Image 1_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.tif by Jian Wang (5901)

“…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …”

Table 2_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx by Jian Wang (5901)

“…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …”

Table 1_Phosphate transporter gene families in rye (Secale cereale L.) – genome-wide identification, characterization and sequence diversity assessment via DArTreseq.xlsx by David Chan-Rodriguez (4865152)

“…Based on DArTreseq genotyping of 94 diverse rye accessions we identified 820 polymorphic sites within rye ScPht, including 12 variants identified by the SIFT algorithm as having a potentially deleterious effect, of which three are scored as high confidence. …”

Data Sheet 1_Phosphate transporter gene families in rye (Secale cereale L.) – genome-wide identification, characterization and sequence diversity assessment via DArTreseq.docx by David Chan-Rodriguez (4865152)

“…Based on DArTreseq genotyping of 94 diverse rye accessions we identified 820 polymorphic sites within rye ScPht, including 12 variants identified by the SIFT algorithm as having a potentially deleterious effect, of which three are scored as high confidence. …”

Relational network prepared by the authoring team. by Lesedi Mamodise Modise (20826978)

“…Additionally, team members are interconnected with color-coded bands that denote functional clusters within the group. <i>Figure representing relationships among team members found at:</i> <a href="https://www.teamcard.io/team/demo" target="_blank">https://www.teamcard.io/team/demo</a>. …”

A Smoothed-Bayesian Approach to Frequency Recovery from Sketched Data by Mario Beraha (11669142)

“…For sketches obtained with a single hash function, our approach is supported by precise theoretical guarantees, including unbiasedness and optimality under a Bayesian framework within an intuitive class of linear estimators. …”

k-means based load estimation of domestic smart meter measurements by Meng Cheng (19655023)

“…The developed algorithm applies cluster centres - of previously clustered load profiles - and distance functions to estimate missing and future measurements. …”

Assessing the risk of acute kidney injury associated with a four-drug regimen for heart failure: a ten-year real-world pharmacovigilance analysis based on FAERS events by Sen Lin (182597)

“…Disproportionality analysis and subgroup analysis were performed using four algorithms. Time-to-onset (TTO) analysis was used to assess the temporal risk patterns of ADE occurrence. …”

Image 3_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 5_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 8_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Table 1_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.docx by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 2_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 6_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 7_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 4_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Image 1_Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma.jpeg by Beichen Cai (16842684)

“…Single-cell RNA sequencing (scRNA-seq) was leveraged to investigate the cellular heterogeneity within the SKCM tumor microenvironment, and macrophage populations were categorized using the Monocle2 algorithm. …”

Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

“…The functions were tested respectively in: MATLAB 2018a or youger, Python 3.9.4, R 4.0.3.…”

Data Sheet 2_Integrated analysis of single-cell RNA-seq and spatial transcriptomics to identify the lactylation-related protein TUBB2A as a potential biomarker for glioblastoma in... by Yifan Xu (87249)

“…</p>Methods<p>We employed functional enrichment algorithms, including AUCell and UCell, to assess lactylation activity in GBM cancer cells. …”

Data Sheet 9_Integrated analysis of single-cell RNA-seq and spatial transcriptomics to identify the lactylation-related protein TUBB2A as a potential biomarker for glioblastoma in... by Yifan Xu (87249)

“…</p>Methods<p>We employed functional enrichment algorithms, including AUCell and UCell, to assess lactylation activity in GBM cancer cells. …”