High functional coherence in k-partite protein cliques of protein interaction networks

We introduce a new topological concept called k-partite protein cliques to study protein interaction (PPI) networks. In particular, we examine functional coherence of proteins in k-partite protein cliques. A k-partite protein clique is a k-partite maximal clique comprising two or more nonoverlapping protein subsets between any two of which full interactions are exhibited. In the detection of PPI’s k-partite maximal cliques, we propose to transform PPI networks into induced K-partite graphs with proteins as vertices where edges only exist among the graph’s partites. Then, we present a k-partite maximal clique mining (MaCMik) algorithm to enumerate k-partite maximal cliques from K-partite graphs. Our MaCMik algorithm is applied to a yeast PPI network. We observe that there does exist interesting and unusually high functional coherence in k-partite protein cliques—most proteins in k-partite protein cliques, especially those in the same partites, share the same functions. Therefore, the idea of k-partite protein cliques suggests a novel approach to characterizing PPI networks, and may help function prediction for unknown proteins.

Using gene-history and expression analyses to assess the involvement of LGI genes in human disorders

Mutations in the leucine-rich, glioma-inactivated 1 gene, LGI1, cause autosomal-dominant lateral temporal lobe epilepsy via unknown mechanisms. LGI1 belongs to a subfamily of leucine-rich repeat genes comprising four members (LGI1–LGI4) in mammals. In this study, both comparative developmental as well as molecular evolutionary methods were applied to investigate the evolution of the LGI gene family and, subsequently, of the functional importance of its different gene members. Our phylogenetic studies suggest that LGI genes evolved early in the vertebrate lineage. Genetic and expression analyses of all five zebrafish lgi genes revealed duplications of lgi1 and lgi2, each resulting in two paralogous gene copies with mostly nonoverlapping expression patterns. Furthermore, all vertebrate LGI1 orthologs experience high levels of purifying selection that argue for an essential role of this gene in neural development or function. The approach of combining expression and selection data used here exemplarily demonstrates that in poorly characterized gene families a framework of evolutionary and expression analyses can identify those genes that are functionally most important and are therefore prime candidates for human disorders.

Population genetic structure, gene flow and sex-biased dispersal in frillneck lizards (Chlamydosaurus kingii)

By using both mitochondrial and nuclear multiloci markers, we explored population genetic structure, gene flow and sex-specific dispersal of frillneck lizards (Chlamydosaurus kingii) sampled at three locations, separated by 10 to 50 km, in a homogenous savannah woodland in tropical Australia. Apart from a recombinant lizard, the mitochondrial analyses revealed two nonoverlapping haplotypes/populations, while the nuclear markers showed that the frillneck lizards represented three separate clusters/populations. Due to the small population size of the mtDNA, fixation may occur via founder effects and/or drift. We therefore suggest that either of these two processes, or a combination of the two, are the most likely causes of the discordant results obtained from the mitochondrial and the nuclear markers. In contrast to the nonoverlapping mitochondrial haplotypes, in 12 out of 74 lizards, mixed nuclear genotypes were observed, hence revealing a limited nuclear gene flow. Although gene flow should ultimately result in a blending of the populations, we propose that the distinct nuclear population structure is maintained by frequent fires resulting in local bottlenecks, and concomitant spatial separation of the frillneck lizard populations. Limited mark-recapture data and the difference in distribution of the mitochondrial and nuclear markers suggest that the mixed nuclear genotypes were caused by juvenile male-biased dispersal.

A comprehensive analytical subdomain model and its field solutions for surface-mounted permanent magnet machines

This paper presents a comprehensive analytical subdomain model together with its field solutions for predicting the magnetic field distributions in surface-mounted permanent magnet (PM) machines. The tooth tips and slotting effects during open-circuit, armature reaction, and on-load conditions are considered when deriving the model and developing its solutions. The model derivations and field solutions are extended from a previous model, and can be applied to PM machines with any combinations of slot and pole numbers and any magnetization patterns in the magnets. This model is initially formulated according to Laplace's and Poisson's equations in 2-D polar coordinates by the separation of variables technique in four subdomains, such as magnet, airgap, winding slots, and slot-openings. The field solution of each subdomain is obtained applying the appropriate boundary conditions and interface conditions between every two subdomains, respectively, which can precisely account for the mutual influence between slots. Finite element analysis (FEA) is later deployed to validate the analytical results in a surface-mounted PM machine that has nonoverlapping winding arrangement. For validation purposes, PM machines having 3-slot/2-pole with parallel magnetization and 12-slot/10-pole with either parallel or radial magnetizations are used for comparisons. Computation of global quantities for the motor which include the phase back-EMF and cogging torque is also included. The results indicate that the proposed analytical model can accurately predict the magnetic field distributions in each subdomain and the motor's global quantities, which are in good agreement with those obtained from the FEA.