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Chunhui Cai
Chunhui Cai
Boston Children's Hospital
Verified email at childrens.harvard.edu
Title
Cited by
Cited by
Year
Inferring causal molecular networks: empirical assessment through a community-based effort
SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ...
Nature methods 13 (4), 310-318, 2016
2372016
Learning a hierarchical representation of the yeast transcriptomic machinery using an autoencoder model
L Chen, C Cai, V Chen, X Lu
BMC bioinformatics 17, 97-107, 2016
1072016
Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma
JD Young, C Cai, X Lu
BMC bioinformatics 18, 5-17, 2017
642017
Chitinase-3-like 1 protein complexes modulate macrophage-mediated immune suppression in glioblastoma
A Chen, Y Jiang, Z Li, L Wu, U Santiago, H Zou, C Cai, V Sharma, Y Guan, ...
The Journal of clinical investigation 131 (16), 2021
592021
Trans-species learning of cellular signaling systems with bimodal deep belief networks
L Chen, C Cai, V Chen, X Lu
Bioinformatics 31 (18), 3008-3015, 2015
392015
Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference
C Cai, GF Cooper, KN Lu, X Ma, S Xu, Z Zhao, X Chen, Y Xue, AV Lee, ...
PLoS computational biology 15 (7), e1007088, 2019
372019
From genome to phenome: Predicting multiple cancer phenotypes based on somatic genomic alterations via the genomic impact transformer
Y Tao, C Cai, WW Cohen, X Lu
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020, 79-90, 2019
242019
Tumor-specific causal inference (tci): A bayesian method for identifying causative genome alterations within individual tumors
G Cooper, C Cai, X Lu
bioRxiv, 225631, 2017
132017
Modeling signal transduction from protein phosphorylation to gene expression
C Cai, L Chen, X Jiang, X Lu
Cancer Informatics 13, CIN. S13883, 2014
82014
Tumour-specific causal inference discovers distinct disease mechanisms underlying cancer subtypes
Y Xue, G Cooper, C Cai, S Lu, B Hu, X Ma, X Lu
Scientific reports 9 (1), 13225, 2019
32019
Signal-oriented pathway analyses reveal a signaling complex as a synthetic lethal target for p53 mutations
S Lu, C Cai, G Yan, Z Zhou, Y Wan, V Chen, L Chen, GF Cooper, ...
Cancer research 76 (23), 6785-6794, 2016
32016
Testing of a machine learning (ML) model for ability to predict oxaliplatin and bevacizumab (bev) benefit in NRG Oncology/NSABP C-07 and C-08.
X Lu, L Chen, Y Wang, C Cai, RS Kim, C Lipchik, D Fumagalli, G Yothers, ...
Journal of Clinical Oncology 40 (16_suppl), 3607-3607, 2022
12022
Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer
L Chen, Y Wang, C Cai, Y Ding, RS Kim, C Lipchik, PG Gavin, G Yothers, ...
Journal of Clinical Oncology, JCO. 23.01080, 2024
2024
FAK loss reduces BRAFV600E-induced ERK phosphorylation to promote intestinal stemness and cecal tumor formation
C Gao, H Ge, SF Kuan, C Cai, X Lu, F Esni, R Schoen, J Wang, E Chu, ...
2024
An individualized Bayesian method for estimating genomic variants of hypertension
MA Rahman, C Cai, N Bo, DM McNamara, Y Ding, GF Cooper, X Lu, J Liu
BMC genomics 23 (Suppl 5), 863, 2023
2023
A Novel Bayesian Framework Infers Driver Activation States and Reveals Pathway-Oriented Molecular Subtypes in Head and Neck Cancer
Z Liu, C Cai, X Ma, J Liu, L Chen, VWY Lui, GF Cooper, X Lu
Cancers 14 (19), 4825, 2022
2022
A Novel Bayesian Framework Infers Driver Activation States and Reveals Pathway-Oriented Molecular Subtypes in Head and Neck Cancer. Cancers 2022, 14, 4825
Z Liu, C Cai, X Ma, J Liu, L Chen, VWY Lui, GF Cooper, X Lu
s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022
2022
Identification of instance-specific somatic genome alterations with functional impact
X Lu, G Cooper, C Cai, S Visweswaran
US Patent App. 16/349,192, 2019
2019
Trans-species learning of cellular signaling with bimodal deep belief networks
L Chen, C Cai, V Chen, X Lu
Breast Cancer Challenge: Team “PittTransMed” places second for Metabric phase of the Challenge
S Lu, C Cai, HU Osmanbeyoglu, L Chen, R Day, G Cooper, X Lu
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