Wang, Bo

Similarity network fusion for aggregating data types on a genomic scale

Wang, B., Mezlini, A. M., Demir, F., Fiume, M., Tu, Z., Brudno, M., Haibe-Kains, B., & Goldenberg, A. (2014) · Nature Methods

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 2,036

scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI

Cui, H., Wang, C., Maan, H., Pang, K., Luo, F., & Wang, B. (2023) · Nature Methods

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 1,383

Machine learning for integrating data in biology and medicine: principles, practice, and opportunities

Zitnik, M., Nguyen, F., Wang, B., Leskovec, J., Goldenberg, A., & Hoffman, M. M. (2019) · Information Fusion

Bioinformatics and Genomic NetworksBiomedical Text Mining and Ontologies

Cited by 675

Transparency and reproducibility in artificial intelligence

Haibe-Kains, B., Adam, G. A., Hosny, A., Khodakarami, F., Massive Analysis Quality Control (MAQC) Society Board of Directors, Shraddha, T., Kusko, R., Sansone, S.-A., Tong, W., Wolfinger, R. D., et al. (2020) · Nature

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 540

The multimodality cell segmentation challenge: toward universal solutions

Ma, J., Xie, R., Ayyadhury, S., Ge, C., Gupta, A., Gupta, R., Gu, S., Zhang, Y., Lee, G., Kim, J., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesAdvanced Neural Network Applications

Cited by 154

Long-term Mortality Risk Stratification of Liver Transplant Recipients: Real-Time Application of Deep Learning Algorithms on Longitudinal Data

Nitski, O., Azhie, A., Qazi-Arisar, F. A., Wang, X., Ma, S., Lilly, L., Watt, K. D., Levitsky, J., Asrani, S. K., Lee, D. S., et al. (2021) · The Lancet Digital Health

Organ Transplantation Techniques and OutcomesMachine Learning in Healthcare

Cited by 110

Deep Differentiable Random Forests for Age Estimation

Shen, W., Guo, Y., Wang, Y., Zhao, K., Wang, B., & Yuille, A. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Face recognition and analysisAdvanced Neural Network Applications

Cited by 91

Detecting and Remediating Harmful Data Shifts for the Responsible Deployment of Clinical AI Models

Subasri, V., Krishnan, A., Kore, A., Dhalla, A., Pandya, D., Wang, B., Malkin, D., Razak, F., Verma, A. A., Goldenberg, A., et al. (2025) · JAMA Network Open

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 87

Segment Anything in Medical Images

Ma, J., He, Y., Li, F., Han, L., You, C., & Wang, B. (2023) · arXiv

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 67

Towards foundation models of biological image segmentation

Ma, J., & Wang, B. (2023) · Nature Methods

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 57

Clinical Camel: An Open Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding

Toma, A., Lawler, P. R., Ba, J., Krishnan, R. G., Rubin, B. B., & Wang, B. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 36

Generative AI could revolutionize health care — but not if control is ceded to big tech

Toma, A., Senkaiahliyan, S., Lawler, P. R., Rubin, B., & Wang, B. (2023) · Nature

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 29

Orthrus: toward evolutionary and functional RNA foundation models

Fradkin, P., Shi, R. “., Dalal, T., Isaev, K., Frey, B. J., Lee, L. J., Morris, Q., & Wang, B. (2026) · Nature Methods

Genomics and Phylogenetic StudiesRNA Research and Splicing

Cited by 22

Orthrus: Towards Evolutionary and Functional RNA Foundation Models

Fradkin, P., Shi, R., Dalal, T., Isaev, K., Frey, B. J., Lee, L. J., Morris, Q., & Wang, B. (2024) · Nature Methods

Genomics and Phylogenetic StudiesRNA Research and Splicing

Cited by 22

Deep learning perturbation models can outperform baselines on calibrated metrics

Miller, H. E., Mejia, G. M., Leblanc, F. J. A., Swain, B., Wang, B., & de Lima Camillo, L. P. (2026) · Nature Biotechnology

Gene Regulatory Network AnalysisCRISPR and Genetic Engineering

Cited by 18

BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing

Fries, J. A., Weber, L., Seelam, N., Altay, G., Datta, D., Garda, S., Kang, M., Su, R., Kusa, W., Cahyawijaya, S., et al. (2022) · arXiv

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 17

MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition

Xie, R., Pang, K., Bader, G. D., & Wang, B. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Cell Image Analysis TechniquesAdvanced Neural Network Applications

Cited by 17

Human haematopoietic stem cells remember inflammatory stress

Zeng, A. G. X., Nagree, M. S., Jakobsen, N. A., Shah, S., Varesi, A., Kang, J. R. W., Murison, A., Cheong, J.-G., Turkalj, S., Zhang, X., et al. (2026) · Nature

Hematopoietic Stem Cell TransplantationAcute Myeloid Leukemia Research

Cited by 10

Diversity by Design: Addressing Mode Collapse Improves scRNA-seq Perturbation Modeling on Well-Calibrated Metrics

Mejia, G. M., Miller, H. E., Leblanc, F. J. A., Wang, B., Swain, B., & Camillo, L. P. D. L. (2025) · arXiv

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 6

Exploring the Design Space of 3D MLLMs for CT Report Generation

Baharoon, M., Ma, J., Fang, C., Toma, A., & Wang, B. (2025) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 2

CodeExp: Explanatory Code Document Generation

Cui, H., Wang, C., Huang, J., Inala, J. P., Mytkowicz, T., Wang, B., Gao, J., & Duan, N. (2022) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 2