Table 3_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.xlsx by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 6_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 1_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 2_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 5_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Supplementary file 1_Hamiltonian formulations of centroid-based clustering.pdf by Myeonghwan Seong (21159605)

“…However, defining similarity is often ambiguous, making it challenging to determine the most appropriate objective function for a given dataset. Traditional clustering methods, such as the k-means algorithm and weighted maximum k-cut, focus on specific objectives—typically relying on average or pairwise characteristics of the data—leading to performance that is highly data-dependent. …”

Data Sheet 1_Modelling the spatial bound of an eDNA signal in the marine environment – the effect of local conditions.pdf by Tiago A. M. Silva (22188730)

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…<p dir="ltr">This dataset contains the data used in the article <a href="https://academic.oup.com/aob/advance-article/doi/10.1093/aob/mcaf043/8074229" rel="noreferrer" target="_blank">"Machine Learning and digital Imaging for Spatiotemporal Monitoring of Stress Dynamics in the clonal plant Carpobrotus edulis: Uncovering a Functional Mosaic</a>", which includes the complete set of collected leaf images, image features (predictors) and response variables used to train machine learning regression algorithms.…”

The organizational flow of the study. by Jennifer Hornung Garvin (20765727)

“…Participants identified design elements that were both facilitators and barriers to use. Usability scores for both prototypes were excellent. …”

Data Sheet 4_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Furthermore, the expression levels of these four genes were significantly altered in both independent validation datasets and in established oxaliplatin-resistant cell lines. …”

Data Sheet 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Furthermore, the expression levels of these four genes were significantly altered in both independent validation datasets and in established oxaliplatin-resistant cell lines. …”

Table 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.xlsx by Xiaopeng Zhan (4170574)

“…Furthermore, the expression levels of these four genes were significantly altered in both independent validation datasets and in established oxaliplatin-resistant cell lines. …”

Data Sheet 2_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Furthermore, the expression levels of these four genes were significantly altered in both independent validation datasets and in established oxaliplatin-resistant cell lines. …”

Image 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Furthermore, the expression levels of these four genes were significantly altered in both independent validation datasets and in established oxaliplatin-resistant cell lines. …”

Data Sheet 3_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Furthermore, the expression levels of these four genes were significantly altered in both independent validation datasets and in established oxaliplatin-resistant cell lines. …”

Descriptions of parameters and symbols (<i>t</i> = 1,2). by Minchao Zheng (20558832)

“…By utilizing Copula functions to model the complex relationship between fluctuating prices and uncertain demand, the study develops both continuous and discrete decision models for practical applications. …”

Solution of approximate optimal order quantity. by Minchao Zheng (20558832)

“…By utilizing Copula functions to model the complex relationship between fluctuating prices and uncertain demand, the study develops both continuous and discrete decision models for practical applications. …”

Data Sheet 1_Assessment of shoulder functional movements through inertial measurement units for tele-rehabilitation: a quaternion-based approach.pdf by Matteo Iurato (22155370)

“…Data from an IMU-based device were acquired during the execution of human functional shoulder movements by both a young and elderly group of participants. …”

Data analyzed for the article of <b>Evaluating photoplethysmography-based pulsewave parameters and composite scores for assessment of cardiac function: A comparison with echocardio... by Kulin (20907929)

“…Concurrently, echocardiographic parameters were derived by averaging the data from 1-3 heartbeats, allowing for a direct comparison of cardiac function assessments between the two techniques, by the following. …”

Table 1_Differential gene expression profiling and machine learning-based discovery of key genetic markers in VTE and CKD.docx by Hui Li (32376)

“…Machine learning analyses identified HNRNPA0 and PI4KA as the most robust feature genes, both exhibiting excellent diagnostic performance (AUC = 1.000). …”