A novel radial basis function neural network for fault section estimation in transmission network

In this paper, the application of Radial Basis Function Neural Network (RBF NN) to fault section estimation in power systems is addressed. The orthogonal least square algorithm has been extended to optimize the parameters of RBF NN. In order to assess the effectiveness of RBF NN, a classical Back-Propagation Neural Network (BP NN) has been developed to solve the same problem for comparison. Computer test is conducted on a 4-bus test system and the test results show that the RBF NN is quite effective and superior to BP NN in fault section estimation.published_or_final_versio

Defining the Plasticity of Transcription Factor Binding Sites by Deconstructing DNA Consensus Sequences: The PhoP-Binding Sites among Gamma/Enterobacteria

Transcriptional regulators recognize specific DNA sequences. Because these sequences are embedded in the background of genomic DNA, it is hard to identify the key cis-regulatory elements that determine disparate patterns of gene expression. The detection of the intra- and inter-species differences among these sequences is crucial for understanding the molecular basis of both differential gene expression and evolution. Here, we address this problem by investigating the target promoters controlled by the DNA-binding PhoP protein, which governs virulence and Mg2+ homeostasis in several bacterial species. PhoP is particularly interesting; it is highly conserved in different gamma/enterobacteria, regulating not only ancestral genes but also governing the expression of dozens of horizontally acquired genes that differ from species to species. Our approach consists of decomposing the DNA binding site sequences for a given regulator into families of motifs (i.e., termed submotifs) using a machine learning method inspired by the “Divide & Conquer” strategy. By partitioning a motif into sub-patterns, computational advantages for classification were produced, resulting in the discovery of new members of a regulon, and alleviating the problem of distinguishing functional sites in chromatin immunoprecipitation and DNA microarray genome-wide analysis. Moreover, we found that certain partitions were useful in revealing biological properties of binding site sequences, including modular gains and losses of PhoP binding sites through evolutionary turnover events, as well as conservation in distant species. The high conservation of PhoP submotifs within gamma/enterobacteria, as well as the regulatory protein that recognizes them, suggests that the major cause of divergence between related species is not due to the binding sites, as was previously suggested for other regulators. Instead, the divergence may be attributed to the fast evolution of orthologous target genes and/or the promoter architectures resulting from the interaction of those binding sites with the RNA polymerase

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Hybrid fault section estimation system with radial basis function neural network and fuzzy system

In this paper, functional equivalence between a radial basis function neural networks (RBF NN) and a companion fuzzy system (CFS) is built up throughout the neural network training process, therefore the black-box-like knowledge in a RBF NN will be rule-based and transparent in its CFS. Through useful knowledge extraction from the old CFS and insertion back to the new CFS piece by piece, the RBF NN retraining issue under network expansion and topology change can be solved effectively and efficiently. The corresponding FSE system has been implemented and tested in the IEEE 118-bus power system. The simulation results show that the suggested approach for RBF NN retraining works successfully and efficiently in the case of power network expansion and topology change, which significantly improves the application potential of RBF NN in FSE of practical power systems.link_to_subscribed_fulltex

Expression and biological function of rhotekin in gastric cancer through regulating p53 pathway

Meng-Yao Sun,1,* Hong Zhang,2,* Jie Tao,1 Zhen-Hua Ni,1 Qiu-Xue Wu,1 Qing-Feng Tang1 1Department of Clinical Laboratory and Central Laboratory, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200062, China; 2Center for Innovative Chinese Medicine Research, Institute of Interdisciplinary Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China *These authors contributed equally to this work Background/aim: Gastric cancer (GC) is one of a most threatening cancer globally. Rhotekin (RTKN), a Rho effector, has been reported to be upregulated in GC tissues. This study aimed to investigate the underlying regulatory roles of RTKN in the biological behavior of GC. Methods: Real-time PCR and Western blotting were carried out to detect the mRNA and protein expression, respectively. Cell Counting Kit-8 and xenograft nude mice model were used to evaluate cell proliferation. Flow cytometry analysis was performed to assess cell cycle distribution and cell apoptosis. Results: RTKN had high expression level in GC compared with normal tissues. RTKN expression strongly associated with tumor size, TNM stage, lymphnode metastasis and the poor prognosis of patients with GC. Downregulation of RTKN significantly repressed GC cell proliferation, but increased cell population in G1/S phase and induced cell apoptosis. Moreover, the RTKN expression level was related to the p53 signaling pathway and histone deacetylase (HDAC) Class I pathway. RTKN knockdown caused a notable increment in the acetylation level of p53 (Lys382), and the expression of p53-target genes (p21, Bax, and PUMA), as well as a reduction in the expression of a potential deacetylase for p53, HDAC1. Notably, downregulation of HDAC1 had similar effects as RTKN knockdown, and RTKN overexpression could hardly abrogate the effects of HDAC1 knockdown on GC cells. Conclusion: RTKN could work as an oncogene via regulating HDAC1/p53 and may become a promising treatment strategy for GC. Keywords: RTKN, gastric cancer, proliferation, invasion, HDAC1/p5