Rui Yin

Rui Yin

Assistant Professor at Department of Health Outcomes and Biomedical Informatics, University of Florida

Please find the most recent articles on my Google Scholar profile

2025
  • Song, R., Mikaeel, R. R., He, Z., Horsnell, M., Uylaki, W., Meng, W., … & Fan, X. (2025). Identification of Novel Susceptibility Genes for Early-Onset Colorectal Cancer Through Germline Rare Variant Burden Testing. Cancers, 17(24), 3931.
  • Jin, Z., Guo, X., Wang, Z., Yang, Q., Yang, X., Zhang, X., … & Garmire, L. X. (2025). PANCDetect: Early Detection of Pancreatic Cancer from Multimodal EHR data with LLM Embeddings. medRxiv, 2025-10.
  • deCrecy, C., Calin, D., Yang, Q., Yin, R., & Sharma, A. (2025). OR19-04 MASLD-a Forgotten Complication in Young Adults with Type 2 Diabetes. Journal of the Endocrine Society, 9(Supplement_1), bvaf149-1024.
  • Yin, R., Gutiérrez-Sacristán, A., Undiagnosed Diseases Network, Kobren, S. N., & Avillach, P. (2025). VarPPUD: Pinpointing diagnostic variants from sets of prioritized, strong candidate variants. PLOS Computational Biology, 21(9), e1013414.
  • Li, L., Yang, Q., Li, L., Zhao, H., Xu, J., Xie, M., & Yin, R.* (2025). GIN-CRC-Pareto: A graph-based Pareto-optimal multi-task learning framework to identify miRNA-target interactions in colorectal cancer. bioRxiv.
  • Yin, R.*, Li, J., Yang, Q., Chen, X., Zhang, X., Lin, M., … & Subramaniam, A. (2025). MTLNFM: A Multi-task Framework Using Neural Factorization Machines to Predict Patient Clinical Outcomes. Applied Sciences, 15(15), 8733.
  • Zhang, Z., Lily, W. A. N. G., Weimin, M. E. N. G., Chang, L. I. U., Hui, S. H. A. O., Yan, V. S., … & Carl, Y. A. N. G. (2025). Type 2 Diabetes Subtyping via Phenotype and Genotype Co-Learning. Studies in health technology and informatics, 329, 1064.
  • Yang, Q., Meng, W., Zhuang, P., Anton, S., Wu, Y., & Yin, R.* (2025). AutoRADP: An Interpretable Deep Learning Framework to Predict Rapid Progression for Alzheimer’s Disease and Related Dementias Using Electronic Health Records. medRxiv, 2025-04.
  • Zeng, M., Zhang, X., Li, Y., Lu, C., Yin, R., Guo, F., & Li, M. (2025). RNALoc-LM: RNA subcellular localization prediction using pre-trained RNA language model. Bioinformatics, 41(4), btaf127.
  • Yang, Q., Fan, X., Zhao, H., Ma, Z., Stanifer, M., Bian, J., … & Yin, R.* (2025). SEHI-PPI: An End-to-End Sampling-Enhanced Human-Influenza Protein-Protein Interaction Prediction Framework with Double-View Learning. bioRxiv, 2025-03.
  • Yang, Q., Sharma, A., Calin, D., de Crecy, C., Inampudi, R., & Yin, R.* (2025). FCFNets: A Factual and Counterfactual Learning Framework for Enhanced Hepatic Fibrosis Prediction in Young Adults with T2D. medRxiv, 2025-03.
  • Meng W, Yang Q, Xu J, Huang Y, Wang C, Song Q, Song L, Bian J, Ma Q, Ma A, Yin, R.* (2025). Identifying Sex-Specific Sub-phenotypes of Alzheimer’s Disease Progression Using Longitudinal Electronic Health Records. medRxiv [Preprint]. 2025 Aug 21:2024.07.07.24310055. doi: 10.1101/2024.07.07.24310055. PMID: 39040206; PMCID: PMC11261930.
  • Chen, W. H., Lee, Y. A., Tang, H., Li, C., Lu, Y., Huang, Y., … & Guo, J. (2025). Social Determinants of Healthy Aging: An Investigation using the All of Us Cohort. medRxiv, 2025-01.
  • Meng W, Inampudi R, Zhang X, Xu J, Huang Y, Xie M, Bian J, Yin, R.* (2025). An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer’s Disease Using UK Biobank. AMIA Annu Symp Proc. 2025 May 22;2024:808-817. PMID: 40417509; PMCID: PMC12099444.
2024
  • Yin, R.*, Zhao, H., Li, L., Yang, Q., Zeng, M., Yang, C., … & Xie, M. (2024). Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer. Computational and Structural Biotechnology Journal, 23, 3020-3029.
  • Zhuang, P., Scott, B., Gao, S., Meng, W. M., Yin, R., Nie, X., … & Cho, C. F. (2024). Blood-tumor barrier organoids recapitulate glioblastoma microenvironment and enable high-throughput modeling of therapeutic delivery. bioRxiv, 2024-11.
