Sentence examples for built using only the from inspiring English sources

A first 3D model is built using only the geological information coming from geological maps, drill-holes, and seismic sections.

Figure 12 was built using only the rotation velocity sensor data, so that the phase 1 Kefalonia soft-soil dataset can be represented and compared with the two other phases.

This is a model of a DNA duplex tetramer, built using only the bases CGCG or ATAT in this example, with inclusion of three phosphate groups and calculated for both the left- and right-handed helical form.

The new emulator was built using only the 8 sensitive inputs with the remaining inputs fixed at their default values.

One was built using only the MolConnZ chemical descriptor set (340 variables), and the other was built using the combined chemico-biological descriptor set (347 variables).

A phylogenetic tree was built using only the GTPase domain with the programs PROTDIST (JTT distances), NEIGHBOR and CONSENSE from the PHYLIP package [ 23].

In fact, a linear model built using only this factor has the opposite sign, indicating that this coefficient is the result of the correlation with other factors.

An ML tree built using only translations of the most conserved pseudogenes showed weakly supported but consistent association of the human pseudogenes with HSPD1 from primates, whereas pseudogenes from mouse and rat all associated with murid Hspd1 sequences, also indicating their relatively recent origin.

A model of lung cancer vs. control built using only subjects from the largest available clinical subgroup (30 subjects) had a C-statistic of 0.970.

To investigate whether the location of each clone on a plate affects the fluorescence levels of cells, models built using only three sets of the STO-RW4 control wells were used to predict the cell types of cells in the set of control wells that were not included in the models.

All the networks were built using only one hidden layer while the ideal number of hidden neurons was determined by training, cross validating and testing a MLP, increasing unitarily the number of neurons beginning with 4 and stopping when the MSE between the predictions and the desired output in the testing subgroup began to increase.