GRADE has an explicit methodology that relies on input from scientific evidence as well as a panel of experts.
It is characterized by the systematic and transparent access to, and appraisal of, evidence as an input into the policymaking process [ 3, 6].
These different pieces of information are fused together by the DS evidence theory using as input features, the mass functions of each information extracted from the input image expressed in different color spaces, previously estimated and associated to each pixel.
Our study revealed that evidence was used as input to decision-making for technical experts, conceptualizing the situation for government policymakers, implementing partners and CSOs, and persuading actors to buy in for certain policies, all of which was achieved by CSO lobbying.
We used these binarized microarray data sets as input evidence in mCADRE to extract individual models from the generic Recon 1, thereby establishing a Tissue-Specific Encyclopedia of Metabolism (TSEM).
This new method uses gene expression microarray data as input evidence to prune a generic model (e.g., Human Recon 1) to a context-specific subset; the SBML file for Recon 1 was obtained from the BiGG database [ 56] and converted into COBRA Toolbox [ 57] model structure for subsequent analysis.
For each marker, an arbitrary reference allele is selected and a Z-statistic, characterizing the evidence for association, is used as input.
As the results of interim assessments can be meaningfully aggregated and reported at a broader level they could serve as input for evidence- based education that could be useful for scientific elaboration.
INIT primarily uses the evidence from the Human Protein Atlas (HPA) as input, but can also incorporate gene expression and metabolomics data; algorithm parameters (e.g., weights assigned to different level of evidence) are also optimized for HPA data [ 44]. mCADRE can use any data that can quantitatively measure mRNA or protein abundance, but herein primarily uses gene expression microarray data.
As much as it seeks to open up the policy process by advancing evidence as a tailored or demanded input, KT also seeks to reform the research process – principally by trying to align research topics with policy needs (as opposed to, for instance, the needs or desires of funders).
