SSD-DIS dataset by Jia Li (21599438)

“…Given the large volume of shadow-free document data, both the dataset and the processing scripts are stored on Baidu Netdisk. …”

CROHME and HME100K Handwritten Mathematical Expression Datasets by Yanjun Wei (22417297)

“…</p><p dir="ltr">Both datasets are widely used for benchmarking handwriting recognition models and serve as valuable resources for developing and evaluating advanced deep learning algorithms in the field of handwritten mathematical expression recognition.…”

Workflow of the flow cytometry experiment and the software-based analysis. by Verena Fischer (3857632)

“…In the present study, we determined the populations CD11b+Ly6G+F4/80- granulocytes, CD11b+Ly6G-F4/80+ macrophages, CD11b+Ly6G+F4/80+ MDSCs, CD19+ B-cells, CD3+ T-cells, CD3+CD8+ cytotoxic T-cells, CD3+CD4+ Thelper-cells as of interest for us. (6) The program calculates multiple subclusters based on AI/machine learning-algorithms. The subclusters can either be independent from the defined population tree or they are classified as subclusters within the pre-defined subpopulations from the population tree. …”

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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

Table 3_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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

Table 4_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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

Table 2_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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

Image 2_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)

“…Differentially expressed genes (DEGs) between TNBC and other BRCA subtypes were intersected with T cell-related genes to identify candidate biomarkers. Machine learning algorithms were used to screen for key hub genes, which were then used to construct a logistic regression (LR) model. …”

Table 1_Integrated analysis of lncRNA and mRNA expression profiles in cutaneous leishmaniasis lesions caused by Leishmania tropica.xlsx by Shima Hadifar (8681223)

“…</p>Methods<p>Herein, we used our previous RNA sequencing data (GSE216638) to investigate the profile of lncRNAs in the skin lesions of L. tropica-infected patients. …”

Table 3_Integrated analysis of lncRNA and mRNA expression profiles in cutaneous leishmaniasis lesions caused by Leishmania tropica.xlsx by Shima Hadifar (8681223)

“…</p>Methods<p>Herein, we used our previous RNA sequencing data (GSE216638) to investigate the profile of lncRNAs in the skin lesions of L. tropica-infected patients. …”

Genomics dataset of marine isolate Streptomyces griseoincarnatus strain R-35 by Danielle Dana Mitchell (20461301)

“…Genome annotations performed using the Rapid Annotation with Subsystem Technology (RAST) and the Bacterial and Viral Bioinformatics Resource Centre (BV-BRC) determined the presence of 7996 coding sequences (CDS), 63 transfer RNAs (tRNAs), and six ribosomal RNAs (rRNAs). …”

Table 4_Integrated analysis of lncRNA and mRNA expression profiles in cutaneous leishmaniasis lesions caused by Leishmania tropica.xlsx by Shima Hadifar (8681223)

“…</p>Methods<p>Herein, we used our previous RNA sequencing data (GSE216638) to investigate the profile of lncRNAs in the skin lesions of L. tropica-infected patients. …”

Table 2_Integrated analysis of lncRNA and mRNA expression profiles in cutaneous leishmaniasis lesions caused by Leishmania tropica.xlsx by Shima Hadifar (8681223)

“…</p>Methods<p>Herein, we used our previous RNA sequencing data (GSE216638) to investigate the profile of lncRNAs in the skin lesions of L. tropica-infected patients. …”

Data Sheet 1_Evaluating the effectiveness of AI-enhanced “One Body, Two Wings” pharmacovigilance models in China: a nationwide survey on medication safety and risk management.pdf... by Jian Yang (12136)

“…As the pharmaceutical landscape grows more complex, integrating AI into pharmacovigilance offers the potential to enhance adverse drug reaction (ADR) detection and monitoring.</p>Methods<p>A nationwide cross-sectional survey was conducted from June 25 to August 10, 2024, involving 1,000 participants from pharmacovigilance centers, hospitals, corporations, and the general public. …”

Supplementary Material for: Developing and tailoring a person-centred pathway for mental health care for people receiving dialysis by figshare admin karger (2628495)

“…Descriptive analyses of the survey data and summative content analysis of qualitative data (written survey comments and data from focus groups and interviews) were conducted to understand current processes, health services, and interventions for mental health care in Alberta Kidney Care for people receiving dialysis, and to determine appropriateness and opportunities of existing mental health services and interventions. …”

Workflow summary: GRN motif, cell signaling model, and inference framework. by Michael Alexander Ramirez Sierra (20209354)

“…<b>[B]</b> Pipeline of data generation and analysis. Key stages of parameter inference (columns 1 through 5). …”

Table 12_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”