Publications

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Publish Date:   2022-03-08

Selected Publications

(† co-first, * corresponding, authors from the group are highlighted in bold)
See this link for full publication list.

  1. Y. Si, C. Yan*. Protein language model embedded geometric graphs power inter-protein contact prediction, eLife 2024, 12:RP92184; doi: https://elifesciences.org/articles/92184.
  2. The EN-TEx resource of multi-tissue personal epigenomes and variant-impact models. Cell 2023, 186, 1493-1511. (The EN-TEx Project, C. Yan is included as an co-author)
  3. Y. Si, C. Yan*. Improved inter-protein contact prediction using dimensional hybrid residual networks and protein language models, Briefings in Bioinformatics , 2023, bbad039.
  4. Y. Si, C. Yan*. Protein Complex Structure Prediction Powered by Multiple Sequence Alignments of Interologs from Multiple Taxonomic Ranks and AlphaFold2, Briefings in Bioinformatics 2022, 23, bbac208.
  5. Y. Si, Y. Zhang, C. Yan*. A reproducibility analysis-based statistical framework for evolutionary coupling detection, Briefings in Bioinformatics 2022, 23, bbab576, doi: 10.1093/bib/bbab576.
  6. Y. Si, C. Yan*. Improved protein contact prediction using dimensional hybrid residual networks and singularityenhanced loss function, Briefings in Bioinformatics 2021, 22, bbab341.
  7. A. Sethi, M. Gu, E. Gumusgoz, L. Chan, K. Yan, J. Rozowsky, I. Barozzi, V. Afzal, J. Akiyama, I. Plajzer-Frick, C. Yan et al. A cross-organism framework for supervised enhancer prediction with epigenetic pattern recognition and targeted validation. Nat. Methods , 17:807-814, 2020 (Part of the ENCODE project).
  8. B. Wang†, C. Yan†, S. Lou, P. Emani, B. Li, M. Xu, X. Kong, W. Meyerson, D.
    Lee, M. Gerstein. Integrating genetic and structural features: building a hybrid model to characterize variants for protein-drug interactions. Structure , 27: 1469-1481,2019. († Equally contributed)
  9. F. Navarro, H. Mohsen, C. Yan, S. Li, M. Gu, W. Meyerson, M. Gerstein. Genomics and data science: an application within an umbrella. Genome biology , 20:109, 2019
  10. D. Wang, S. Liu, J. Warrell, H. Won, X. Shi, F. Navarro, D. Clarke, M. Gu, P. Emani, Y. Yang, M. Xu, M. Gandal, S. Lou, J. Zhang, J. Park, C. Yan et al. Comprehensive functional genomics resource and integrative model for the human brain. Science , 362: eaat8464, 2018 (Part of the PsychENCODE project).
  11. X. Xu†, C. Yan†, X. Zou. MDockPeP: An ab-initio protein-peptide docking server. J. Comput. Chem. , 38: 2409-2413, 2018 († Equally contributed).
  12. K. Yan. G. Yardimci, C. Yan, W. Nobel, M. Gerstein. HiC-spector: a matrix library for spectral and reproducibility analysis of Hi-C contact maps. Bioinformatics , 33: 2199-2201, 2017.
  13. X. Xu†, L. Qiu†, C. Yan†, Z. Ma, S. Grinter, X. Zou. Performance of MDockPP in CAPRI Rounds 28-29 and 31-35 including the prediction of water-mediated interactions. Proteins , 85: 424-434,2017. († Equally contributed)
  14. C. Yan, X. Zou. Modeling protein flexibility in molecular docking. Comprehensive Medicinal Chemistry III , 3: 319-328, 2017. (Invited book chapter)
  15. C. Yan, X. Xu, X. Zou. The usage of ACCLUSTER for peptide binding site prediction. Methods in molecular biology , 1516: 3-9, 2017 (Invited book chapter)
  16. C. Yan†, X. Xu†, X. Zou. Fully blind docking at the atomic level for protein-peptide complex structure prediction. Structure , 24: 1842-1853, 2016.
  17. C. Yan, X. Zou. MDock: An ensemble docking suite for molecular docking, scoring and in silico screening. Methods in Pharmacology and Toxicology , pp 153-166, 2016. (Invited book chapter).
  18. C. Yan, S. Grinter, B. Merideth, Z. Ma, X. Zou. Iterative knowledge-based scoring functions derived from rigid and flexible decoy structures: Evaluation with the 2013 and 2014 CSAR benchmarks. J. Chem. Inf. Model. , 56: 1013-1021, 2016.
  19. C. Yan, X. Zou. Predicting peptide binding sites on protein surfaces by clustering chemical interactions. J. Comput. Chem., 36: 49-61, 2015. (Featured in the inside cover of the issue).
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