Table3_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.xlsx by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

Table1_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.xlsx by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

DataSheet2_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.PDF by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

DataSheet1_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.PDF by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

DataSheet3_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.PDF by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

Table2_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.XLSX by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

Image1_Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.JPEG by Roberto Martin-Hernandez (3661549)

“…</p><p>Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. …”

Cell content predictions derived from microarray data match known relationships between subject variables and brain tissue cell content. by Megan Hastings Hagenauer (5523191)

“…</b> Age was associated with a decrease in the neuronal indices (p = 0.000956) which fits known decreases in gray matter density in the frontal cortex in aging humans [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0200003#pone.0200003.ref047" target="_blank">47</a>]. …”

Dual-Mode Ultrasensitive Quantification of MicroRNA in Living Cells by Chiroplasmonic Nanopyramids Self-Assembled from Gold and Upconversion Nanoparticles by Si Li (375535)

“…The experimental results show that the CD intensity had an outstanding linear range from 0.073 to 43.65 fmol/10 μg_RNA and a limit of detection (LOD) of 0.03 fmol/10 μg_RNA, whereas the luminescence intensity ranged from 0.16 to 43.65 fmol/10 μg_RNA with a LOD of 0.12 fmol/10 μg_RNA. …”

Contractile and Mechanical Properties of Epithelia with Perturbed Actomyosin Dynamics by Sabine C. Fischer (554860)

“…Conversely, an increase in Myosin phosphorylation and an increase in actin linear polymerization induce a solidification of cells. …”

DataSheet_4_Overfishing Increases the Carbon Footprint of Seafood Production From Small-Scale Fisheries.pdf by Erica M. Ferrer (12455388)

“…We find an inverse relationship between B/B_MSY and fuel intensity using a test for simple correlation between the two (r= -0.44), a linear regression analysis (R²<sub>adj.…”

DataSheet_3_Overfishing Increases the Carbon Footprint of Seafood Production From Small-Scale Fisheries.csv by Erica M. Ferrer (12455388)

“…We find an inverse relationship between B/B_MSY and fuel intensity using a test for simple correlation between the two (r= -0.44), a linear regression analysis (R²<sub>adj.…”

DataSheet_1_Overfishing Increases the Carbon Footprint of Seafood Production From Small-Scale Fisheries.csv by Erica M. Ferrer (12455388)

“…We find an inverse relationship between B/B_MSY and fuel intensity using a test for simple correlation between the two (r= -0.44), a linear regression analysis (R²<sub>adj.…”

Influence of the Extraction Location on the Physical and Mechanical Properties of the Pseudo-Trunk Banana Fibers by Laurent Libog (15348295)

“…Due to diameter scatter, variations of 42% were found for fibers in the same area. In a region, the physical properties increase from the periphery to the core, and the mechanical properties decrease in the same direction, except for elongation. …”

Interrupting wave progression resets rhythm generation in abdominal model incorporating wave detectors and initiation detectors. by Jacob Francis (5027897)

“…<p>Inhibiting exciters (E_F or E_B) blocks forwards and backwards wave propagation across segments in a stepwise fashion, thereby effectively reducing the number of intact segments. …”

Presentation: Deep-pass — An aeromagnetic data filter to enhance deep features in marginal basins by Darcicléa F. Santos (387574)

“…This amplification compensates for the magnetic response attenuation over the continental slope as a result of (1) the seaward increase of the distance between the source and the magnetometer and (2) the seaward decrease in the volume of sources within the continental crust. …”

DataSheet1_ECG based assessment of circadian variation in AV-nodal conduction during AF—Influence of rate control drugs.PDF by Mattias Karlsson (2674390)

“…Based on the estimated model parameters, the circadian variation and its drug-dependent difference between treatment with two β-blockers and two calcium channel blockers were quantified on a population level by means of cosinor analysis using a linear mixed-effect approach. …”

Data for paper: Women's voice pitch lowers after pregnancy, Evolution and Human Behavior by Kasia Pisanski (4467112)

“…These F0 parameters did not decrease within-individuals over a 5-year period prior to conception above and beyond the effects of ageing. …”

Yield and nutritional efficiency of corn in response to rates and splits of nitrogen fertilization by Telmo Jorge Carneiro Amado (4655344)

“…The results showed the occurrence of a linear relationship between nitrogen fertilizer dose and NDVI at V8 as well as at V12 stages. …”

Influence of different types of silver nanoparticles on the biodegradation of the organic fraction of municipal solid waste by Isabela da Cruz Bonatto (8182911)

“…Finally, the statistical studies and the mathematical modeling of the results showed that the logistic model adjusted well to the experimental data. The linear regression of the model parameters with the concentration of AgNPs demonstrates the decrease in the values of the parameters with the increase in the concentration of these compounds.…”