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In this article, we introduce a new modeling methodology called disciplined convex programming.
Candidate mechanisms were identified via analysis of gene expression profiling data and phosphoproteomic data using a causal network modeling methodology called "Reverse Causal Analysis" (RCA) [ 16, 17].
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A methodology called PRISMA was developed to trace prevention options.
Instead we use a methodology called "Jobs to Done".
In this work a methodology called EVAL is presented.
The design procedure follows a methodology called design space approach.
To ensure that scores are fair, test administrators employ a statistical methodology called equating.
Based on these assumptions, we introduce a knowledge strategy planning methodology, called P2-KSP methodology.
Why is this methodology called Symbergetic?
It is imperative to advance modeling methodology and enrich model repertoire in order to capture or uncover, differentiate and recognize various network phenomenons and propagation patterns.
However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used.
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