Evidence for an AR(1) model for the Lake Michigan-Huron data. by Jesse Wheeler (18462457)

A structure determination protocol based on combined analysis of 3D-ED data, powder XRD data, solid-state NMR data and DFT-D calculations reveals the structure of a new polymorph o... by Christopher Smalley (19655662)

Patch-level landscape metrics derived using the <i>HabSpace</i> function of <i>HabplanR</i> for the entire 35 three-year projection period, across two possible Habplan solutions. by Max D. Jones (6269006)

Schematic showcasing main steps involved in the generation of a new daughter node <i>C</i>_<i>i</i> and subsequently a new branch <i>B</i>_<i>i</i>. by Diana C. de Oliveira (9220729)

Schematic representation of important placental morphological parameters. by Diana C. de Oliveira (9220729)

Infrared Spectroscopy Coupled with Machine Learning Algorithms to Investigate Vascular Dysfunction in Ovariectomy: An Animal Model Study by Tháfanys S. Travezani (20609398)

Swarm-averaged relative link counts <i>U</i>_<i>r</i> as a function of simulation tick-count <i>t</i> for the different transmission tactics. by Paul Kinsler (3975620)

An example of an aSNP affecting G4 formation. by Rongxin Zhang (1618159)

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

“…</p>Conclusion<p>This study establishes SRGs as independent prognostic indicators and defines SUMOylation-driven subtypes with distinct immune and molecular features. The SRS model and functional validation of L3MBTL2/VHL provide actionable insights for personalized STAD management and immunotherapy targeting. (214 words)</p>…”

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

“…</p>Conclusion<p>This study establishes SRGs as independent prognostic indicators and defines SUMOylation-driven subtypes with distinct immune and molecular features. The SRS model and functional validation of L3MBTL2/VHL provide actionable insights for personalized STAD management and immunotherapy targeting. (214 words)</p>…”

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

“…</p>Conclusion<p>This study establishes SRGs as independent prognostic indicators and defines SUMOylation-driven subtypes with distinct immune and molecular features. The SRS model and functional validation of L3MBTL2/VHL provide actionable insights for personalized STAD management and immunotherapy targeting. (214 words)</p>…”

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

“…</p>Conclusion<p>This study establishes SRGs as independent prognostic indicators and defines SUMOylation-driven subtypes with distinct immune and molecular features. The SRS model and functional validation of L3MBTL2/VHL provide actionable insights for personalized STAD management and immunotherapy targeting. (214 words)</p>…”

Optimal Subsampling for Functional Quasi-Mode Regression with Big Data by Tao Wang (12008)

“…The optimal subsampling probabilities by minimizing the asymptotic variance-covariance matrix under A- and L-optimality criteria are identified. These optimal probabilities rely on the full data estimate, prompting the development of a two-step algorithm to approximate the optimal subsampling procedure. …”

The KEGG pathways of all enzymes with high gains. by Heather L. Deel (20370535)

Construction of SEMWISE indicator ratings. by Heather L. Deel (20370535)

Screening process for marker genes from 7 DEGs and the diagnostic value of marker genes. by Kaiyi Zhou (2553352)

Identification, validation, and functional analyses of hub immune-related genes. by Chengjun Yu (12136227)

Prognostic Analysis of the Screened Mitophagy-Related Genes. by Jie Chu (293795)

The information of datasets used in this study. by Kaiyi Zhou (2553352)

“…Both machine learning algorithms identified Ribosomal Protein L22-like 1 (RPL22L1) and Lymphocyte Antigen 96 (LY96) as potential diagnostic markers for PsA and RA. …”

The workflow of the present study. by Kaiyi Zhou (2553352)

“…Both machine learning algorithms identified Ribosomal Protein L22-like 1 (RPL22L1) and Lymphocyte Antigen 96 (LY96) as potential diagnostic markers for PsA and RA. …”