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DISCOVERY INFORMATICS IN BIOLOGICAL AND BIOMEDICAL SCIENCES: RESEARCH CHALLENGES AND OPPORTUNITIES

机译:生物和生物医学科学的发现信息学:研究挑战与机遇

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New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing,prioritizing,planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).
机译:我们在生物学,生物医学和健康科学中的新发现越来越多地受到我们获得,分享,集成和分析和构建和构建生物系统预测模型的能力的推动。虽然很多关注都侧重于自动化管理和分析“大数据”的常规方面,但实现“大数据”的全部潜力,以加速发现呼叫,以便自动化到目前为止抵制自动化的科学进程的许多其他方面:识别目前知识状态的差距;生成和优先考虑问题;设计研究;设计,优先考虑,规划和执行实验;解释结果;形成假设;得出结论;复制研究;验证索赔;记录研究;沟通结果;审查结果;并将结果整合到纪律的较大知识中。在此背景下,生物和生物医学科学中发现信息学的PSB研讨会探讨了通过进步(i)理解,正式化和信息处理账户,探讨了自动化发现或协助人类的机会和挑战; (ii)体现这种理解的计算伪影(表示,过程)的设计,开发和评估; (iii)将所产生的工件和系统应用于推进科学(通过增强个人或集体人力努力,或通过全自动化科学)。

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