It's challenging work to identify disease-causing genes from the next-generation sequencing (NGS) data of patients with Mendelian disorders. To improve this situation, researchers have developed many phenotype-driven gene prioritization methods using a patient's genotype and phenotype information, or phenotype information only as input to rank the candidate's pathogenic genes. Evaluations of these ranking methods provide practitioners with convenience for choosing an appropriate tool for their workflows, but retrospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate. In this research, the performance of ten recognized causal-gene prioritization methods was benchmarked using 305 cases from the Deciphering Developmental Disorders (DDD) project and 209 in-house cases via a relatively unbiased methodology. The evaluation results show that methods using Human Phenotype Ontology (HPO) terms and Variant Call Format (VCF) files as input achieved better overall performance than those using phenotypic data alone. Besides, LIRICAL and AMELIE, two of the best methods in our benchmark experiments, complement each other in cases with the causal genes ranked highly, suggesting a possible integrative approach to further enhance the diagnostic efficiency. Our benchmarking provides valuable reference information to the computer-assisted rapid diagnosis in Mendelian diseases and sheds some light on the potential direction of future improvement on disease-causing gene prioritization methods.

Fluorescence lifetime imaging (FLIM) is used for measuring material properties in a wide range of applications, including biology, medical imaging, chemistry, and material science. In frequency-domain FLIM (FD-FLIM), the object of interest is illuminated with a temporally modulated light source. The fluorescence lifetime is measured by computing the correlations of the emitted light with a demodulation function at the sensor. The signal-to-noise ratio (SNR) and the acquisition time of a FD-FLIM system is determined by the coding scheme (modulation and demodulation functions). In this article, we develop theory and algorithms for designing high-performance FD-FLIM coding schemes that can achieve high SNR and short acquisition time, given a fixed source power budget. Based on a geometric analysis of the image formation and noise model, we propose a novel surrogate objective for the performance of a given coding scheme. The surrogate objective is extremely fast to compute, and can be used to efficiently explore the entire space of coding schemes. Based on this objective, we design novel, high-performance coding schemes that achieve up to an order of magnitude shorter acquisition time as compared to existing approaches. We demonstrate the performance advantage of the proposed schemes in a variety of imaging conditions, using a modular hardware prototype that can implement various coding schemes.

The star schema is widely accepted as the de facto data model for data warehouse design. A popular approach for developing a star schema is to develop it from an entity-relationship diagram with some heuristics. Most of the existing approaches analyze the semantics of an ERD to generate a star schema. In this paper, we present the SAMSTAR method, which semi-automatically generates star schemas from an ERD by analyzing its semantics as well as structure. The novel features of SAMSTAR are (1) the use of the notion of Connection Topology Value (CTV) in identifying the candidates of facts and dimensions and (2) the use of Annotated Dimensional Design Patterns (A_DDP) as well as WordNet to extend the list of dimensions. We illustrate our method by applying it to the examples from existing literature. We prove that the outputs of our method are a superset of those of the existing methods. The SAMSTAR method simplifies the work of experienced designers and gives a smooth head-start to novices.

The objective of the medical teleconsultation system presented in this paper is to demonstrate the use of the World Wide Web (WWW) for telemedicine and interactive medical information exchange. The system, which is developed based on Java, could provide several basic Java tools to fulfill the requirements of medical applications, including a file manager, data tool, bulletin board, and digital audio tool. The digital audio tool uses point-to-point structure to enable two physicians to communicate directly through voice. The others use multipoint structure. The file manager manages the medical images stored in the WWW information server, which come from a hospital database. The data tool supports cooperative operations on the medical data between the participating physicians. The bulletin board enables the users to discuss special cases by writing text on the board, send their personal or group diagnostic reports on the cases, and reorganize the reports and store them in its report file for later use. The system provides a hardware-independent platform for physicians to interact with one another as well as to access medical information over the WWW.