Cheng, Feixiong

The Immune Landscape of Cancer

Thorsson, V., Gibbs, D. L., Brown, S. D., Wolf, D., Bortone, D. S., Ou Yang, T.-H., Porta-Pardo, E., Gao, G. F., Plaisier, C. L., Eddy, J. A., et al. (2018) · Immunity

Cancer Immunotherapy and BiomarkersImmune cells in cancer

Cited by 5,870

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

Liu, J., Lichtenberg, T., Hoadley, K. A., Poisson, L. M., Lazar, A. J., Cherniack, A. D., Kovatich, A. J., Benz, C. C., Levine, D. A., Lee, A. V., et al. (2018) · Cell

Cancer Genomics and DiagnosticsGene expression and cancer classification

Cited by 3,725

Oncogenic Signaling Pathways in The Cancer Genome Atlas

Sanchez-Vega, F., Mina, M., Armenia, J., Chatila, W. K., Luna, A., La, K. C., Dimitriadoy, S., Liu, D. L., Kantheti, H. S., Saghafinia, S., et al. (2018) · Cell

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

Cited by 3,201

Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

Hoadley, K. A., Yau, C., Hinoue, T., Wolf, D. M., Lazar, A. J., Drill, E., Shen, R., Taylor, A. M., Cherniack, A. D., Thorsson, V., et al. (2018) · Cell

Cancer Genomics and DiagnosticsGene expression and cancer classification

Cited by 2,546

Comprehensive Characterization of Cancer Driver Genes and Mutations

Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell

Cancer Genomics and DiagnosticsGenomics and Rare Diseases

Cited by 2,256

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

Malta, T. M., Sokolov, A., Gentles, A. J., Burzykowski, T., Poisson, L., Weinstein, J. N., Kamińska, B., Huelsken, J., Omberg, L., Gevaert, O., et al. (2018) · Cell

Cancer Cells and MetastasisPluripotent Stem Cells Research

Cited by 2,180

Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., Samaras, D., Shroyer, K. R., Zhao, T., Batiste, R., et al. (2018) · Cell Reports

AI in cancer detectionCancer Immunotherapy and Biomarkers

Cited by 1,027

Alzheimer’s disease drug development pipeline: 2024

Cummings, J., Zhou, Y., Lee, G., Zhong, K., Fonseca, J., & Cheng, F. (2024) · Alzheimer's & Dementia: Translational Research & Clinical Interventions

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 702

Artificial intelligence in COVID-19 drug repurposing

Zhou, Y., Wang, F., Tang, J., Nussinov, R., & Cheng, F. (2020) · The Lancet Digital Health

Computational Drug Discovery MethodsArtificial Intelligence in Healthcare and Education

Cited by 636

Network-based approach to prediction and population-based validation of in silico drug repurposing

Cheng, F., Desai, R. J., Handy, D. E., Wang, R., Schneeweiss, S., Barabási, A.-L., & Loscalzo, J. (2018) · Nature Communications

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 552

Comprehensive Characterization of Cancer Driver Genes and Mutations

Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

Cited by 552

Comprehensive Molecular Characterization of the Hippo Signaling Pathway in Cancer

Wang, Y., Xu, X., Maglic, D., Dill, M. T., Mojumdar, K., Ng, P. K.-S., Jeong, K. J., Tsang, Y. H., Moreno, D., Bhavana, V. H., et al. (2018) · Cell Reports

Hippo pathway signaling and YAP/TAZCancer-related molecular mechanisms research

Cited by 500

Alzheimer’s disease drug development pipeline: 2023

Cummings, J., Zhou, Y., Lee, G., Zhong, K., Fonseca, J., & Cheng, F. (2023) · Alzheimer's & Dementia: Translational Research & Clinical Interventions

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 477

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Schaub, F. X., Dhankani, V., Berger, A. C., Trivedi, M., Richardson, A. B., Shaw, R., Zhao, W., Zhang, X., Ventura, A., Liu, Y., et al. (2018) · Cell Systems

Cancer Genomics and DiagnosticsCancer-related Molecular Pathways

Cited by 431

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

Ding, L., Bailey, M. H., Porta-Pardo, E., Thorsson, V., Colaprico, A., Bertrand, D., Gibbs, D. L., Weerasinghe, A., Huang, K.-L., Tokheim, C., et al. (2018) · Cell

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

Cited by 399

Target identification among known drugs by deep learning from heterogeneous networks

Zeng, X., Zhu, S., Lu, W., Liu, Z., Huang, J., Zhou, Y., Fang, J., Huang, Y., Guo, H., Li, L., et al. (2020) · Chemical Science

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 357

Deep generative molecular design reshapes drug discovery

Zeng, X., Wang, F., Luo, Y., Kang, S.-G., Tang, J., Lightstone, F. C., Fang, E. F., Cornell, W., Nussinov, R., & Cheng, F. (2022) · Cell Reports Medicine

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 295

Reducing acetylated tau is neuroprotective in brain injury

Shin, M.-K., Vázquez-Rosa, E., Koh, Y., Dhar, M., Chaubey, K., Cintrón-Pérez, C. J., Barker, S., Miller, E., Franke, K., Noterman, M. F., et al. (2021) · Cell

Alzheimer's disease research and treatmentsTraumatic Brain Injury Research

Cited by 226

A genome-wide positioning systems network algorithm for in silico drug repurposing

Cheng, F., Lu, W., Liu, C., Fang, J., Hou, Y., Handy, D. E., Wang, R., Zhao, Y., Yang, Y., Huang, J., et al. (2019) · Nature Communications

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 215

Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer’s disease

Fang, J., Zhang, P., Zhou, Y., Chiang, C.-W., Tan, J., Hou, Y., Stauffer, S., Li, L., Pieper, A. A., Cummings, J., et al. (2021) · Nature Aging

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 206

Alzheimer's disease drug development pipeline: 2025

Cummings, J. L., Zhou, Y., Lee, G., Zhong, K., Fonseca, J., Leisgang‐Osse, A. M., & Cheng, F. (2025) · Alzheimer's & Dementia: Translational Research & Clinical Interventions

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 190

A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19

Zhou, Y., Hou, Y., Shen, J., Mehra, R., Kallianpur, A., Culver, D. A., Gack, M. U., Farha, S., Zein, J., Comhair, S., et al. (2020) · PLoS Biology

Bioinformatics and Genomic NetworksSARS-CoV-2 and COVID-19 Research

Cited by 180

Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer’s disease

Fang, J., Zhang, P., Wang, Q., Chiang, C.-W., Zhou, Y., Hou, Y., Xu, J., Chen, R., Zhang, B., Lewis, S. J., et al. (2022) · Alzheimer's Research & Therapy

Alzheimer's disease research and treatmentsComputational Drug Discovery Methods

Cited by 140

Publisher Correction: Network-based prediction of drug combinations

Cheng, F., Kovács, I. A., & Barabási, A.-L. (2019) · Nature Communications

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 131