Catálogo de publicaciones - libros

Algorithms for detecting anomalous events can be divided into those that are designed to detect specific diseases and those that are non-specific in what they detect. Specific detection methods determine if patterns in the data are consistent with known outbreak diseases, as for example influenza. These methods are usually Bayesian. Non-specific detection methods attempt broadly to detect deviations from some model of the non-outbreak situation, regardless of which disease might be causing the deviation. Many frequentist outbreak detection methods are non-specific. In this paper, we introduce a Bayesian approach for detecting both specific and non-specific disease outbreaks, and we report a preliminary study of the approach.

An exploration in Symbolic Computational bio-surveillance is showed. The main obtained results are that the geometry of the habitat determines the critical parameters via the zeroes of the Bessel functions and the explicit forms of the static and non-static spatial epidemic patterns.

Conserved regions, or motifs, present among RNA secondary structures serve as a useful indicator for predicting the functionality of the RNA molecules. Automated detection or discovery of these conserved regions is emerging as an important research topic in health and disease informatics. In this short paper we present a new approach for detecting conserved regions in RNA secondary structures by the use of constrained alignment and apply the approach to finding structural motifs in some viral genomes. Our experimental results show that the proposed approach is capable of efficiently detecting conserved regions in the viral genomes and is comparable to existing methods. We implement our constrained structure alignment algorithm into a web server, called RADAR. This web server is fully operational and accessible on the Internet at http://datalab.njit.edu/biodata/rna/RSmatch/server.htm.

The Gemina system (http://gemina.tigr.org) developed at TIGR is a tool for identification of microbial and viral pathogens and their associated genomic sequences based on the associated epidemiological data. Gemina has been designed as a tool to identify epidemiological factors of disease incidence and to support the design of DNA-based diagnostics such as the development of DNA signature-based assays. The Gemina database contains the full complement of microbial and viral pathogens enumerated in the Microbial Rosetta Stone database (MRS) [1]. Initially, curation efforts in Gemina have focused on the NIAID category A, B, and C priority pathogens [2] identified to the level of strains. For the bacterial NIAID category A-C pathogens, for example, we have included 38 species and 769 strains in Gemina. Representative genomic sequences are selected for each pathogen from NCBI’s GenBank by a three tiered filtering system and incorporated into TIGR’s Panda DNA sequence database. A single representative sequence is selected for each pathogen firstly from complete genome sequences (Tier 1), secondly from whole genome shotgun (WGS) data from genome projects (Tier 2), or thirdly from genomic nucleotide sequences from genome projects (Tier3). The list of selected accessions is transferred to Insignia when new pathogens are added to Gemina, allowing Insignia’s Signature Pipeline [3] to be run for each pathogen identified in a Gemina query.

APRS is an abbreviation for Automatic Packet Reporting System, and is a method of broadcasting GPS positioning information in real time from packet radio-equipped stations. It was designed in the early 90’s, but it has seen growth in the last few years due to user-friendly software such as WinAPRS or UI-View, and Kenwood’s APRS enabled radio transceivers becoming available. APRS equipped stations send latitude and longitude information, as well as course, speed and altitude of mobile stations. These are commonly set up for use as Search and Rescue operations or special public events such as parades for tactical overviews. Even the International Space Station and a number of low-earth orbiting satellites have an APRS repeater on board, with amateur earth stations watching positions on their PC screens. Many stations also transmit weather data, which is collected for use by the US Weather Service.