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In addition to accommodating cell lineage relations during development, our approach has the benefit that it works at single CpG dinucleotide resolution and does not require the spatial aggregation of methylation measurements across the genome.
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Our results lead us to suggest that with further development our modelling approach offers new opportunities for scenario-based predictions of response to environmental change and to assess anthropogenic impacts on water temperature.
Critically, although the experimental design of the previous studies did not allow a precise distinction between the contribution of cancer cell- and host-associated mPGES-1 to tumour development, our present approach clearly underscores the importance of mPGES-1 pools both in cancer cells (as discussed above) and in microenvironments (see below).
During the development of our approach, several observations were noticed.
The development of our approach was also inspired by other ranking-based approaches, such as Ranking SVM [25], RankBoost [26], and RankNet [27].
Remark 2.1 We remark that for the subsequent development of our approach, it suffices to assume that A is a closed and convex set of admissible parameters.
The conduct of the AGPNS and development of our approach, like any field-based method, can be derailed by major events.
We would like to acknowledge the feedback from members of our independent scientific advisory panel, government staff with knowledge of existing useful databases, and other interested stakeholders during the development of our approach and subsequent implementation over the past three years.
The technical development of our approach based on the formalism of field-theory and its application to molecular signal transduction is the main subject of a forthcoming manuscript [ 16].
Many developments of our approach are envisaged to provide more complete estimates of the public health impact of treatment strategies.
It would be desirable in future developments of our approach to include separate estimates for relevant outcomes, which underlines the need for high-quality data to build up suitable risk equations.
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