Image_2_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.TIF by Iulian Gabur (11720927)

“…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”

Table_1_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.XLSX by Iulian Gabur (11720927)

“…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”

Table_3_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.xlsx by Iulian Gabur (11720927)

“…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”

Table_4_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.xlsx by Iulian Gabur (11720927)

“…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”

Occurrence of brushing movements on the buccal surfaces in the study quadrant. by Nadine Schlueter (755050)

Assessment values of machine learning models. by Bin Pan (742525)

“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”

List of datasets in AqSolDB. by Bin Pan (742525)

“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”

Feature importance derived from SHAP analysis. by Bin Pan (742525)

“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”

<i>P</i>. <i>yoelii</i> infection increases plasma cell apoptosis, decreases plasma cell BAFF-R and increases circulating BAFF concentrations. by Simran Banga (227952)

Photographs of MTS testing setup. by Brian E. Walczak (11377108)

Gene expression analysis of T3-regulated genes in the cerebral cortex of vehicle treated Wt (<i>Hr</i> n = 4; <i>Cbr2</i> n = 4; <i>Flywch2</i> n = 3; <i>Dio3</i> n = 4; <i>Abcd2</... by Soledad Bárez-López (607514)

Significant repeated measurements sEMG outcomes. by María Benito-de-Pedro (22057468)

“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”

Maximum voluntary contraction assessment. by María Benito-de-Pedro (22057468)

“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”

Significant single measurement sEMG outcomes. by María Benito-de-Pedro (22057468)

“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”

LF-induced lipolysis in LRP1-silenced adipocytes. by Keiko Ikoma-Seki (818838)

Starvation improves locomotory capacity and decreases the number of α-synuclein-YFP aggregates of transgenic <i>C. elegans</i> through LMP-1 dependent mechanism. by María Gallardo-Campos (22170919)

Scoring schemes for the assessment of skin and keel bone status in laying hens¹ [29]. by Lisa Jung (13264758)

Principle of planimetric analysis. by Nadine Schlueter (755050)

Comparison of meniscus extrusion between the medial and lateral meniscus under constant axial compression load. by Brian E. Walczak (11377108)

ITYPs (A) and TYTE (B) in fungal treatment experiment 2. by Bowen Zhang (595078)