PedExpert: a computer program for the application of Bayesian networks to human paternity testing.

PedExpert is a Windows-based Bayesian network software, especially constructed to solve problems in parentage testing that are complex because of missing genetic information on the alleged father and/or because they involve genetic mutations. PedExpert automates the creation and manipulation of Bayesian networks, implementing algorithms that convert pedigrees and sets of indispensable information (genotypes, allele frequencies, mutation rates) into Bayesian networks. This program has a novel feature that can incorporate information about gene mutations into tables of conditional probabilities of transmission of alleles from the alleged father to the child, without adding new nodes to the network. This permits using the same Bayesian network in different modes, for analysis of cases that include mutations or not. PedExpert is user-friendly and greatly reduces the time of analysis for complex cases of paternity testing, eliminating most sources of logical and operational error.

BNDb--Biomolecules Nucleus Database: an integrated proteomics and transcriptomics database.

Proteomics correspond to the identification and quantitative analysis of proteins expressed in different conditions or life stages of a cell or organism. Methods used in proteomics analysis include mainly chromatography, two-dimensional electrophoresis and mass spectrometry. Data generated in proteomics analysis vary significantly, and to identify a protein it is often necessary to perform a series of experiments, comparing its results to those found in proteomics databases. Existing proteomics databases are usually related to only one type of experiment or represent processed results, not raw data. Therefore, proteomics researchers frequently have to resort to several data repositories in order to be able to perform the identification. In this paper, we propose an integrated proteomics and transcriptomics database that stores raw and processed data, which are indexed allowing them to be retrieved together or individually. The proposed database, dubbed BNDb for Biomolecules Nucleus Database, is implemented using an MySQL server and is being used to store data from the parasite Schistosoma mansoni, the scorpion Tittyus serrulatus and the spider Phoneutria nigriventer. The database construction uses a relational approach and data indexes. The data model proposed uses groups of tables for each data subtype, which store details regarding the experimental procedure as well as raw data, analysis results and associated publications. BNDb also stores transcriptomics data publicly available which are associated with identifications performed on new samples. By using BNDb, we expect not only to contribute to proteomics research but also to provide a useful service for the scientific community.

BNDb - Biomolecules Nucleus Database: an integrated proteomics and transcriptomics database

Proteomics correspond to the identification and quantitative analysis of proteins expressed in different conditions or life stages of a cell or organism. Methods used in proteomics analysis include mainly chromatography, two-dimensional electrophoresis and mass spectrometry. Data generated in proteomics analysis vary significantly, and to identify a protein it is often necessary to perform a series of experiments, comparing its results to those found in proteomics databases. Existing proteomics databases are usually related to only one type of experiment or represent processed results, not raw data. Therefore, proteomics researchers frequently have to resort to several data repositories in order to be able to perform the identification. In this paper, we propose an integrated proteomics and transcriptomics database that stores raw and processed data, which are indexed allowing them to be retrieved together or individually. The proposed database, dubbed BNDb for Biomolecules Nucleus Database, is implemented using an MySQL server and is being used to store data from the parasite Schistosoma mansoni, the scorpion Tittyus serrulatus and the spider Phoneutria nigriventer. The database construction uses a relational approach and data indexes. The data model proposed uses groups of tables for each data subtype, which store details regarding the experimental procedure as well as raw data, analysis results and associated publications. BNDb also stores transcriptomics data publicly available which are associated with identifications performed on new samples. By using BNDb, we expect not only to contribute to proteomics research but also to provide a useful service for the scientific community.