Empirical evaluation of scoring functions for Bayesian network model selection

In this work, we empirically evaluate the capability of various scoring functions of Bayesian networks for recovering true underlying structures. Similar investigations have been carried out before, but they typically relied on approximate learning algorithms to learn the network structures. The suboptimal structures found by the approximation methods have unknown quality and may affect the reliability of their conclusions. Our study uses an optimal algorithm to learn Bayesian network structures from datasets generated from a set of gold standard Bayesian networks. Because all optimal algorithms always learn equivalent networks, this ensures that only the choice of scoring function affects the learned networks. Another shortcoming of the previous studies stems from their use of random synthetic networks as test cases. There is no guarantee that these networks reflect real-world data. We use real-world data to generate our gold-standard structures, so our experimental design more closely approximates real-world situations. A major finding of our study suggests that, in contrast to results reported by several prior works, the Minimum Description Length (MDL) (or equivalently, Bayesian information criterion (BIC)) consistently outperforms other scoring functions such as Akaike\u27s information criterion (AIC), Bayesian Dirichlet equivalence score (BDeu), and factorized normalized maximum likelihood (fNML) in recovering the underlying Bayesian network structures. We believe this finding is a result of using both datasets generated from real-world applications rather than from random processes used in previous studies and learning algorithms to select high-scoring structures rather than selecting random models. Other findings of our study support existing work, e.g., large sample sizes result in learning structures closer to the true underlying structure; the BDeu score is sensitive to the parameter settings; and the fNML performs pretty well on small datasets. We also tested a greedy hill climbing algorithm and observed similar results as the optimal algorithm

NCK2 Is Significantly Associated with Opiates Addiction in African-Origin Men

Substance dependence is a complex environmental and genetic disorder with significant social and medical concerns. Understanding the etiology of substance dependence is imperative to the development of effective treatment and prevention strategies. To this end, substantial effort has been made to identify genes underlying substance dependence, and in recent years, genome-wide association studies (GWASs) have led to discoveries of numerous genetic variants for complex diseases including substance dependence. Most of the GWAS discoveries were only based on single nucleotide polymorphisms (SNPs) and a single dichotomized outcome. By employing both SNP- and gene-based methods of analysis, we identified a strong (odds ratio = 13.87) and significant (P value = 1.33E−11) association of an SNP in the NCK2 gene on chromosome 2 with opiates addiction in African-origin men. Codependence analysis also identified a genome-wide significant association between NCK2 and comorbidity of substance dependence (P value = 3.65E−08) in African-origin men. Furthermore, we observed that the association between the NCK2 gene (P value = 3.12E−10) and opiates addiction reached the gene-based genome-wide significant level. In summary, our findings provided the first evidence for the involvement of NCK2 in the susceptibility to opiates addiction and further revealed the racial and gender specificities of its impact

A decision analysis model for KEGG pathway analysis

The 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. A 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. A 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.https://doi.org/10.1186/s12859-016-1285-

Guardian spirit of be (Shaman) and Culture tradition : For ongdin - taban - tnger ritual

This file provide the detailed impact direction data of selected KEGG pathway categories, subcategories and the secondary pathways from− 15 to 300 vs.− 30d in bovine mammary tissue during lactation in Table S2 (a) and (b), respectively. The numbers colored in red color are the filled data by the average of all the other impact values in this pathway, which is the missing data originally. (DOCX 35 kb

Identification of anti-Jra antibodies by serology and mass spectrometry

Objective To report the antibody specific identification process of a pregnant woman who had no history of blood transfusion but presented high-frequency anti-Jra antibodies. Methods Antibody screening and identification were performed by saline and indirect Coomb’s technique (microcolumn gel card, PEG). ABO, Rh and other blood group antigens were identified by saline. Further antibody identification tests were performed by the reaction between cells treated with various enzymes and patient plasma. Jra antigen was identified by human anti-Jra antibody. JR blood type genotyping was performed by MALDI-TOF mass spectrometry detection system. Antibody titer in serum was tested. Results The patient′s blood type was O with RhD(+ ) and CcDEe. The plasma reacted negatively with antibody screening and identification cells by saline, but positively by indirect globulin test. The self-control was negative. The patient′s Jra antigen was negative in serological tests and mass spectrometry blood type genotyping. Mass spectrometry revealed a homozygous nonsense mutation (c.376C>T) in exon 4. The anti-Jra antibody titer was 1∶2. Conclusion The patient developed high-frequency anti-Jra antibodies during pregnancy

The 102 Landslide: human-slope interaction in SE Tibet over a 20-year period

The evolution of large- scale landslides should be studied because, over long periods of time, primary remediation measures may suffer reduced efficiency or have to be adjusted many times. The 102 Landslide in southeast Tibet, which originally formed in 1991 with a volume of 5.1 million m(3) and still exhibits post- failure activity, provides a distinctive case study. The landslide evolved from earthquake destruction and unloading, rainfall- triggered sliding, and debris flow to sands sliding slopes. The NE ringed scarp receded by 38.96 m during a five- year period (2003-2008). The total recession was 160 m with a total area of 2500 m (2) during a 17-year period (1991-2008). Although several types of remediation measures were applied and were temporarily effective, the normal function of the Sichuan-Tibet Highway was affected by landslide reactivation from time to time. Actual effects of the engineering measures such as retaining walls, prestressed anchor cables, and drainage ditches confirm that hasty governance of this type of large-scale landslide is generally unfeasible over long time periods. Finally, an approach involving a tunnel running backward from the front face has been adopted as a permanent solution to large-scale moraine slope failures: This engineering practice has been in progress since April 2012. This paper describes the evolution of the 102 Landslide, the engineering interventions to mitigate the effects of the landslide on the Sichuan-Tibet Highway, and the choice of tunneling as a final mitigation measure. The present study concludes that approaches that allow escape from developing geohazards should always be the initial choice.N

Additional file 1: Table S8. of A decision analysis model for KEGG pathway analysis

This file provides the original DIA impact values and the detailed subdivided results of decision coefficient for the other KEGG subcategory pathways and the other KEGG secondary pathways in Table S8 (a)–(d), respectively. In order to distinguish between the direct and indirect determination factor clearly, the direct determination factor has been indicated in red box. (DOCX 67 kb