RASP performance across different scales in the Mouse Sagittal brain dataset. by Ian K. Gingerich (22822222)

Lattice diagrams for a sequence of complexes that carry one autocatalytic <i>A</i>_<i>n</i> backbone through the sequence of its conversions in one full turn of the CBB c... by Eric Smith (75971)

PhAMEs group into clusters of structurally related proteins. by Federico G. Mirkin (22615287)

Spatial domain analysis of human breast cancer tissue using 10x Xenium data. by Ian K. Gingerich (22822222)

Human dorsolateral prefrontal cortex (DLPFC) spatial transcriptomics analysis, 10X Visium data. by Ian K. Gingerich (22822222)

Covariate analysis (Mouse ovary dataset) for the cell type clustering case. by Ian K. Gingerich (22822222)

S1 Graphical abstract - by José M. Rivera-Arbeláez (12418512)

“…<div><p>Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart <i>in vitro</i>. …”

PPI network and identification of hub genes. by Jun Li (6494)

Alpha networks. by Ying Joey Zhou (22479044)

Schematic of our autoencoder-based feature extraction framework. by Zahra Rostami (20472226)

“…<p>a) We collect data and categorize it into the four subtypes of breast cancer, namely TNBC, HER2-enriched, luminal A, and luminal B. The gene expression data for each subtype is passed to the autoencoder one at a time. b) For each subtype, we perform autoencoder-based feature inference and select the top 3000 genes that have the highest feature scores according to our algorithm. c) For each subtype, we run the autoencoder 30 times with a fixed seed and find the overlap of the resulting gene sets (each containing 3000 genes). …”

3D analysis of the perforated pebbles and the perforations. by Talia Yashuv (12883867)

Key Genes Screening and LASSO Risk Model Construction. by Jianguo Ma (2119684)

Citation distribution and allometric relations for the bibliographic coupling network. by Carlos G.O. Fernandes (21417304)

“…<p><b>(a)</b> Citation distribution, for courts. <b>(b)</b> Cases (size) as function of citations (mass), for courts. …”

Study flowchart. by Jingqi Dong (22378904)

“…Differential expression gene (DEG) analysis was performed on the profiles, followed by further screening using four machine learning algorithms. Concurrently, weighted gene co-expression network analysis (WGCNA) was applied to identify gene modules, and enrichment analysis of WGCNA-derived genes was conducted to explore their biological functions. …”

The top ten related predicted drug compounds. by Jingqi Dong (22378904)

“…Differential expression gene (DEG) analysis was performed on the profiles, followed by further screening using four machine learning algorithms. Concurrently, weighted gene co-expression network analysis (WGCNA) was applied to identify gene modules, and enrichment analysis of WGCNA-derived genes was conducted to explore their biological functions. …”

Self-similarity analysis for the MSTs of coupling network communities. by Carlos G.O. Fernandes (21417304)

“…<p><b>(a)</b> Log-log plot of the number of boxes (<i>N</i>_<i>B</i>) as a function of the size of the boxes (<i>l</i>_<i>B</i>) obtained from the CBB algorithm. …”

Analysis of PPI network and hub genes. by Yubin Xue (1537042)

Structure of optimized model parameters in the high-dimensional cases. by Kevin J. Wischnewski (21354521)

Distributions of the goodness-of-fit (GoF) values for all tested approaches and parameter spaces. by Kevin J. Wischnewski (21354521)

Example of the results of the model fitting in the 103-dimensional parameter space. by Kevin J. Wischnewski (21354521)