Which clustering algorithm is better for predicting protein complexes?

<p>Abstract</p> <p>Background</p> <p>Protein-Protein interactions (PPI) play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks.</p> <p>Results</p> <p>In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H) and Tandem Affinity Purification (TAP) methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases.</p> <p>Conclusions</p> <p>While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: <url>http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm</url></p

Production of phi mesons at mid-rapidity in sqrt(s_NN) = 200 GeV Au+Au collisions at RHIC

We present the first results of meson production in the K^+K^- decay channel from Au+Au collisions at sqrt(s_NN) = 200 GeV as measured at mid-rapidity by the PHENIX detector at RHIC. Precision resonance centroid and width values are extracted as a function of collision centrality. No significant variation from the PDG accepted values is observed. The transverse mass spectra are fitted with a linear exponential function for which the derived inverse slope parameter is seen to be constant as a function of centrality. These data are also fitted by a hydrodynamic model with the result that the freeze-out temperature and the expansion velocity values are consistent with the values previously derived from fitting single hadron inclusive data. As a function of transverse momentum the collisions scaled peripheral.to.central yield ratio RCP for the is comparable to that of pions rather than that of protons. This result lends support to theoretical models which distinguish between baryons and mesons instead of particle mass for explaining the anomalous proton yield.Comment: 326 authors, 24 pages text, 23 figures, 6 tables, RevTeX 4. To be submitted to Physical Review C as a regular article. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm

Specific Gene Expression Responses to Parasite Genotypes Reveal Redundancy of Innate Immunity in Vertebrates

Vertebrate innate immunity is the first line of defense against an invading pathogen and has long been assumed to be largely unspecific with respect to parasite/pathogen species. However, recent phenotypic evidence suggests that immunogenetic variation, i.e. allelic variability in genes associated with the immune system, results in host-parasite genotype-by-genotype interactions and thus specific innate immune responses. Immunogenetic variation is common in all vertebrate taxa and this reflects an effective immunological function in complex environments. However, the underlying variability in host gene expression patterns as response of innate immunity to within-species genetic diversity of macroparasites in vertebrates is unknown. We hypothesized that intra-specific variation among parasite genotypes must be reflected in host gene expression patterns. Here we used high-throughput RNA-sequencing to examine the effect of parasite genotypes on gene expression patterns of a vertebrate host, the three-spined stickleback (Gasterosteus aculeatus). By infecting naïve fish with distinct trematode genotypes of the species Diplostomum pseudospathaceum we show that gene activity of innate immunity in three-spined sticklebacks depended on the identity of an infecting macroparasite genotype. In addition to a suite of genes indicative for a general response against the trematode we also find parasite-strain specific gene expression, in particular in the complement system genes, despite similar infection rates of single clone treatments. The observed discrepancy between infection rates and gene expression indicates the presence of alternative pathways which execute similar functions. This suggests that the innate immune system can induce redundant responses specific to parasite genotypes

Bmi-1 Absence Causes Premature Brain Degeneration

Bmi-1, a polycomb transcriptional repressor, is implicated in cell cycle regulation and cell senescence. Its absence results in generalized astrogliosis and epilepsy during the postnatal development, but the underlying mechanisms are poorly understood. Here, we demonstrate the occurrence of oxidative stress in the brain of four-week-old Bmi-1 null mice. The mice showed various hallmarks of neurodegeneration including synaptic loss, axonal demyelination, reactive gliosis and brain mitochondrial damage. Moreover, astroglial glutamate transporters and glutamine synthetase decreased in the Bmi-1 null hippocampus, which might contribute to the sporadic epileptic-like seizures in these mice. These results indicate that Bmi-1 is required for maintaining endogenous antioxidant defenses in the brain, and its absence subsequently causes premature brain degeneration

Exact analysis of summary statistics for continuous-time discrete-state Markov processes on networks using graph-automorphism lumping

We propose a unified framework to represent a wide range of continuous-time discrete-state Markov processes on networks, and show how many network dynamics models in the literature can be represented in this unified framework. We show how a particular sub-set of these models, referred to here as single-vertex-transition (SVT) processes, lead to the analysis of quasi-birth-and-death (QBD) processes in the theory of continuous-time Markov chains. We illustrate how to analyse a number of summary statistics for these processes, such as absorption probabilities and first-passage times. We extend the graph-automorphism lumping approach [Kiss, Miller, Simon, Mathematics of Epidemics on Networks, 2017; Simon, Taylor, Kiss, J. Math. Bio. 62(4), 2011], by providing a matrix-oriented representation of this technique, and show how it can be applied to a very wide range of dynamical processes on networks. This approach can be used not only to solve the master equation of the system, but also to analyse the summary statistics of interest. We also show the interplay between the graph-automorphism lumping approach and the QBD structures when dealing with SVT processes. Finally, we illustrate our theoretical results with examples from the areas of opinion dynamics and mathematical epidemiology

