Anna Goldenberg
Anna Goldenberg
Scientist, SickKids Research Institute; Assistant Professor Department of Computer Science, University of Toronto
Verified email at - Homepage
Cited by
Cited by
Similarity network fusion for aggregating data types on a genomic scale
B Wang, AM Mezlini, F Demir, M Fiume, Z Tu, M Brudno, B Haibe-Kains, ...
Nature methods 11 (3), 333-337, 2014
Integrated genomic characterization of pancreatic ductal adenocarcinoma
BJ Raphael, RH Hruban, AJ Aguirre, RA Moffitt, JJ Yeh, C Stewart, ...
Cancer cell 32 (2), 185-203. e13, 2017
A survey of statistical network models
A Goldenberg, AX Zheng, SE Fienberg, EM Airoldi
Foundations and Trends® in Machine Learning 2 (2), 129-233, 2010
Intertumoral heterogeneity within medulloblastoma subgroups
FMG Cavalli, M Remke, L Rampasek, J Peacock, DJH Shih, B Luu, ...
Cancer cell 31 (6), 737-754. e6, 2017
Sensitive tumour detection and classification using plasma cell-free DNA methylomes
SY Shen, R Singhania, G Fehringer, A Chakravarthy, MHA Roehrl, ...
Nature 563 (7732), 579-583, 2018
Do no harm: a roadmap for responsible machine learning for health care
J Wiens, S Saria, M Sendak, M Ghassemi, VX Liu, F Doshi-Velez, K Jung, ...
Nature medicine 25 (9), 1337-1340, 2019
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
M Zitnik, F Nguyen, B Wang, J Leskovec, A Goldenberg, MM Hoffman
Information Fusion 50, 71-91, 2019
What clinicians want: contextualizing explainable machine learning for clinical end use
S Tonekaboni, S Joshi, MD McCradden, A Goldenberg
Machine learning for healthcare conference, 359-380, 2019
Transparency and reproducibility in artificial intelligence
B Haibe-Kains, GA Adam, A Hosny, F Khodakarami, ...
Nature 586 (7829), E14-E16, 2020
TensorFlow: biology’s gateway to deep learning?
L Rampasek, A Goldenberg
Cell systems 2 (1), 12-14, 2016
Explaining image classifiers by counterfactual generation
CH Chang, E Creager, A Goldenberg, D Duvenaud
arXiv preprint arXiv:1807.08024, 2018
PharmacoGx: an R package for analysis of large pharmacogenomic datasets
P Smirnov, Z Safikhani, N El-Hachem, D Wang, A She, C Olsen, ...
Bioinformatics 32 (8), 1244-1246, 2016
Machine learning approaches to drug response prediction: challenges and recent progress
G Adam, L Rampášek, Z Safikhani, P Smirnov, B Haibe-Kains, ...
NPJ precision oncology 4 (1), 19, 2020
Early statistical detection of anthrax outbreaks by tracking over-the-counter medication sales
A Goldenberg, G Shmueli, RA Caruana, SE Fienberg
Proceedings of the National Academy of Sciences 99 (8), 5237-5240, 2002
Unsupervised representation learning for time series with temporal neighborhood coding
S Tonekaboni, D Eytan, A Goldenberg
arXiv preprint arXiv:2106.00750, 2021
Biological embedding of experience: a primer on epigenetics
MJ Aristizabal, I Anreiter, T Halldorsdottir, CL Odgers, TW McDade, ...
Proceedings of the National Academy of Sciences 117 (38), 23261-23269, 2020
Applying machine learning in liver disease and transplantation: a comprehensive review
A Spann, A Yasodhara, J Kang, K Watt, BO Wang, A Goldenberg, M Bhat
Hepatology 71 (3), 1093-1105, 2020
iReckon: simultaneous isoform discovery and abundance estimation from RNA-seq data
AM Mezlini, EJM Smith, M Fiume, O Buske, GL Savich, S Shah, S Aparicio, ...
Genome research 23 (3), 519-529, 2013
To embed or not: network embedding as a paradigm in computational biology
W Nelson, M Zitnik, B Wang, J Leskovec, A Goldenberg, R Sharan
Frontiers in genetics 10, 381, 2019
Recurrent noncoding U1 snRNA mutations drive cryptic splicing in SHH medulloblastoma
H Suzuki, SA Kumar, S Shuai, A Diaz-Navarro, A Gutierrez-Fernandez, ...
Nature 574 (7780), 707-711, 2019
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