  • Yin, R., Wack, M., Hassen-Khodja, C., McDuffie, M. T., Bliss, G., Horn, E. J., … & Avillach, P. (2024). Phenome-wide profiling identifies genotype-phenotype associations in Phelan-McDermid syndrome using family-sourced data from an international registry. Molecular Autism, 15(1), 40.
  • Li, C., Wang, H., Wen, Y., Yin, R.*, Zeng, X., & Li, K. (2024). GenoM7GNet: an efficient N7-Methylguanosine site prediction approach based on a nucleotide language model. IEEE/ACM transactions on computational biology and bioinformatics.
  • Li, M., Zhao, B., Li, Y., Ding, P., Yin, R., Kan, S., & Zeng, M. (2024). SGCL-LncLoc: an interpretable deep learning model for improving IncRNA subcellular localization prediction with supervised graph contrastive learning. Big Data Mining and Analytics, 7(3), 765-780.
  • Luo, H., Tang, L., Zeng, M., Yin, R., Ding, P., Luo, L., & Li, M. (2024). BertSNR: an interpretable deep learning framework for single-nucleotide resolution identification of transcription factor binding sites based on DNA language model. Bioinformatics, 40(8), btae461.
  • Arif, A., Wang, Y., Yin, R., Zhang, X., & Helmy, A. (2024). EF-Net: mental state recognition by analyzing multimodal EEG-fNIRS via CNN. Sensors, 24(6), 1889.
  • Xu, J., Yin, R., Huang, Y., Gao, H., Wu, Y., Guo, J., … & Bian, J. (2024, January). Identification of outcome-oriented progression subtypes from mild cognitive impairment to Alzheimer’s disease using electronic health records. In AMIA Annual Symposium Proceedings (Vol. 2023, p. 764).
2023
  • Hendricks-Sturrup, R., Simmons, M., Anders, S., Aneni, K., Clayton, E. W., Coco, J., … & Malin, B. (2023). Developing ethics and equity principles, terms, and engagement tools to advance health equity and researcher diversity in AI and machine learning: modified Delphi approach. Jmir ai, 2(1), e52888.
  • Zhou, T., Glanz, Z., Liu, M., Bian, J., Yin, R.*, & Gao, H. (2023, December). HSELDA: Heterogeneous Sub-Graph Learning for lncRNA-Disease Associations Prediction. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1798-1805). IEEE.
  • Wan, Z., Lin, Z., Rashid, S., Ng, S. Y. H., Yin, R., Senthilnath, J., & Kwoh, C. K. (2023, December). PESI: paratope-epitope set interaction for SARS-CoV-2 neutralization prediction. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 49-56). IEEE.- - Ding, P., Zeng, M., Yin, R.* (2023). Editorial: Computational Methods to Analyze RNA Data for Human Diseases. Frontiers in Genetics.
  • Zeng, M., Wu, Y., Li, Y., Yin, R., Lu, C., Duan, J., & Li, M. (2023). LncLocFormer: a transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism. Bioinformatics, 39(12), btad752.
  • Zhang, Y., Yin, R., & Liu, X. (2023). Changes in Cyclic Guanosine monophosphate channel of 661w cells in vitro with excessive light time. Journal of ophthalmic & vision research, 18(4), 417.
  • Yin, R.*, Luo, Z., Zhuang, P., Zeng, M., Li, M., Lin, Z., Kwoh, C. K. (2023). ViPal: a framework for virulence prediction of influenza viruses with prior viral knowledge using genomic sequences. Journal of Biomedical Informatics, 142, 104388.
  • Yin, R.*, Ye, B., Bian J. (2023). CLCAP: Contrastive Learning Improves Antigenicity Prediction for Influenza A Virus Using Convolutional Neural Networks. Methods
  • Ming, Y., Wang, W., Yin, R., Zeng, M., Tang, L., Tang, S., & Li, M. (2023). A review of enzyme design in catalytic stability by artificial intelligence. Briefings in Bioinformatics, 24(3), bbad065.
  • Lin, Z., Feng, L., Guo, X., Zhang, Y., Yin, R., Kwoh, C. K., Xu, C. (2023). Comet: Convolutional dimension interaction for collaborative filtering. ACM Transactions on Intelligent Systems and Technology, 14(4), 1-18.
  • Li, M., Zhao, B., Yin, R., Lu, C., Guo, F., & Zeng, M. (2023). GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation. Briefings in Bioinformatics, 24(1), bbac565.
