A clustering-based approach for efficient identification of microRNA combinatorial biomarkers.

BACKGROUND: MicroRNAs (miRNAs) have great potential serving as tumor biomarkers and therapeutic targets. As the rapid development of high-throughput experimental technology, gene expression experiments have become more and more specialized and diversified. The complex data structure has brought great challenge for the identification of biomarkers. In the meantime, current statistical and machine learning methods for detecting biomarkers have the problem of low reliability and biased criteria. RESULTS: This study aims to select combinatorial miRNA biomarkers, which have higher sensitivity and specificity than single-gene biomarkers. In order to avoid exhaustive search and redundant information, miRNAs are firstly clustered, then the combinations of representative cluster members are assessed as potential biomarkers. Both the criteria for the partition of clusters and selection of representative members are based on Fisher linear discriminant analysis (FDA). The FDA-based criterion has been demonstrated to be superior to three other criteria in selecting representative members, and also good at refining clusters. In the comparison with eight common feature selection methods, this clustering-based method performs the best with regard to the discriminative ability of selected biomarkers. CONCLUSIONS: Our experimental results demonstrate that the clustering-based method can identify microRNA combinatorial biomarkers with high accuracy and efficiency. Our method and data are available to the public upon request.

NCBI's Database of Genotypes and Phenotypes: dbGaP.

The Database of Genotypes and Phenotypes (dbGap, http://www.ncbi.nlm.nih.gov/gap) is a National Institutes of Health-sponsored repository charged to archive, curate and distribute information produced by studies investigating the interaction of genotype and phenotype. Information in dbGaP is organized as a hierarchical structure and includes the accessioned objects, phenotypes (as variables and datasets), various molecular assay data (SNP and Expression Array data, Sequence and Epigenomic marks), analyses and documents. Publicly accessible metadata about submitted studies, summary level data, and documents related to studies can be accessed freely on the dbGaP website. Individual-level data are accessible via Controlled Access application to scientists across the globe.

Numerical Modelling of the Dynamic Voltage in HTS Materials under the Action of DC Transport Currents and Different Oscillating Magnetic Fields.

The dynamic voltage is a unique phenomenon of superconducting materials. It arises when the superconductor is carrying a DC transport current and spontaneously in subject to an AC magnetic field. This study excavates the aspects that previous studies have not comprehensively investigated: the dynamic voltage in a DC-carrying superconducting tape exposed to different oscillating AC magnetic fields. First, the fundamental physics of dynamic voltage/flux of superconductors is reviewed and further analysed in detail. We used the superconducting modelling method using the H-formulation merged into the finite-element method (FEM) software, to re-produce the typical dynamic voltage behaviour of a superconducting tape. The modelling was verified by both the analytical and experimental results, in order to precisely prove the reliability of the modelling. Afterwards, the modelling was performed for a DC-carrying superconducting tape under four different oscillating magnetic fields (sine, triangle, sawtooth and square), and their corresponding dynamic voltages and energy losses were analysed and compared. Results show the sinusoidal magnetic field can lead to the optimal combination of reasonable dynamic voltage but relatively lower loss, which is suitable for those superconducting applications requiring dynamic voltage as the energy source, e.g., flux pumps. This article presents novel investigation and analysis of the dynamic voltage in superconducting materials, and both the methodology and results can provide useful information for the future design/analysis of superconducting applications with DC transport currents and AC magnetic fields.

On fault-mode phenomenon in no-insulation superconducting magnets: A preventive approach.

Here, we present experimental and analytical results of a preventive approach applied to a fault-mode phenomenon caused by electrodes or power-source failure in a no-insulation (NI) high-temperature superconducting REBa2Cu3O7-x (REBCO, RE = rare earth) magnet. It is generally agreed that the NI magnets, at least those of laboratory scale, are self-protected from overheating and, therefore, from quenching, chiefly because of turn-to-turn current bypassing unique to NI. However, these NI magnets do experience unexpected quenches, e.g., when the current through the magnet suddenly drops due to the aforementioned fault-mode phenomenon. Here, we report this phenomenon of a sudden-discharging-triggered quench of an NI REBCO coil, conduction-cooled, and operated at 4.2 K. We also present our preventive approach for this phenomenon that relies on an appropriately designed resistor shunted across the coil terminals. With this shunt resistor, a quench was prevented by suppressing the quench initiating turn-to-turn heat and induced overcurrent within the NI winding, and the coil current decayed safely.

CDD: a conserved domain database for interactive domain family analysis.

The conserved domain database (CDD) is part of NCBI's Entrez database system and serves as a primary resource for the annotation of conserved domain footprints on protein sequences in Entrez. Entrez's global query interface can be accessed at http://www.ncbi.nlm.nih.gov/Entrez and will search CDD and many other databases. Domain annotation for proteins in Entrez has been pre-computed and is readily available in the form of 'Conserved Domain' links. Novel protein sequences can be scanned against CDD using the CD-Search service; this service searches databases of CDD-derived profile models with protein sequence queries using BLAST heuristics, at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi. Protein query sequences submitted to NCBI's protein BLAST search service are scanned for conserved domain signatures by default. The CDD collection contains models imported from Pfam, SMART and COG, as well as domain models curated at NCBI. NCBI curated models are organized into hierarchies of domains related by common descent. Here we report on the status of the curation effort and present a novel helper application, CDTree, which enables users of the CDD resource to examine curated hierarchies. More importantly, CDD and CDTree used in concert, serve as a powerful tool in protein classification, as they allow users to analyze protein sequences in the context of domain family hierarchies.

An on-board 2G HTS magnets system with cooling-power-free and persistent-current operation for ultrahigh speed superconducting maglevs.

Introduction of superconductor to magnetic levitation (maglev) trains greatly enhances the performances compared to those of normal conductor maglevs, e.g. from 430 km/h of the Transrapid (in Shanghai) to 603 km/h of the L0 Series in Japan. However, one of the important constraints on development of superconducting maglevs is limited wireless feeding power for on-board superconducting magnets and cryogenic cooling. In this paper, a persistent-current superconducting magnets system with solid nitrogen (SN2) cooling preservation is proposed for liberation of its demanding on-board power feeding requirement. The magnets are optimally designed with no-insulation technique guaranteeing a safe operation with magnetic field over 0.8 T. Lasting time of persistent current (at 96.5% magnetic field retained) and SN2 cooling preservation (up to 40 K) is all >9 h, covering a maglev traveling distance of >5400 km at average designed speed of >600 km/h. The magnets have anti-vibration ability of 15 g (147 m/s2) up to 350 Hz, which has covered the vibratory motion range in maglevs. This work is intended to provide a reference for superconducting maglev developments.

The NCBI dbGaP database of genotypes and phenotypes.

The National Center for Biotechnology Information has created the dbGaP public repository for individual-level phenotype, exposure, genotype and sequence data and the associations between them. dbGaP assigns stable, unique identifiers to studies and subsets of information from those studies, including documents, individual phenotypic variables, tables of trait data, sets of genotype data, computed phenotype-genotype associations, and groups of study subjects who have given similar consents for use of their data.