Table 1_Integrated multi-omics analysis and machine learning identify G protein-coupled receptor-related signatures for diagnosis and clinical benefits in soft tissue sarcoma.xlsx by Duo Wang (1787634)

“…Moreover, the GPR-TME classifier as the prognosis model was constructed and further performed for immune infiltration, functional enrichment, somatic mutation, immunotherapy response prediction, and scRNA-seq analyses.…”

Polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

“…The Perdew-Burke-Ernzerhof (PBE) functional with Hubbard-U corrections were applied was utilized for all calculations. …”

Behavioral raw data recorded by HABITS autonomously by bowen yu (19822908)

“…Supported by the microcontroller-based general programming framework, we have not only replicated established paradigms in current neuroscience research but also developed several novel paradigms previously unexplored in mice, resulting in more than 300 mice tested in various cognition functions. …”

Estilometría TIP: enhanced text analysis tool with customisable metrics for Spanish texts by Francisco J. Carreras-Riudavets (20562834)

“…Lexicon TIP draws on a comprehensive database of more than 320,000 lemmas and 8 million inflected forms, accounting for variations in number, gender, superlatives, diminutives, augmentatives, derogatory terms, and verb conjugations. Two key algorithms enhance this functionality: prefix detection, which accurately identifies prefixed words (e.g. …”

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

“…The screening process employed the SOL docking program with MMFF94 force field and genetic algorithms for global optimization, targeting the human AChE structure (PDB ID: 6O4W). …”

Data Sheet 1_Following intravenous thrombolysis, the outcome of diabetes mellitus associated with acute ischemic stroke was predicted via machine learning.docx by Xiaoqing Liu (196900)

“…The findings underscore the effectiveness of machine learning algorithms, particularly XGB, in predicting functional outcomes in diabetic AIS patients, providing clinicians with a valuable tool for treatment planning and improving patient outcome predictions based on receiver operating characteristic (ROC) analysis and accuracy assessments.…”

Turkish_native_goat_genotypes by Yalçın YAMAN (20209833)

“…</p><p dir="ltr">Nine heterogeneous machine-learning models—including penalised linear methods, gradient-boosting algorithms, and interaction-sensitive tree ensembles—were applied to examine genotype–phenotype relationships. …”

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

“…Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

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

“…Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

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

“…Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

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

“…Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

<b>NanoNeuroBot: Beyond Healing, Toward Human Connection</b> by ahmed hossam (21420446)

“…<p dir="ltr">NanoNeuroBot & NeuroStimAI: Dual Non-Invasive Neuroregenerative Therapies for Spinal Cord Injury</p><p><br></p><p dir="ltr">⸻</p><p><br></p><p dir="ltr">Abstract / Description:</p><p><br></p><p dir="ltr">This dual-initiative research introduces two complementary, non-invasive technologies designed to restore neural connectivity and functionality in patients with Spinal Cord Injury (SCI).…”

<b>Drug Release Nanoparticle Systems Design:</b><b>Dataset Compilation and Machine Learning Modeling</b> by Shan He (14524901)

“…In this paper, we experimentally synthesized and characterized new Fe₃O₄basedMNPs, functionalizing its surface with a 5-TAMRA cadaverine modified copolymer consisting of PMAO and PEG. …”

Image 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

“…Their immune-related functions highlight their potential for guiding targeted immunotherapy strategies.…”

Image 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

“…Their immune-related functions highlight their potential for guiding targeted immunotherapy strategies.…”

Table 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx by Zhi-Chuan He (21563657)

“…Their immune-related functions highlight their potential for guiding targeted immunotherapy strategies.…”

Image 3_Dysregulated arginine metabolism is associated with pro-tumor neutrophil polarization in liver cancer.tif by Xingchao Liu (3501161)

“…Although neutrophils are recognized as key regulators of LIHC progression, their functional heterogeneity and metabolic drivers are not yet fully understood.…”

Image 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

“…Their immune-related functions highlight their potential for guiding targeted immunotherapy strategies.…”

Image 5_Dysregulated arginine metabolism is associated with pro-tumor neutrophil polarization in liver cancer.tif by Xingchao Liu (3501161)

“…Although neutrophils are recognized as key regulators of LIHC progression, their functional heterogeneity and metabolic drivers are not yet fully understood.…”

Image 4_Dysregulated arginine metabolism is associated with pro-tumor neutrophil polarization in liver cancer.tif by Xingchao Liu (3501161)

“…Although neutrophils are recognized as key regulators of LIHC progression, their functional heterogeneity and metabolic drivers are not yet fully understood.…”