Sentence examples for mouse tractography datasets from inspiring English sources

High-quality mouse tractography datasets, like those presented here, will be essential for understanding the neural basis of tractography, through direct comparisons with more specific, invasive connectivity methods like neuronal tracer studies and electrophysiology.

Connectivity estimates were generated for all 296 seed region tractography datasets and all 296 anatomic regions.

Colocalization analysis for both tractography datasets (i.e., 488 comparisons × 2) revealed weak but significant correlation between neuronal tracer data and probabilistic tractography (Fig. 5 A, B).

Probabilistic tractography maps were individually generated for the left and right halves of each of the 148 anatomic labels (i.e., 296 total tractography datasets per specimen).

For a given seed region A, the corresponding tractography dataset represents all connections from region A to the rest of the brain.

Based on our results, we then compared pig and mouse in vivo datasets with human PED datasets.

Finally we obtained 14036 and 13134 human and mouse gene datasets with AP annotations, respectively.

Table 2 describes the datasets used, which include 12 human cancer datasets, five mouse cancer datasets, one rat cancer dataset, and one dataset from zebrafish.

The Yeast dataset includes 44 functional association networks, the Human dataset includes 8 networks, the Mouse dataset consists of 10 networks, and the Fly dataset has 38 networks.

The human and mouse datasets were normalized using the Robust Multichip Average (RMA) algorithm.

Note p-values in Figure 4 are not directly comparable between Drosophila and mouse datasets.