Cross-dataset Validation
Cross-Dataset Validation is a validation methodology in pharmacophore modeling that assesses the generalizability and robustness of a pharmacophore model by evaluating its performance across distinct, independently curated datasets, thereby distinguishing it from single-dataset or internal validation approaches through its reliance on external data heterogeneity.
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528
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2017–2026
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The PRIDE database at 20 years: 2025 update
Yasset Pérez‐Riverol, Chakradhar Bandla, Deepti J Kundu et al. · Nucleic Acids Research · 2024 · 1.7K citations · Full text
Walter J. Scheirer, Anderson de Rezende Rocha, Amir Sapkota et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2012 · 1.5K citations
Appearance-based gaze estimation in the wild
2015 · 727 citations · Full text
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Chinese Academy of Sciences
Beijing, China
11 h-index
23 publications
1.3K citations
University of Washington
Seattle, United States
9 h-index
31 publications
2.8K citations
Tsinghua University
Beijing, China
8 h-index
14 publications
455 citations
University of Chinese Academy of Sciences
Beijing, China
7 h-index
15 publications
558 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
16 publications
1.1K citations
Nanyang Technological University
Singapore, Singapore
6 h-index
12 publications
3.1K citations
University of Science and Technology of China
Hefei, China
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21 publications
743 citations
Ludwig-Maximilians-Universität München
Munich, Germany
5 h-index
13 publications
178 citations
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Repository · 25 publications · 1.4K citations
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6 publications · 374 citations
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Conference · 6 publications · 152 citations
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