王博｜中国药科大学｜学者主页

2026

LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery.

Yue Xu, Haotian Cui, Kuan Pang, Gen Li, Fang-Lin Gong, Song-Tao Dong, Bo Wang, Bo-Wen Li

Cell

2026

A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling

Mehran Karimzadeh, L. Fish, Heather Karner, Johannes Linder, A. Emadi, A. Hernandez-Corchado, F. Smaili, Khashayar Ghavami, Edna S. Stewart, David R. Kelley, Bo Wang, Hamed S. Najafabadi, Manuel D. Leonetti, H. Goodarzi

bioRxiv

DOI

2026

Generalist biological artificial intelligence in modeling the language of life

Vishwanatha M. Rao, Serena Zhang, Brian S. Plosky, Patrick D. Hsu, Bo Wang, James Zou, M. Zitnik, Eric J. Topol, P. Rajpurkar

Nature Biotechnology

DOI

2026

dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning

Arnav Shah, Jun-Zhe Li, Parsa Idehpour, Adibvafa Fallahpour, Brandon Wang, Sukjun Hwang, Bo Wang, Patrick D. Hsu, H. Goodarzi, Albert Gu

arXiv.org

DOI

2026

Orthrus: toward evolutionary and functional RNA foundation models

Phil Fradkin, Rui-An Shi, Taykhoom Dalal, Keren Isaev, Brendan J. Frey, Leo J. Lee, Quaid Morris, Bo Wang

Nature Methods

DOI

2026

BioReason-Pro: Advancing Protein Function Prediction with Multimodal Biological Reasoning

Adibvafa Fallahpour, A. Seyed-Ahmadi, Parsa Idehpour, Omar Ibrahim, Benedict M. H. Choi, Purav Gupta, Jack Naimer, Kevin Zhu, Abhinav K. Adduri, Arnav Shah, Shihao Ma, Talu Güloglu, Nuo Liu, Haotian Cui, Arihant Jain, M. de Castro, Amirfaham Fallahpour, A. Cembellin-Prieto, John S. Stiles, Filip Nemčko, Alexander A. Nevue, Hyungseok C. Moon, Lucas Sosnick, O. Markham, Haonan Duan, Michelle Y. Y. Lee, Andrea F. M. Salvador, Chris J. Maddison, Cristoph Thaiss, Chiara Ricci-Tam, Brian S. Plosky, Dave P. Burke, Patrick D. Hsu, H. Goodarzi, Bo Wang

bioRxiv

DOI

2026

X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language Models

Chloe Wang, Mehran Karimzadeh, Neal G. Ravindra, Lexi R. Bounds, Nader Alerasool, Ann C. Huang, Shihao Ma, D. Gulbranson, Haotian Cui, Yongju Lee, Anusuya Arjavalingam, Elliot J. MacKrell, M. Wilken, Jie-Ming Chen, Benjamin W. Herken, J. A. Weber, Massimo M. Onesto, Bárbara González-Terán, N. F. Leung, S. Shi, Byron J. Smith, Sharon Lam, Adam Barner, P. Wright, Elizabeth M. Rumsey, Soohong Kim, Re-Ne V. Sit, Adam J. Litterman, C. Chu, Bo Wang

bioRxiv

DOI

2026

CpGPT: a Foundation Model for DNA Methylation

Lucas Paulo de Lima Camillo, R. Sehgal, J. Armstrong, Max Melnikas, Henry E. Miller, Jun Ding, L. Ferruci, J. Lasky-Su, A. Higgins-Chen, S. Horvath, Bo Wang

bioRxiv

DOI

2025

Towards multimodal foundation models in molecular cell biology

Haotian Cui, Alejandro Tejada-Lapuerta, Maria Brbić, J. Sáez-Rodríguez, Simona Cristea, H. Goodarzi, M. Lotfollahi, F. Theis, Bo Wang

Nature

DOI

2025

scGPT: end-to-end protocol for fine-tuned retinal cell type annotation.

