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Equation 5 · Part 2 · Comparing the Main Approaches to AI for Science and Medicine

Symbol i

RMSD=1N∑i=1N∥xi−x^i∥2\text{RMSD} = \sqrt{\frac{1}{N} \sum_{i=1}^{N} \lVert x_i - \hat{x}_i \rVert^2}
ii

What this part means

i appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

Its job in the formula

i appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

The passage around this formula

…What that root-mean-square-deviation figure actually measures is worth stating explicitly, because the number is often quoted without the definition it depends on: RMSD=1N∑i=1N∥xi−x^i∥2\text{RMSD} = \sqrt{\frac{1}{N} \sum_{i=1}^{N} \lVert x_i - \hat{x}_i \rVert^2}. where xix_i is the coordinate of atom i in the experimentally solved structure, x^i\hat{x}_i is the corresponding coordinate in the predicted structure after optimal superposition of the two, and N is the number of atoms compared. This is a statement about the average positional deviation of one predicted, static conformation from one…

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A variable is a named place for a value. Its letter is a local label: x can mean position in one formula and a data point in another.

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