In this study we identify suitable reconstruction methods, types of experiments and requirements on data size and quality in order to reverse engineer gene regulatory networks from time series data.
Based on our analyses of current availability and future requirements of data, we make clear recommendations for forthcoming research.
In conclusion, the architecture provides a holistic view of the aspects and requirements of a big data technology application system for purposes of asset management.
This chapter is structured to showcase the challenges and requirements of a big data processing infrastructure and also gives an overview of the core technologies and considerations involved in the concept of big data processing.
We first formally define a consistency model, which not only includes temporal consistency and numerical consistency, but also considers the application-specific requirements of data and data dynamics in the sensing field.
It eliminates the requirements of data distribution and load balancing by using MapReduce paradigm.
Consequently, the data would need to be exported and manually manipulated in a spreadsheet program, bearing the risk of not being in accordance with the requirements of data safety and data integrity [6].
Study investigators respected the requirements of data protection and medical professional secrecy.
Some gaps were identified between available experimental data and requirements of the system design and operation.
Choose prediction method, starting from the characteristics of forecasting object, according to the purpose and requirements of forecast, which holds the data situation and predicts the comparison of cost and benefit factors synthetically considered.