Shan-Li Ding, Jin Li, Ruibang Luo, Haotian Cui, Bo Wang, Rui Chen

Nature Protocols

DOI

2025

Harnessing artificial intelligence to advance CRISPR-based genome editing technologies

Tyler Thomson, Gen Li, A. Strilchuk, Haotian Cui, Bo Wang, Bo-Wen Li

Nature reviews genetics

DOI

2025

Transformers and genome language models

Micaela E. Consens, Cameron Dufault, Michael Wainberg, Duncan Forster, Mehran Karimzadeh, H. Goodarzi, F. Theis, Alan M. Moses, Bo Wang

Nature Machine Intelligence

DOI

2025

Interpreting Attention Mechanisms in Genomic Transformer Models: A Framework for Biological Insights

Micaela E. Consens, A. Díaz-Navarro, Vivian Chu, Lincoln D. Stein, Hou-Sheng H. He, Alan M. Moses, Bo Wang

bioRxiv

DOI

2025

In silico generation of synthetic cancer genomes using generative AI

A. Díaz-Navarro, Xin-Di Zhang, W. Jiao, Bo Wang, Lincoln D. Stein

bioRxiv

DOI

2025

scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics

Chloe Wang, Haotian Cui, Andrew Zhang, Ronald Xie, H. Goodarzi, Bo Wang

bioRxiv

DOI

2025

Moving towards genome-wide data integration for patient stratification with Integrate Any Omics

Shihao Ma, Andy G. X. Zeng, Benjamin Haibe-Kains, Anna Goldenberg, John E. Dick, Bo Wang

Nature Machine Intelligence

DOI

2025

mRNABench: A curated benchmark for mature mRNA property and function prediction

Rui-An Shi, Taykhoom Dalal, Phil Fradkin, Divya Koyyalagunta, Simran Chhabria, A. Jung, Cyrus Tam, Defne Ceyhan, Jessica Lin, Kaitlin U. Laverty, Ilyes Baali, Bo Wang, Quaid D. Morris

bioRxiv

DOI

2025

Exploring Drug Repositioning: Enhanced Co-Delivery of Disulfiram and Celecoxib by Nanostructured Lipid Carriers for Breast Cancer Cells

Theodora Amanda Seidu, Muhammad Asim Farooq, Masanja Pius Wande, Sana Ghayas, Perpetua Takunda Kutoka, Raphael Nammahime Alolga, Bo Wang

Current Drug Delivery

DOI

2024

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery

Yue Xu, Shihao Ma, Haotian Cui, Jin-Gan Chen, Shufen Xu, Fang-Lin Gong, Alex Golubovic, Mu-Ye Zhou, K. Wang, Andrew Varley, R. X. Z. Lu, Bo Wang, Bo-Wen Li

Nature Communications

DOI

2024

MorphoDiff: Cellular Morphology Painting with Diffusion Models

Zeinab Navidi, Jun Ma, Esteban A. Miglietta, Le Liu, A. Carpenter, B. Cimini, Benjamin Haibe-Kains, Bo Wang

bioRxiv

DOI

2024

FraGNNet: A Deep Probabilistic Model for Tandem Mass Spectrum Prediction

A. Young, Fei Wang, D. Wishart, Bo Wang, Russell Greiner, Hannes Rost

Trans. Mach. Learn. Res.

2024

scGPT: toward building a foundation model for single-cell multi-omics using generative AI

Haotian Cui, Chloe Wang, H. Maan, Kuan Pang, Fengning Luo, Nan Duan, Bo Wang

Nature Methods

DOI

2024

Transformers in single-cell omics: a review and new perspectives

A. Szałata, Karin Hrovatin, Sören Becker, Alejandro Tejada-Lapuerta, Haotian Cui, Bo Wang, F. Theis

Nature Methods

DOI

2024

Tandem mass spectrum prediction for small molecules using graph transformers

A. Young, H. Röst, Bo Wang

Nature Machine Intelligence

DOI

2024

DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics

Haotian Cui, H. Maan, Maria C. Vladoiu, Jiao Zhang, Michael D. Taylor, Bo Wang

Genome Biology

DOI

2024

Characterizing the impacts of dataset imbalance on single-cell data integration

H. Maan, Lin Zhang, Cheng-Xin Yu, Michael J. Geuenich, Kieran R. Campbell, Bo Wang

Nature Biotechnology

DOI

2024

MethylGPT: a foundation model for the DNA methylome

K. Ying, Jinyeop Song, Haotian Cui, Yi-Kun Zhang, Si-Yuan Li, Xingyu Chen, Hanna Liu, A. Eames, Daniel L. McCartney, R. Marioni, J. Poganik, M. Moqri, Bo Wang, V. Gladyshev

bioRxiv

DOI

2024

GraphComm: A Graph-based Deep Learning Method to Predict Cell-Cell Communication in single-cell RNAseq data

Emily So, S. Hayat, S. Nair, Bo Wang, Benjamin Haibe-Kains

bioRxiv

DOI

2023

Towards foundation models of biological image segmentation

Jun Ma, Bo Wang

Nature Methods

DOI

2023

Reusability Report: Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients

Emily So, Feng Yu, Bo Wang, Benjamin Haibe-Kains

bioRxiv

DOI

2023

The use of machine learning models to predict PFS and OS outcomes from waterfall plots in randomized clinical trials (MAP-OUTCOMES).

