Graph kernel of brain networks considering functional similarity measures.

As a tool of brain network analysis, the graph kernel is often used to assist the diagnosis of neurodegenerative diseases. It is used to judge whether the subject is sick by measuring the similarity between brain networks. Most of the existing graph kernels calculate the similarity of brain networks based on structural similarity, which can better capture the topology of brain networks, but all ignore the functional information including the lobe, centers, left and right brain to which the brain region belongs and functions of brain regions in brain networks.

BIC-LP: A Hybrid Higher-Order Dynamic Bayesian Network Score Function for Gene Regulatory Network Reconstruction.

Reconstructing gene regulatory networks(GRNs) is an increasingly hot topic in bioinformatics. Dynamic Bayesian network(DBN) is a stochastic graph model commonly used as a vital model for GRN reconstruction. But probabilistic characteristics of biological networks and the existence of data noise bring great challenges to GRN reconstruction and always lead to many false positive/negative edges.

The Analysis of Relevant Gene Networks Based on Driver Genes in Breast Cancer.

Background: The occurrence and development of breast cancer has a strong correlation with a person's genetics. Therefore, it is important to analyze the genetic factors of breast cancer for future development of potential targeted therapies from the genetic level.

Methods: In this study, we complete an analysis of the relevant protein-protein interaction network relating to breast cancer.

is a later heterotypic synonym of , and transfer of to the genus as comb. nov.

The 16S rRNA genes of G7 and FJ12 shared 100 % sequence identity with AM-4. Phylogeny of 16S rRNA gene sequences showed that the three type strains formed a monophyletic clade within the genus . Whole genome sequence comparisons showed that three type strains shared 46.