The phrase "a multidimensional space to" is correct and usable in written English.
It can be used in contexts related to mathematics, physics, or abstract concepts where multiple dimensions are being discussed or utilized.
Example: "In our research, we aim to create a multidimensional space to analyze the interactions between various variables."
Alternatives: "a complex space to" or "a multi-faceted environment to".
Principal coordinate analyses transforms a complex multidimensional space to another orthogonal set of axes, such that the first principal coordinate reflects the largest portion of the structural variance in the data set, the second one the next largest, and so on.
Given the complexity of interpreting such a multidimensional matrix, PCA was applied to reduce this multidimensional space to a small number of principal components (PCs).
Here again, PCA reduced this multidimensional space to a small number of PCs.
We therefore use the position of known precursors in this multidimensional space to identify the region of interest and select the candidates populating it.
It proposed that molecular evolution of a gene occurs in a multidimensional space corresponding to the same canonical number of molecular phenotypes.
To further analyze the data, we employed PCA, which can reduce the dimensionality of the gene expression profiles and map individual cells in a multidimensional space according to their global gene expression patterns (see Section 2.3 for the explanation of PCA).
In conclusion, our manually curated decomposition of disease phenotypes is based on the set of elementary phenotypic features that serve as basis vectors in a multidimensional space, as opposed to previously reported automated (Lage et al., 2007; van Driel et al., 2006) or semi-automated (Robinson et al., 2008) ontologies of phenotypic terms.
Nearest neighbor (NN) queries ask for the point(s) in a multidimensional space that are closest to a given point.
Individual organisms are depicted as points in a multidimensional space and each axis corresponds to an independent phenotype under selection.
Cluster analysis reveals dissimilarities between cells by calculating the intercellular distance in a multidimensional space, where each dimension corresponds to one of the quantified cellular parameters.
