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Nature Communications|September 19, 2022
Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanomaAndrew Patterson, Noam Auslander
International Journal of Molecular Sciences|April 3, 2021
Incorporating Machine Learning into Established Bioinformatics FrameworksNoam Auslander, Ayal B Gussow, Eugene V Koonin
Cancers|April 13, 2023
Computational Methods Summarizing Mutational Patterns in Cancer: Promise and Limitations for Clinical ApplicationsAndrew Patterson, Abdurrahman Elbasir, Bin Tian, et al.
Proceedings of the National Academy of Sciences of the United States of America|April 25, 2019
In silico learning of tumor evolution through mutational time seriesNoam Auslander, Yuri I Wolf, Eugene V Koonin
Plos Computational Biology|September 28, 2016
Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival PredictionNoam Auslander, Allon Wagner, Matthew Oberhardt, et al.
Cancer Informatics|March 27, 2019
Predicting Complete Remission of Acute Myeloid Leukemia: Machine Learning Applied to Gene ExpressionOphir Gal, Noam Auslander, Yu Fan, et al.
Plos Computational Biology|September 11, 2025
kMermaid: Ultrafast metagenomic read assignment to protein clusters by hashing of amino acid k-mer frequenciesAnastasia Lucas, Daniel E Schäffer, Jayamanna Wickramasinghe, et al.
Biorxiv : the Preprint Server for Biology|April 29, 2026
OncoBERT: Context-Aware Modeling of Somatic Mutations for Precision OncologySushant Patkar, Noam Auslander, Stephanie Harmon, et al.
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