2022
  • Li M, Zhao B, Yin R, et al. GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence-to-graph transformation. Briefings in Bioinformatics (2022)
  • Yin R, Zhu X, Kwoh CK, et al. “A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods.” Briefings in Bioinformatics (2022)
  • Zhang W, Wu P, Yin R, Sun M, Zhang R, Liao X, Lin Y, Lu H. Mendelian Randomization Analysis Suggests No Associations of Herpes Simplex Virus Infections With Multiple Sclerosis. Frontiers in neuroscience. 2022;16. (pdf)
2021
  • Yin R, Luo Z, Kwoh CK. Exploring the Lethality of Human-Adapted Coronavirus Through Alignment-Free Machine Learning Approaches Using Genomic Sequences. Current Genomics. 2021 Dec 1;22(8):583-95. (pdf)
  • Wu P, Du B, Wang B, Yin R, Lv X, Dai Y, Zhang W, Xia K. Joint Analysis of Genome-Wide Association Data Reveals No Genetic Correlations Between Low Back Pain and Neurodegenerative Diseases. Frontiers in genetics. 2021:1717. (pdf)
  • Yin R, Luo Z, Zhuang P, Zhuoyi Lin, et al. VirPreNet: a weighted ensemble convolutional neural network for the virulence prediction of influenza a virus using all 8 segments[J]. Bioinformatics. (pdf)
  • Lin Z, Feng L, Yin R, Xu C, Kwoh CK. GLIMG: Global and local item graphs for top-N recommender systems. Information Sciences. 2021 Nov 1;580:1-4. (pdf)
  • Yin R, Yin R, Thwin N N, Zhuang P, Zhuoyi Lin, et al. IAV-CNN: a 2D convolutional neural network model to predict antigenic variants of influenza A virus[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021. (pdf)
  • Wu PF, Zhang X, Zhou P, Yin R, Zhou XT, Zhang W. Growth differentiation factor 15 is associated with Alzheimer’s disease risk. Frontiers in Genetics. 2021 Aug 13:1500. (pdf)
2020
  • Yin R, Luusua E, Dabrowski J, et al. Tempel: Time-series Mutation Prediction of Influenza A Viruses via Attention-based Recurrent Neural Networks[J]. Bioinformatics, 2020. (pdf)
  • Zhang Y, Long Y, Yin R, et al. DL-CRISPR: A Deep Learning Method for Off-Target Activity Prediction in CRISPR/Cas9 With Data Augmentation[J]. IEEE Access, 2020, 8: 76610-76617. (pdf)
  • Yin R, Zhang Y, Zhou X, et al. Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks[J]. Journal of Bioinformatics and Computational Biology, 2020. (pdf)
  • Yin R,, Zhou X, Rashid S, et al. HopPER: an adaptive model for probability estimation of influenza reassortment through host prediction[J]. BMC Medical Genomics, 2020, 13(1): 9. (pdf)
2019
  • Zhou X, Yin R, Zheng J, et al. An encoding scheme capturing generic priors and properties of amino acids improves protein classification[J]. IEEE Access, 2019, 7: 7348-7356. (pdf)
  • Yin R, Chee Keong Kwoh, and Jie Zheng. Whole Genome Sequencing Analysis: Computational Pipelines and Workflows in Bioinformatics, Encyclopedia of Bioinformatics and Computational Biology, 176-183, 2019. (pdf)
2018
  • Yin R, Tran V H, Zhou X, et al. Predicting antigenic variants of H1N1 influenza virus based on epidemics and pandemics using a stacking model[J]. PloS one, 2018, 13(12): e0207777. (pdf)
  • Zhou X, Yin R, Kwoh C K, et al. A context-free encoding scheme of protein sequences for predicting antigenicity of diverse influenza A viruses[J]. BMC genomics, 2018, 19(10): 936. (pdf)
  • Yin R, Zhou X, Zheng J, et al. Computational identification of physicochemical signatures for host tropism of influenza A virus[J]. Journal of bioinformatics and computational biology, 2018: 1840023- 1840023. (pdf)
  • Ding P, Yin R, Luo J, et al. Ensemble Prediction of Synergistic Drug Combinations Incorporating Biological, Chemical, Pharmacological and Network Knowledge[J]. IEEE journal of biomedical and health informatics, 2018. (pdf)
  • Yin R, Tan J, Akhila D, et al. Inference of Sequence Homology by BLAST visualization of Influenza Genome set[C]//Proceedings of the 9th International Conference on Computational Systems-Biology and Bioinformatics. ACM, 2018: 5. (pdf)
2017
  • Ivan F X, Zhou X, Deshpande A, Yin R, et al. Phylogenetic tree based method for uncovering co- mutational site-pairs in influenza viruses[C]//Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 2017: 21-26. (pdf)
  • Yin R, Zhou X, Ivan F X, et al. Identification of Potential Critical Virulent Sites Based on Hemagglu- tinin of Influenza a Virus in Past Pandemic Strains[C]//Proceedings of the 6th International Conference on Bioinformatics and Biomedical Science. ACM, 2017: 30-36. (Best presentation) (pdf)
Prior to 2016
  • The device of matrix sedimentation, China, 2014
  • The device and method of Linear sweep polarographic wave model, China, 2013