Standout Papers

TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-a... 2020 2026 2022 2024289
  1. TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments (2020)
    Lifan Chen, Xiaoqin Tan et al. Bioinformatics

Immediate Impact

1 by Nobel laureates 55 standout
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Citing Papers

Quantitative prediction of toxicological points of departure using two-stage machine learning models: A new approach methodology (NAM) for chemical risk assessment
2025 Standout
Machine Learning-Assisted High-Donor-Number Electrolyte Additive Screening toward Construction of Dendrite-Free Aqueous Zinc-Ion Batteries
2025 Standout
2 intermediate papers

Works of Lifan Chen being referenced

A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling
2021

Author Peers

Author Last Decade Papers Cites
Lifan Chen 434 380 12 166 19 585
Tianbiao Yang 442 364 6 134 17 606
Nicolas Bosc 379 362 18 106 12 595
Norman Sieroka 234 288 2 148 22 537
Christoph Gorgulla 463 311 16 109 15 645
Jeff Blaney 326 376 2 172 9 635
Christof Gerlach 406 355 6 235 15 659
Paul Coote 388 247 10 101 14 538
Hans‐Christian Ehrlich 376 186 42 82 11 584
Peter Monecke 391 292 17 122 19 618
Xi Chen 285 251 5 118 37 568

All Works

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Rankless by CCL
2026