PubMed · 11964464
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John H Reif. 2002-04-19. Computing. Successes and challenges.. https://doi.org/10.1126/science.1070978
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OBJECTIVE: The objective of the study is to validate self-reported cellular phone use information by comparing it with the cumulative emitted power and duration of calls measured by software-modified cellular phones (SMP). The information was obtained using a questionnaire developed for the international case-control study on the risk of the use of mobile phones in tumours of the brain or salivary gland (INTERPHONE-study). METHOD: The study was conducted in Bielefeld, Germany. Volunteers were asked to use SMPs instead of their own cellular phones for a period of 1 month. The SMP recorded the power emitted by the mobile phone handset during each base station contact. Information on cellular phone use for the same time period from traffic records of the network providers and from face-to-face interviews with the participants 3 months after the SMP use was assessed. Pearson's correlation coefficients and linear regression models were used to analyse the association between information from the interview and from the SMP. RESULTS: In total, 1757 personal mobile phone calls were recorded for 45 persons by SMP and traffic records. The correlation between the self-reported information about the number and the duration of calls with the cumulative power of calls was 0.50 (P<0.01) and 0.48 (P<0.01), respectively. Almost 23% of the variance of the cumulative power was explained by either the number or the cumulative duration of calls. After inclusion of possible confounding factors in the regression model, the variance increased to 26%. Minor confounding factors were "network provider", "contract form", and "cellular phone model". DISCUSSION: The number of calls alone is a sufficient parameter to estimate the cumulative power emitted by the handset of a cellular telephone. The cumulative power emitted by these phones is only associated with number of calls but not with possible confounding factors. Using the mobile phone while driving, mainly in cities, or mainly in rural areas is not associated with the recorded cumulative power in the SMP.
We have developed a new scoring function, the template modeling score (TM-score), to assess the quality of protein structure templates and predicted full-length models by extending the approaches used in Global Distance Test (GDT)1 and MaxSub.2 First, a protein size-dependent scale is exploited to eliminate the inherent protein size dependence of the previous scores and appropriately account for random protein structure pairs. Second, rather than setting specific distance cutoffs and calculating only the fractions with errors below the cutoff, all residue pairs in alignment/modeling are evaluated in the proposed score. For comparison of various scoring functions, we have constructed a large-scale benchmark set of structure templates for 1489 small to medium size proteins using the threading program PROSPECTOR_3 and built the full-length models using MODELLER and TASSER. The TM-score of the initial threading alignments, compared to the GDT and MaxSub scoring functions, shows a much stronger correlation to the quality of the final full-length models. The TM-score is further exploited as an assessment of all 'new fold' targets in the recent CASP5 experiment and shows a close coincidence with the results of human-expert visual assessment. These data suggest that the TM-score is a useful complement to the fully automated assessment of protein structure predictions. The executable program of TM-score is freely downloadable at http://bioinformatics.buffalo.edu/TM-score.
Trends in increased tuberculosis infection and a fatality rate of approximately 23% have necessitated the search for alternative biomarkers using newly developed postgenomic approaches. Here we provide a systematic analysis of Mycobacterium tuberculosis (Mtb) by directly profiling its gene products. This analysis combines high-throughput proteomics and computational approaches to elucidate the globally expressed complements of the three subcellular compartments (the cell wall, membrane, and cytosol) of Mtb. We report the identifications of 1044 proteins and their corresponding localizations in these compartments. Genome-based computational and metabolic pathways analyses were performed and integrated with proteomics data to reconstruct response networks. From the reconstructed response networks for fatty acid degradation and lipid biosynthesis pathways in Mtb, we identified proteins whose involvements in these pathways were not previously suspected. Furthermore, the subcellular localizations of these expressed proteins provide interesting insights into the compartmentalization of these pathways, which appear to traverse from cell wall to cytoplasm. Results of this large-scale subcellular proteome profile of Mtb have confirmed and validated the computational network hypothesis that functionally related proteins work together in larger organizational structures.