordination polymers: five-fold interpenetrated diamond-like net of Ni-II, sheets of Ni-II and Co-II

The hydrothermal reactions of Ni(NO3)(2).6H(2)O, disodium fumarate (fum) and 1,2-bis(4-pyridyl)ethane (bpe)/1,3-bis(4-pyridyl) propane (bpp) in aqueous-methanol medium yield one 3-D and one 2-D metal-organic hybrid material, [Ni(fum)(bpe)] (1) and [Ni(fum)(bpp)(H2O)] (2), respectively. Complex 1 possesses a novel unprecedented structure, the first example of an "unusual mode" of a five-fold distorted interpenetrated network with metal-ligand linkages where the four six-membered windows in each adamantane-type cage are different. The structural characterization of complex 2 evidences a buckled sheet where nickel ions are in a distorted octahedral geometry, with two carboxylic groups, one acting as a bis-chelate, the other as a bis-monodentate ligand. The metal ion completes the coordination sphere through one water molecule and two bpp nitrogens in cis position. Variable-temperature magnetic measurements of complexes 1 and 2 reveal the existence of very weak antiferromagnetic intramolecular interactions and/or the presence of single-ion zero field splitting (D) of isolated Ni-II ions in both the compounds. Experimentally, both the J parameters are close, comparable and very small. Considering zero-field splitting of Ni-II, the calculated D values are in agreement with values reported in the literature for Ni-II ions. Complex 3, [{Co(phen)}(2)(fum)(2)] (phen=1,10-phenanthroline) is obtained by diffusing methanolic solution of 1,10-phenanthroline on an aqueous layer of disodium fumarate and Co(NO3)(2).6H(2)O. It consists of dimeric Co-II(phen) units, doubly bridged by carboxylate groups in a distorted syn-syn fashion. These fumarate anions act as bis-chelates to form corrugated sheets. The 2D layer has a (4,4) topology, with the nodes represented by the centres of the dimers. The magnetic data were fitted ignoring the very weak coupling through the fumarate pathway and using a dimer model.

Factors controlling the distribution of ozone in the West African lower troposphere during the AMMA (African Monsoon Multidisciplinary Analysis) wet season campaign

Ozone and its precursors were measured on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe 146 Atmospheric Research Aircraft during the monsoon season 2006 as part of the African Monsoon Multidisciplinary Analysis (AMMA) campaign. One of the main features observed in the west African boundary layer is the increase of the ozone mixing ratios from 25 ppbv over the forested area (south of 12 degrees N) up to 40 ppbv over the Sahelian area. We employ a two-dimensional ( latitudinal versus vertical) meteorological model coupled with an O-3-NOx-VOC chemistry scheme to simulate the distribution of trace gases over West Africa during the monsoon season and to analyse the processes involved in the establishment of such a gradient. Including an additional source of NO over the Sahelian region to account for NO emitted by soils we simulate a mean NOx concentration of 0.7 ppbv at 16 degrees N versus 0.3 ppbv over the vegetated region further south in reasonable agreement with the observations. As a consequence, ozone is photochemically produced with a rate of 0.25 ppbv h(-1) over the vegetated region whilst it reaches up to 0.75 ppbv h(-1) at 16 degrees N. We find that the modelled gradient is due to a combination of enhanced deposition to vegetation, which decreases the ozone levels by up to 11 pbbv, and the aforementioned enhanced photochemical production north of 12 degrees N. The peroxy radicals required for this enhanced production in the north come from the oxidation of background CO and CH4 as well as from VOCs. Sensitivity studies reveal that both the background CH4 and partially oxidised VOCs, produced from the oxidation of isoprene emitted from the vegetation in the south, contribute around 5-6 ppbv to the ozone gradient. These results suggest that the northward transport of trace gases by the monsoon flux, especially during nighttime, can have a significant, though secondary, role in determining the ozone gradient in the boundary layer. Convection, anthropogenic emissions and NO produced from lightning do not contribute to the establishment of the discussed ozone gradient.

Real-time context-aware network security policy enforcement system (RC-NSPES)

The major technical objectives of the RC-NSPES are to provide a framework for the concurrent operation of reactive and pro-active security functions to deliver efficient and optimised intrusion detection schemes as well as enhanced and highly correlated rule sets for more effective alerts management and root-cause analysis. The design and implementation of the RC-NSPES solution includes a number of innovative features in terms of real-time programmable embedded hardware (FPGA) deployment as well as in the integrated management station. These have been devised so as to deliver enhanced detection of attacks and contextualised alerts against threats that can arise from both the network layer and the application layer protocols. The resulting architecture represents an efficient and effective framework for the future deployment of network security systems.

Conceptualisation of an application of adaptive synthetic socioeconomic agents for intelligent network control

The deployment of Quality of Service (QoS) techniques involves careful analysis of area including: those business requirements; corporate strategy; and technical implementation process, which can lead to conflict or contradiction between those goals of various user groups involved in that policy definition. In addition long-term change management provides a challenge as these implementations typically require a high-skill set and experience level, which expose organisations to effects such as “hyperthymestria” [1] and “The Seven Sins of Memory”, defined by Schacter and discussed further within this paper. It is proposed that, given the information embedded within the packets of IP traffic, an opportunity exists to augment the traffic management with a machine-learning agent-based mechanism. This paper describes the process by which current policies are defined and that research required to support the development of an application which enables adaptive intelligent Quality of Service controls to augment or replace those policy-based mechanisms currently in use.

