Table_2_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

“…Furthermore, we identified genes co-associated with the key regulators previously reported as candidate genes (e.g., ANGPT1, CD4, CD36, DOCK1, PDE4B, PRKCE, PTPRC and SH2B3) for immunity traits in humans and pigs, but also new candidate ones (e.g., ACSL3, CXADR, HBB, MMP12, PTPN6, WLS) that were not previously described. …”

Free-Form Diffractive Metagrating Design Based on Generative Adversarial Networks by Jiaqi Jiang (5534351)

Bivariate Residual Plots With Simulation Polygons by Rafael A. Moral (7046630)

Data from "Minigene splicing assays identify 12 spliceogenic variants of BRCA2 exons 14 and 15" by Eladio Andrés Velasco (3369893)

“…<div>Sequencing, fragment analysis and quantification files from manuscript ""Minigene splicing assays identify 12 spliceogenic variants of BRCA2 exons 14 and 15"<br></div><div><b>Abstract</b><br></div><div>A relevant fraction of BRCA2 variants are associated with splicing alterations and with an increased risk of hereditary breast and ovarian cancer (HBOC). …”

Harnessing Natural Modularity of Metabolism with Goal Attainment Optimization to Design a Modular Chassis Cell for Production of Diverse Chemicals by Sergio Garcia (3423011)

Harnessing Natural Modularity of Metabolism with Goal Attainment Optimization to Design a Modular Chassis Cell for Production of Diverse Chemicals by Sergio Garcia (3423011)

ScanProsite motif hits. by Patrick W. Cervantes (18806249)

“…Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. …”

Search for acetylcholinesterase inhibitors by computerized screening of approved drug compounds by T.A. Materova (22770138)

What Electronic Structure Method Can Be Used in the Global Optimization of Nanoclusters? by Breno R. L. Galvão (7900016)

Table1_Construction of five cuproptosis-related lncRNA signature for predicting prognosis and immune activity in skin cutaneous melanoma.XLSX by Xiaojing Yang (154840)

“…We applied Univariate/multivariate and LASSO Cox regression algorithms, and finally identified 5 cuproptosis-related lncRNAs for constructing prognosis prediction models (VIM-AS1, AC012443.2, MALINC1, AL354696.2, HSD11B1-AS1). …”

Turkish_native_goat_genotypes by Yalçın YAMAN (20209833)

“…An ensemble feature-importance analysis, evaluated through 10,000 permutations, identified 31 FDR-significant SNPs representing markers consistently associated with MAP status. Functional annotation indicated involvement of immune-related processes such as cytokine–receptor signalling, antigen presentation, glycan-mediated T-cell regulation, and NF-κB–linked inflammatory pathways. …”

Image 3_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…Immune infiltration, pathway enrichment identified key SRGs, and in vitro functional assays were validated.</p>Results<p>Two molecular subtypes (A/B) with distinct SUMOylation patterns, survival outcomes (log-rank p < 0.001), and immune microenvironments were identified. …”

Image 1_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…Immune infiltration, pathway enrichment identified key SRGs, and in vitro functional assays were validated.</p>Results<p>Two molecular subtypes (A/B) with distinct SUMOylation patterns, survival outcomes (log-rank p < 0.001), and immune microenvironments were identified. …”

Image 2_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…Immune infiltration, pathway enrichment identified key SRGs, and in vitro functional assays were validated.</p>Results<p>Two molecular subtypes (A/B) with distinct SUMOylation patterns, survival outcomes (log-rank p < 0.001), and immune microenvironments were identified. …”

Image 4_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…Immune infiltration, pathway enrichment identified key SRGs, and in vitro functional assays were validated.</p>Results<p>Two molecular subtypes (A/B) with distinct SUMOylation patterns, survival outcomes (log-rank p < 0.001), and immune microenvironments were identified. …”

Image1_Construction of five cuproptosis-related lncRNA signature for predicting prognosis and immune activity in skin cutaneous melanoma.pdf by Xiaojing Yang (154840)

“…We applied Univariate/multivariate and LASSO Cox regression algorithms, and finally identified 5 cuproptosis-related lncRNAs for constructing prognosis prediction models (VIM-AS1, AC012443.2, MALINC1, AL354696.2, HSD11B1-AS1). …”

Image 1_Integrated bioinformatics and molecular docking analysis reveal potential hub genes and targeted therapeutics in sepsis-associated acute lung injury.jpeg by Qiongyan Chen (22406809)

“…Hub genes were screened using PPI network construction and three machine learning algorithms, and validated by Western blot. Functional enrichment, immune infiltration, and drug prediction (DSigDB) were performed, followed by molecular docking.…”

Identification of ferroptotic genes and phenotypes in idiopathic nonobstructive azoospermia by Chen Liao (1288563)

“…Here, we tried to identify the functional ferroptosis-related genes and phenotypes involved in iNOA. …”

Table 1_Integrated bioinformatics and molecular docking analysis reveal potential hub genes and targeted therapeutics in sepsis-associated acute lung injury.docx by Qiongyan Chen (22406809)

“…Hub genes were screened using PPI network construction and three machine learning algorithms, and validated by Western blot. Functional enrichment, immune infiltration, and drug prediction (DSigDB) were performed, followed by molecular docking.…”

Table 2_Integrated bioinformatics and molecular docking analysis reveal potential hub genes and targeted therapeutics in sepsis-associated acute lung injury.docx by Qiongyan Chen (22406809)

“…Hub genes were screened using PPI network construction and three machine learning algorithms, and validated by Western blot. Functional enrichment, immune infiltration, and drug prediction (DSigDB) were performed, followed by molecular docking.…”