Image5_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.tif حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Image2_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.tif حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Image4_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.tif حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table13_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table11_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table8_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table9_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table6_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table7_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table12_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table5_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Image1_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.tif حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Image3_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.tif حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

Table10_Integrating genomics and AI to uncover molecular targets for mRNA vaccine development in lupus nephritis.xlsx حسب Lisha Mou (151003)

"…Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. …"

An open paradigm dataset for intelligent monitoring of underground drilling operations in coal mines حسب pengzhen zhao (19023119)

"…The experimental results show that the proposed dataset can effectively improve the accuracy of various object detection and pose estimation models in coal mines, filling the data gap in the coal mining field and providing valuable resources for the development of coal mine safety monitoring and automation technologies.…"

Dataset for Partial Parallelism Plot Analysis in Neurodegeneration Biomarker Assays (2010–2024) حسب Axel Petzold (7076261)

"…<br></p><p dir="ltr">Each dataset entry is annotated with:</p><ul><li>Sample type (serum, plasma, cerebrospinal fluid)</li><li>Assay platform and dilution steps</li><li>Classification of outcome (partial parallelism achieved or not)</li></ul><p dir="ltr"><b>Use cases:</b><br>This dataset is designed to help researchers, assay developers, and meta-analysts to:</p><ul><li>Reproduce figures and analyses from the published review</li><li>Benchmark or validate new assay performance pipelines</li><li>Train algorithms for automated detection of dilutional non-parallelism</li></ul><p dir="ltr"><b>Files included:</b></p><ul><li><code>.csv</code> files containing dilution–response data</li><li>Metadata spreadsheets with assay and sample annotations</li></ul><p></p>…"

Image 2_Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis.tif حسب Chao Tan (698513)

"…</p>Conclusion<p>This study offers the first comprehensive bibliometric analysis of ML in proteomics, revealing key themes such as deep learning, pretrained models, and multi-omics integration. Future efforts should focus on building interpretable models, enhancing cross-disciplinary collaboration, and ensuring secure, standardized data use to advance precision medicine.…"

Table 1_Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis.docx حسب Chao Tan (698513)

"…</p>Conclusion<p>This study offers the first comprehensive bibliometric analysis of ML in proteomics, revealing key themes such as deep learning, pretrained models, and multi-omics integration. Future efforts should focus on building interpretable models, enhancing cross-disciplinary collaboration, and ensuring secure, standardized data use to advance precision medicine.…"

Image 1_Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis.png حسب Chao Tan (698513)

"…</p>Conclusion<p>This study offers the first comprehensive bibliometric analysis of ML in proteomics, revealing key themes such as deep learning, pretrained models, and multi-omics integration. Future efforts should focus on building interpretable models, enhancing cross-disciplinary collaboration, and ensuring secure, standardized data use to advance precision medicine.…"

Table3_A real-world pharmacovigilance analysis of eslicarbazepine acetate using the FDA adverse events reporting system (FAERS) database from 2013 (Q4) to 2024 (Q1).docx حسب Huafei Tang (19710232)

"…</p>Methods<p>By extracting all available data since the FDA approval of ESL (2013Q4-2024Q1), disproportionality analysis was performed using reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN) and multi-item gamma Poisson shrinker (MGPS) algorithms. …"