4 resultados para Computing Classification Systems
em University of Queensland eSpace - Australia
Resumo:
Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.
Resumo:
Patients who have no residual invasive cancer following neoadjuvant chemotherapy for breast carcinoma have a better overall survival than those with residual disease. Many classification systems assessing pathological response to neoadjuvant chemotherapy include residual ductal carcinoma in situ (DCIS) only in the definition of pathological complete response. The purpose of this study was to investigate whether patients with residual DCIS only have the same prognosis as those with no residual invasive or in situ disease. A retrospective analysis of a prospectively maintained database identified 435 patients, who received neoadjuvant chemotherapy for operable breast cancer between February 1985 and February 2003. Of these, 30 (7%; 95% CI 5-9%) had no residual invasive disease or DCIS and 20 (5%; CI 3-7%) had residual DCIS only. With a median follow-up of 61 months, there was no statistical difference in disease-free survival, 80% (95% CI 60-90%) in those with no residual invasive or in situ disease and 61% (95% CI 35-80%) in those with DCIS only (P = 0.4). No significant difference in 5-year overall survival was observed, 93% (95% CI 75-98%) in those with no residual invasive or in situ disease and 82% (95% CI 52-94%) in those with DCIS only (P = 0.3). Due to the small number of patients and limited number of events in each group, it is not possible to draw definitive conclusions from this study. Further analyses of other databases are required to confirm our finding of no difference in disease-free and overall survival between patients with residual DCIS and those with no invasive or in situ disease following neoadjuvant chemotherapy for breast cancer.