Publications

WT1 and BCORL1 Identified By Computational Biology Modeling Analysis of Patient Genomics Are Novel Predictors of Response to Azacitidine (AZA) and Lenalidomide (LEN) Treatment in Acute Myeloid Leukemia (AML)

Blood Journal,

Clinical Validation of Treatment Response Predictions Using a Genomics Driven Computational Biology Modelling Multiple Myeloma Algorithm

Blood Journal,

Azacitidine Response Prediction in MDS Patients with NGS Data Using a Computational Biology Modeling (CBM) Based Clinical Decision Support System

Blood Journal,

Identification of Molecular Subtypes of Thymic Epithelial Tumors and Novel Treatments Using a Computational Biological Model

Journal of Thoracic Oncology,

Computational Biological Model Prediction of PD-L1 Expression and Immunotherapy Response for KRAS Mutated Lung Cancer Based on Co-Mutations

Journal of Thoracic Oncology,

Genomics-driven clustering of disease-related biomarkers identifies therapeutic options in myelodysplastic syndromes (MDS)

AACR,

iCare 1: A prospective clinical trial to predict treatment response based on genomics-informed computational biology in patients with acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS).

ASCO Annual Meeting,

Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.

BMC Cancer,

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