2 resultados para Computer Science(all)

em DigitalCommons@The Texas Medical Center


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Physical activity has been, and remains, a significant public health issue. Thus, increasing physical activity has been identified as a top priority according to Healthy People 2010. Various behavioral variables have been associated with participation in physical activity, including the Type A behavior pattern (TABP). This study was a secondary data analysis of the Women On The Move pilot study data and examined the relationship between Type A behavior with physical activity. The study population consisted of fifty-six (56) adult minority women 40 years of age and above. The Thurstone Activity Scale was adapted for use in this study to measure TABP. Physical activity behavior was measured using an accelerometer (Computer Science Application, [CSA]) and a physical activity diary. All study questions were examined using multiple linear regression analysis. In all analyses age, household income, and level of education were entered as covariates. The results found no association with TABP and exercise or physical activity. More research involving a larger, more active study population is recommended in order to more precisely determine the relationship of TABP and physical activity. ^

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Historically morphological features were used as the primary means to classify organisms. However, the age of molecular genetics has allowed us to approach this field from the perspective of the organism's genetic code. Early work used highly conserved sequences, such as ribosomal RNA. The increasing number of complete genomes in the public data repositories provides the opportunity to look not only at a single gene, but at organisms' entire parts list. ^ Here the Sequence Comparison Index (SCI) and the Organism Comparison Index (OCI), algorithms and methods to compare proteins and proteomes, are presented. The complete proteomes of 104 sequenced organisms were compared. Over 280 million full Smith-Waterman alignments were performed on sequence pairs which had a reasonable expectation of being related. From these alignments a whole proteome phylogenetic tree was constructed. This method was also used to compare the small subunit (SSU) rRNA from each organism and a tree constructed from these results. The SSU rRNA tree by the SCI/OCI method looks very much like accepted SSU rRNA trees from sources such as the Ribosomal Database Project, thus validating the method. The SCI/OCI proteome tree showed a number of small but significant differences when compared to the SSU rRNA tree and proteome trees constructed by other methods. Horizontal gene transfer does not appear to affect the SCI/OCI trees until the transferred genes make up a large portion of the proteome. ^ As part of this work, the Database of Related Local Alignments (DaRLA) was created and contains over 81 million rows of sequence alignment information. DaRLA, while primarily used to build the whole proteome trees, can also be applied shared gene content analysis, gene order analysis, and creating individual protein trees. ^ Finally, the standard BLAST method for analyzing shared gene content was compared to the SCI method using 4 spirochetes. The SCI system performed flawlessly, finding all proteins from one organism against itself and finding all the ribosomal proteins between organisms. The BLAST system missed some proteins from its respective organism and failed to detect small ribosomal proteins between organisms. ^