K. Alshankati, A. Alshibany, Augustin Toma, K. Lajkosz, Bo Wang, Benjamin Haibe-Kains, L. Siu

JCO Global Oncology

DOI

2023

CongFu: Conditional Graph Fusion for Drug Synergy Prediction

Oleksii Tsepa, Bohdan Naida, Bo Wang

arXiv.org

DOI

2022

Development of diagnostic and prognostic molecular biomarkers in hepatocellular carcinoma using machine learning: A systematic review

A. Brar, A. Zhu, C. Baciu, Divya Sharma, Wei Xu, A. Orchanian-Cheff, Bo Wang, J. Reimand, R. Grant, M. Bhat

HPB

DOI

2022

The promise of machine learning applications in solid organ transplantation

N. Gotlieb, A. Azhie, Divya Sharma, Ashley Spann, Nan-Jia Suo, Jason Tran, A. Orchanian-Cheff, Bo Wang, Anna Goldenberg, M. Chassé, H. Cardinal, Joseph Paul Cohen, Andrea Lodi, Mélanie Dieudé, M. Bhat

npj Digital Medicine

DOI

2021

scDeepHash: An automatic cell type annotation and cell retrieval method for large-scale scRNA-seq datasets using neural network-based hashing

Shihao Ma, Yanyi Zhang, Bo-Hao Wang, Zian Hu, Jing-Wei Zhang, Bo Wang

bioRxiv

DOI

2020

Applying Machine Learning in Liver Disease and Transplantation: A Comprehensive Review

Ashley Spann, Angeline Yasodhara, J. Kang, K. Watt, Bo Wang, Anna Goldenberg, M. Bhat

Hepatology

DOI

2019

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

Walter Nelson, M. Zitnik, Bo Wang, J. Leskovec, Anna Goldenberg, Roded Sharan

Frontiers in Genetics

DOI

2014

Similarity network fusion for aggregating data types on a genomic scale

Bo Wang, A. Mezlini, Feyyaz Demir, M. Fiume, Zhuowen Tu, M. Brudno, B. Haibe-Kains, Anna Goldenberg

Nature Methods

DOI

精选作品

期刊论文

LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery.

A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling

Generalist biological artificial intelligence in modeling the language of life

dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning

Orthrus: toward evolutionary and functional RNA foundation models

BioReason-Pro: Advancing Protein Function Prediction with Multimodal Biological Reasoning

X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language Models

CpGPT: a Foundation Model for DNA Methylation

Towards multimodal foundation models in molecular cell biology

scGPT: end-to-end protocol for fine-tuned retinal cell type annotation.

Harnessing artificial intelligence to advance CRISPR-based genome editing technologies

Transformers and genome language models

Interpreting Attention Mechanisms in Genomic Transformer Models: A Framework for Biological Insights

In silico generation of synthetic cancer genomes using generative AI

scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics

Moving towards genome-wide data integration for patient stratification with Integrate Any Omics

mRNABench: A curated benchmark for mature mRNA property and function prediction

Exploring Drug Repositioning: Enhanced Co-Delivery of Disulfiram and Celecoxib by Nanostructured Lipid Carriers for Breast Cancer Cells

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery

MorphoDiff: Cellular Morphology Painting with Diffusion Models

FraGNNet: A Deep Probabilistic Model for Tandem Mass Spectrum Prediction

scGPT: toward building a foundation model for single-cell multi-omics using generative AI

Transformers in single-cell omics: a review and new perspectives

Tandem mass spectrum prediction for small molecules using graph transformers

DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics

Characterizing the impacts of dataset imbalance on single-cell data integration

MethylGPT: a foundation model for the DNA methylome

GraphComm: A Graph-based Deep Learning Method to Predict Cell-Cell Communication in single-cell RNAseq data

Towards foundation models of biological image segmentation

Reusability Report: Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients

The use of machine learning models to predict PFS and OS outcomes from waterfall plots in randomized clinical trials (MAP-OUTCOMES).

CongFu: Conditional Graph Fusion for Drug Synergy Prediction

Development of diagnostic and prognostic molecular biomarkers in hepatocellular carcinoma using machine learning: A systematic review

The promise of machine learning applications in solid organ transplantation

scDeepHash: An automatic cell type annotation and cell retrieval method for large-scale scRNA-seq datasets using neural network-based hashing

Applying Machine Learning in Liver Disease and Transplantation: A Comprehensive Review

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

Similarity network fusion for aggregating data types on a genomic scale

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