Interaction of Crohn's Disease Susceptibility Genes in an Australian Paediatric Cohort

Genetic susceptibility is an important contributor to the pathogenesis of Crohn's disease (CD). We investigated multiple CD susceptibility genes in an Australian paediatric onset CD cohort. Newly diagnosed paediatric onset CD patients (n = 72) and controls (n = 98) were genotyped for 34 single nucleotide polymorphisms (SNPs) in 18 genetic loci. Gene-gene interaction analysis, gene-disease phenotype analysis and genetic risk profiling were performed for all SNPs and all genes. Of the 34 SNPs analysed, four polymorphisms on three genes (NOD2, IL23R, and region 3p21) were significantly associated with CD status (p<0.05). All three CD specific paediatric polymorphisms on PSMG1 and TNFRSF6B showed a trend of association with p<0.1. An additive gene-gene interaction involving TLR4, PSMG1, TNFRSF6B and IRGM was identified with CD. Genes involved in microbial processing (TLR4, PSMG1, NOD2) were significantly associated either at the individual level or in gene-gene interactive roles. Colonic disease was significantly associated with disease SNP rs7517847 (IL23R) (p<0.05) and colonic and ileal/colonic disease was significantly associated with disease SNP rs125221868 (IBD5) and SLC22A4 & SLC22A4/5 variants (p<0.05). We were able to demonstrate genetic association of several genes to CD in a paediatric onset cohort. Several of the observed associations have not been reported previously in association with paediatric CD patients. Our findings demonstrate that CD genetic susceptibility in paediatric patients presents as a complex interaction between numerous genes

Cervical epidural steroid injections in the management of cervical radiculitis: interlaminar versus transforaminal. A review

There has been recent concern regarding the safety of cervical epidural steroid injections. The decision to proceed with treatment requires balancing the risk and benefits. This article is an in depth review of the efficacy, complications, and technique of both interlaminar and transforaminal cervical epidural steroid injections in the management of cervical radiculitis

Genetics of human hydrocephalus

Human hydrocephalus is a common medical condition that is characterized by abnormalities in the flow or resorption of cerebrospinal fluid (CSF), resulting in ventricular dilatation. Human hydrocephalus can be classified into two clinical forms, congenital and acquired. Hydrocephalus is one of the complex and multifactorial neurological disorders. A growing body of evidence indicates that genetic factors play a major role in the pathogenesis of hydrocephalus. An understanding of the genetic components and mechanism of this complex disorder may offer us significant insights into the molecular etiology of impaired brain development and an accumulation of the cerebrospinal fluid in cerebral compartments during the pathogenesis of hydrocephalus. Genetic studies in animal models have started to open the way for understanding the underlying pathology of hydrocephalus. At least 43 mutants/loci linked to hereditary hydrocephalus have been identified in animal models and humans. Up to date, 9 genes associated with hydrocephalus have been identified in animal models. In contrast, only one such gene has been identified in humans. Most of known hydrocephalus gene products are the important cytokines, growth factors or related molecules in the cellular signal pathways during early brain development. The current molecular genetic evidence from animal models indicate that in the early development stage, impaired and abnormal brain development caused by abnormal cellular signaling and functioning, all these cellular and developmental events would eventually lead to the congenital hydrocephalus. Owing to our very primitive knowledge of the genetics and molecular pathogenesis of human hydrocephalus, it is difficult to evaluate whether data gained from animal models can be extrapolated to humans. Initiation of a large population genetics study in humans will certainly provide invaluable information about the molecular and cellular etiology and the developmental mechanisms of human hydrocephalus. This review summarizes the recent findings on this issue among human and animal models, especially with reference to the molecular genetics, pathological, physiological and cellular studies, and identifies future research directions

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

J/psi production from proton-proton collisions at sqrt(s) = 200 GeV

J/psi production has been measured in proton-proton collisions at sqrt(s)= 200 GeV over a wide rapidity and transverse momentum range by the PHENIX experiment at RHIC. Distributions of the rapidity and transverse momentum, along with measurements of the mean transverse momentum and total production cross section are presented and compared to available theoretical calculations. The total J/psi cross section is 3.99 +/- 0.61(stat) +/- 0.58(sys) +/- 0.40(abs) micro barns. The mean transverse momentum is 1.80 +/- 0.23(stat) +/- 0.16(sys) GeV/c.Comment: 326 authors, 6 pages text, 4 figures, 1 table, RevTeX 4. To be submitted to PRL. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm