Use of handheld computers with global positioning systems for probability sampling and data entry in household surveys.

We introduce an innovative method that uses personal digital assistants (PDAs) equipped with global positioning system (GPS) units in household surveys to select a probability-based sample and perform PDA-based interviews. Our approach uses PDAs with GPS to rapidly map all households in selected areas, choose a random sample, and navigate back to the sampled households to conduct an interview. We present recent field experience in two large-scale nationally representative household surveys to assess insecticide-treated bed net coverage as part of malaria control efforts in Africa. The successful application of this method resulted in statistically valid samples; quality-controlled data entry; and rapid aggregation, analyses, and availability of preliminary results within days of completing the field work. We propose this method as an alternative to the Expanded Program on Immunization cluster sample method when a fast, statistically valid survey is required in an environment with little census information at the enumeration area level.

Application of pre-programmed PDA devices equipped with global GPS to conduct paperless household surveys in rural Mozambique.

Personal digital assistants (PDAs) are extending how we use software normally associated with desktop and laptop computers. As interface design improves and specialized software becomes available, health professionals are choosing to usePDAs. A logical next step to use PDAs is in remote areas where electronic data collection is needed and electricity is limited. A test of PDAs', equipped with global positioning system, ability to improve household surveys in rural Mozambique was completed in February 2006.

rSNP_Guide, a database system for analysis of transcription factor binding to DNA with variations: application to genome annotation.

The analysis of gene regulatory networks has become one of the most challenging problems of the postgenomic era. Earlier we developed rSNP_Guide (http://util.bionet.nsc.ru/databases/rsnp.html), a computer system and database devoted to prediction of transcription factor (TF) binding sites (TF sites), which can be responsible for disease phenotypes. The prediction results were confirmed by 70 known relationships between TF sites and diseases, as well as by site-directed mutagenesis data. The rSNP_Guide is being investigated as a tool for TF site annotation. Previously analyzed and characterized cases of altered TF sites were used to annotate potential sites of the same type and at the same location in homologous genes. Based on 20 TF sites with known alterations in TF binding to DNA, we localized 245 potential TF sites in homologous genes. For these potential TF sites, rSNP_Guide estimates TF-DNA interaction according to three categories: 'present', 'weak', and 'absent'. The significance of each assignment is statistically measured.

rSNP_Guide: an integrated database-tools system for studying SNPs and site-directed mutations in transcription factor binding sites.

Since the human genome was sequenced in draft, single nucleotide polymorphism (SNP) analysis has become one of the keynote fields of bioinformatics. We have developed an integrated database-tools system, rSNP_Guide (http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/), devoted to prediction of transcription factor (TF) binding sites, alterations of which could be associated with disease phenotype. By inputting data on alterations in DNA sequence and in DNA binding pattern of an unknown TF, rSNP_Guide searches for a known TF with alterations in the recognition score calculated on the basis of TF site's sequence and consistent with the input alterations in DNA binding to the unknown TF. Our system has been tested on many relationships between known TF sites and diseases, as well as on site-directed mutagenesis data. Experimental verification of rSNP_Guide system was made on functionally important SNPs in human TDO2and mouse K-ras genes. Additional examples of analysis are reported involving variants in the human gammaA-globin (HBG1), hsp70(HSPA1A), and Factor IX (F9) gene promoters.

SELEX_DB: a database on in vitro selected oligomers adapted for recognizing natural sites and for analyzing both SNPs and site-directed mutagenesis data.

SELEX_DB is an online resource containing both the experimental data on in vitro selected DNA/RNA oligomers (aptamers) and the applets for recognition of these oligomers. Since in vitro experimental data are evidently system-dependent, the new release of the SELEX_DB has been supplemented by the database SYSTEM storing the experimental design. In addition, the recognition applet package, SELEX_TOOLS, applying in vitro selected data to annotation of the genome DNA, is accompanied by the cross-validation test database CROSS_TEST discriminating the sites (natural or other) related to in vitro selected sites out of random DNA. By cross-validation testing, we have unexpectedly observed that the recognition accuracy increases with the growth of homology between the training and test sets of protein binding sequences. For natural sites, the recognition accuracy was lower than that for the nearest protein homologs and higher than that for distant homologs and non-homologous proteins binding the common site. The current SELEX_DB release is available at http://wwwmgs.bionet.nsc.ru/mgs/systems/selex/.