Analyzing patient health through irregular time series vital sign data demands innovative methods beyond conventional imputation techniques. This study introduces a novel approach diverging from prevailing attention-based models to explicitly capture temporal patient evolution. We adopt a paradigm where patients are viewed as dynamic systems evolving over time, with their vital signs encapsulating the system’s states. Our conceptual framework draws parallels to a Markov chain, exploring the transitions between states within a unit of time. To navigate the challenge of a vast state space, we employ a neural network to model expected transitions. Our method portrays the patient’s progression within one unit of time as the system evolves from one state to another, and forecasts states into the future. We outline the training process using irregular time series data and demonstrate its efficacy through analysis on two large vital sign data sets. Comparative analysis against attention-based models emphasizes the effectiveness and efficiency of our approach. This research heralds a promising avenue for patient vital sign analysis, providing insights into temporal patient evolution without relying on imputation methods, thereby enhancing predictive accuracy and interpretability of models.

SUMMARY: JCVI Metagenomics Reports (METAREP) is a Web 2.0 application designed to help scientists analyze and compare annotated metagenomics datasets. It utilizes Solr/Lucene, a high-performance scalable search engine, to quickly query large data collections. Furthermore, users can use its SQL-like query syntax to filter and refine datasets. METAREP provides graphical summaries for top taxonomic and functional classifications as well as a GO, NCBI Taxonomy and KEGG Pathway Browser. Users can compare absolute and relative counts of multiple datasets at various functional and taxonomic levels. Advanced comparative features comprise statistical tests as well as multidimensional scaling, heatmap and hierarchical clustering plots. Summaries can be exported as tab-delimited files, publication quality plots in PDF format. A data management layer allows collaborative data analysis and result sharing. AVAILABILITY: Web site http://www.jcvi.org/metarep; source code http://github.com/jcvi/METAREP CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: DNA sequence reads from Sanger and pyrosequencing platforms differ in cost, accuracy, typical coverage, average read length and the variety of available paired-end protocols. Both read types can complement one another in a 'hybrid' approach to whole-genome shotgun sequencing projects, but assembly software must be modified to accommodate their different characteristics. This is true even of pyrosequencing mated and unmated read combinations. Without special modifications, assemblers tuned for homogeneous sequence data may perform poorly on hybrid data. RESULTS: Celera Assembler was modified for combinations of ABI 3730 and 454 FLX reads. The revised pipeline called CABOG (Celera Assembler with the Best Overlap Graph) is robust to homopolymer run length uncertainty, high read coverage and heterogeneous read lengths. In tests on four genomes, it generated the longest contigs among all assemblers tested. It exploited the mate constraints provided by paired-end reads from either platform to build larger contigs and scaffolds, which were validated by comparison to a finished reference sequence. A low rate of contig mis-assembly was detected in some CABOG assemblies, but this was reduced in the presence of sufficient mate pair data. AVAILABILITY: The software is freely available as open-source from http://wgs-assembler.sf.net under the GNU Public License.

BACKGROUND: Polymerase chain reaction (PCR) is used in directed sequencing for the discovery of novel polymorphisms. As the first step in PCR directed sequencing, effective PCR primer design is crucial for obtaining high-quality sequence data for target regions. Since current computational primer design tools are not fully tuned with stable underlying laboratory protocols, researchers may still be forced to iteratively optimize protocols for failed amplifications after the primers have been ordered. Furthermore, potentially identifiable factors which contribute to PCR failures have yet to be elucidated. This inefficient approach to primer design is further intensified in a high-throughput laboratory, where hundreds of genes may be targeted in one experiment. RESULTS: We have developed a fully integrated computational PCR primer design pipeline that plays a key role in our high-throughput directed sequencing pipeline. Investigators may specify target regions defined through a rich set of descriptors, such as Ensembl accessions and arbitrary genomic coordinates. Primer pairs are then selected computationally to produce a minimal amplicon set capable of tiling across the specified target regions. As part of the tiling process, primer pairs are computationally screened to meet the criteria for success with one of two PCR amplification protocols. In the process of improving our sequencing success rate, which currently exceeds 95% for exons, we have discovered novel and accurate computational methods capable of identifying primers that may lead to PCR failures. We reveal the laboratory protocols and their associated, empirically determined computational parameters, as well as describe the novel computational methods which may benefit others in future primer design research. CONCLUSION: The high-throughput PCR primer design pipeline has been very successful in providing the basis for high-quality directed sequencing results and for minimizing costs associated with labor and reprocessing. The modular architecture of the primer design software has made it possible to readily integrate additional primer critique tests based on iterative feedback from the laboratory. As a result, the primer design software, coupled with the laboratory protocols, serves as a powerful tool for low and high-throughput primer design to enable successful directed sequencing.

Current HTTP servers process requests using a first-come first-serve queuing policy. What this implies is that the WWW server must process each request as it arrives. The result is that the more requests a client makes, the more replies the server will generate in response. Unfortunately, the bandwidth of the network and the processing capabilities of the server are often limited resulting in an aggressive client, or sets of clients, consuming the majority of the server's resources, limiting other clients' ability to use their fair allocation. While the traditional behavior of a Web server works efficiently for a Web site that is non-discriminating towards all clients, guaranteeing service for preferred clients from the server itself is not yet possible. This paper describes the algorithm we have designed and implemented on the Apache HTTP server, which has been shown to be effective in allocating configurable fixed percentages of bandwidth across numerous simultaneous clients, independent of the aggressiveness of the clients' requests.