Enhancing change detection in low-quality surveillance footage using markov random fields

Urban surveillance footage can be of poor quality, partly due to the low quality of the camera and partly due to harsh lighting and heavily reflective scenes. For some computer surveillance tasks very simple change detection is adequate, but sometimes a more detailed change detection mask is desirable, eg, for accurately tracking identity when faced with multiple interacting individuals and in pose-based behaviour recognition. We present a novel technique for enhancing a low-quality change detection into a better segmentation using an image combing estimator in an MRF based model.

Robustness and applicability of Markov chain Monte Carlo algorithms for eigenvalue problems

In this paper we analyse applicability and robustness of Markov chain Monte Carlo algorithms for eigenvalue problems. We restrict our consideration to real symmetric matrices. Almost Optimal Monte Carlo (MAO) algorithms for solving eigenvalue problems are formulated. Results for the structure of both - systematic and probability error are presented. It is shown that the values of both errors can be controlled independently by different algorithmic parameters. The results present how the systematic error depends on the matrix spectrum. The analysis of the probability error is presented. It shows that the close (in some sense) the matrix under consideration is to the stochastic matrix the smaller is this error. Sufficient conditions for constructing robust and interpolation Monte Carlo algorithms are obtained. For stochastic matrices an interpolation Monte Carlo algorithm is constructed. A number of numerical tests for large symmetric dense matrices are performed in order to study experimentally the dependence of the systematic error from the structure of matrix spectrum. We also study how the probability error depends on the balancing of the matrix. (c) 2007 Elsevier Inc. All rights reserved.

Suprathermal electron flux peaks at stream interfaces: Signature of solar wind dynamics or tracer for open magnetic flux transport on the Sun?

The high variability of the intensity of suprathermal electron flux in the solar wind is usually ascribed to the high variability of sources on the Sun. Here we demonstrate that a substantial amount of the variability arises from peaks in stream interaction regions, where fast wind runs into slow wind and creates a pressure ridge at the interface. Superposed epoch analysis centered on stream interfaces in 26 interaction regions previously identified in Wind data reveal a twofold increase in 250 eV flux (integrated over pitch angle). Whether the peaks result from the compression there or are solar signatures of the coronal hole boundary, to which interfaces may map, is an open question. Suggestive of the latter, some cases show a displacement between the electron and magnetic field peaks at the interface. Since solar information is transmitted to 1 AU much more quickly by suprathermal electrons compared to convected plasma signatures, the displacement may imply a shift in the coronal hole boundary through transport of open magnetic flux via interchange reconnection. If so, however, the fact that displacements occur in both directions and that the electron and field peaks in the superposed epoch analysis are nearly coincident indicate that any systematic transport expected from differential solar rotation is overwhelmed by a random pattern, possibly owing to transport across a ragged coronal hole boundary.

Influence of drought-induced acidification on the mobility of dissolved organic carbon in peat soils

A strong relationship between dissolved organic carbon (DOC) and sulphate (SO42−) dynamics under drought conditions has been revealed from analysis of a 10-year time series (1993–2002). Soil solution from a blanket peat at 10 cm depth and stream water were collected at biweekly and weekly intervals, respectively, by the Environmental Change Network at Moor House-Upper Teesdale National Nature Reserve in the North Pennine uplands of Britain. DOC concentrations in soil solution and stream water were closely coupled, displaying a strong seasonal cycle with lowest concentrations in early spring and highest in late summer/early autumn. Soil solution DOC correlated strongly with seasonal variations in soil temperature at the same depth 4-weeks prior to sampling. Deviation from this relationship was seen, however, in years with significant water table drawdown (>−25 cm), such that DOC concentrations were up to 60% lower than expected. Periods of drought also resulted in the release of SO42−, because of the oxidation of inorganic/organic sulphur stored in the peat, which was accompanied by a decrease in pH and increase in ionic strength. As both pH and ionic strength are known to control the solubility of DOC, inclusion of a function to account for DOC suppression because of drought-induced acidification accounted for more of the variability of DOC in soil solution (R2=0.81) than temperature alone (R2=0.58). This statistical model of peat soil solution DOC at 10 cm depth was extended to reproduce 74% of the variation in stream DOC over this period. Analysis of annual budgets showed that the soil was the main source of SO42− during droughts, while atmospheric deposition was the main source in other years. Mass balance calculations also showed that most of the DOC originated from the peat. The DOC flux was also lower in the drought years of 1994 and 1995, reflecting low DOC concentrations in soil and stream water. The analysis presented in this paper suggests that lower concentrations of DOC in both soil and stream waters during drought years can be explained in terms of drought-induced acidification. As future climate change scenarios suggest an increase in the magnitude and frequency of drought events, these results imply potential for a related increase in DOC suppression by episodic acidification.

Cloud optical depth retrievals from the Aerosol Robotic Network (AERONET) cloud mode observations

Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program’s Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale.