HC-HDSD: A method of hypergraph construction and high-density subgraph detection for inferring high-order epistatic interactions

Detecting epistatic interactions, or nonlinear interactive effects of Single Nucleotide Polymorphisms (SNPs), has gained increasing attention in explaining the “missing heritability” of complex diseases. Though much work has been done in mapping SNPs underlying diseases, most of them constrain to 2-order epistatic interactions. In this paper, a method of hypergraph construction and high-density subgraph detection, named HC-HDSD, is proposed for detecting high-order epistatic interactions. The hypergraph is constructed by low-order epistatic interactions that identified using the normalized co-information measure and the exhaustive search. The hypergraph consists of two types of vertices: real ones representing main effects of SNPs and virtual ones denoting interactive effects of epistatic interactions. Then, both maximal clique centrality algorithm and near-clique mining algorithm are employed to detect high-density subgraphs from the constructed hypergraph. These high-density subgraphs are inferred as high-order epistatic interactions in the HC-HDSD. Experiments are performed on several simulation data sets, results of which show that HC-HDSD is promising in inferring high-order epistatic interactions while substantially reducing the computation cost. In addition, the application of HC-HDSD on a real Age-related Macular Degeneration (AMD) data set provides several new clues for the exploration of causative factors of AMD.     

Estimation of the limit of detection using information theory measures

Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise.     

The effect of hydrophobic-lipophilic interactions on chemical reactivity. 9. Putting the spotlight on lipophilic forces in solvent-effect studies

The hydrolytic rate constants of thep-nitrophenyl esters of acetic, octanoic, dodecanoic and hexadecanoic acids in six aquiorgano binary mixtures of graded compositions at various initial substrate concentrations were measured and discussed in terms of the hydrophobic-lipophilic interactions between the substrate molecules, and the organic cosolvents which were MeOH, Me₂SO, 1, 4-dioxane, 1,2-dimethoxyethane,n-propanol andt-butanol. The accelerating or retarding effects of the organic cosolvents on the rate constants of hydrolysis were found to be directly related to the lipophilicities of the solvents which were changed either by changing the content (ϕ) or the nature of the organic cosolvent. The classification or ordering of the six solvents on the basis of their solvent effects were found to conform to the lipophilicity order derived from Rekker's Σf values. The results support the proposition that lipophilic interactions can play an important role in solvent effects of aqueous binaries.