BackgroundThe knowledge base-driven pathway analysis is becoming the first choice for many investigators, in that it not only can reduce the complexity of functional analysis by grouping thousands of genes into just several hundred pathways, but also can increase the explanatory power for the experiment by identifying active pathways in different conditions. However, current approaches are designed to analyze a biological system assuming that each pathway is independent of the other pathways.ResultsA decision analysis model is developed in this article that accounts for dependence among pathways in time-course experiments and multiple treatments experiments. This model introduces a decision coefficient—a designed index, to identify the most relevant pathways in a given experiment by taking into account not only the direct determination factor of each Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway itself, but also the indirect determination factors from its related pathways. Meanwhile, the direct and indirect determination factors of each pathway are employed to demonstrate the regulation mechanisms among KEGG pathways, and the sign of decision coefficient can be used to preliminarily estimate the impact direction of each KEGG pathway. The simulation study of decision analysis demonstrated the application of decision analysis model for KEGG pathway analysis.ConclusionsA microarray dataset from bovine mammary tissue over entire lactation cycle was used to further illustrate our strategy. The results showed that the decision analysis model can provide the promising and more biologically meaningful results. Therefore, the decision analysis model is an initial attempt of optimizing pathway analysis methodology.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1285-1) contains supplementary material, which is available to authorized users.

BackgroundLack of clear risk factor identification is the main reason for the persistence of brucellosis infection in the Chinese population, and there has been little assessment of the factors contributing to Brucella contamination of raw whole milk. The purpose of this study was to identify risk factors affecting Brucella contamination of raw milk, and to evaluate effective measures for disease reduction in order to determine preventive strategies.Methods and FindingsA nationwide survey was conducted and samples were obtained from 5211 cows corresponding to 25 sampling locations throughout 15 provinces in China. The prevalence of Brucella in the raw milk samples averaged 1.07% over the 15 Chinese provinces, while the prevalence of positive areas within these regions ranged from 0.23–3.84% among the nine provinces with positive samples. The survey examined factors that supposedly influence Brucella contamination of raw whole milk, such as management style, herd size, abortion rate, hygiene and disease control practices. A binary logistic regression analysis was carried out to determine the association between risk factors for Brucella and contamination of milk samples. Furthermore, a relative effect decomposition study was conducted to determine effective strategies for reducing the risk of Brucella contamination of raw whole milk. Our data indicate that disease prevention and control measures, abortion rate, and animal polyculture are the most important risk factors. Meanwhile, culling after quarantine was identified as an effective protective measure in the current Chinese dairy situation.ConclusionsThese results indicate that, although there is a low risk of contamination of milk with Brucella nationwide in China, there are individual regions where contamination is a significant problem. Controlling three factors–culling after quarantine, maintaining a low abortion rate, and avoiding mixing groups of cattle and small ruminants–could effectively reduce the risk of Brucella contamination of raw whole milk.

Biology sequence comparison is a fundamental task in computational biology. According to the hydropathy profile of amino acids, a protein sequence is taken as a string with three letters. Three curves of the new protein sequence were defined to describe the protein sequence. A new method to analyze the similarity/dissimilarity of protein sequence was proposed based on the conditional probability of the protein sequence. Finally, the protein sequences of ND6 (NADH dehydrogenase subunit 6) protein of eight species were taken as an example to illustrate the new approach. The results demonstrated that the method is convenient and efficient.

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Soil water is a key factor limiting plant growth in water-limited regions. Without limit of soil water used by plants, soil degradation in the form of soil desiccation is easy to take place in the perennial forestland and grassland with too higher density or productivity. Soil water resources use limit (SWRUL) is the lowest control limit of soil water resources which is used by plants in those regions. It can be defined as soil water storage within the maximum infiltration depth in which all of soil layers belong to dried soil layers. In this paper, after detailed discussion of characteristics of water resources and the relationship between soil water and plant growth in the Loess Plateau, the definition, quantitative method, and practical applications of SWRUL are introduced. Henceforth, we should strengthen the study of SWRUL and have a better understanding of soil water resources. All those are of great importance for designing effective restoration project and sustainable management of soil water resources in waterlimited regions in the future.