Michael F. Berger mostly deals with Internal medicine, Cancer research, Cancer, Genetics and Oncology. His research in Internal medicine intersects with topics in Diabetes mellitus and Endocrinology. His Cancer research includes themes of Genetic testing, Evidence-based medicine, Bioinformatics and Pathology.
Michael F. Berger interconnects Mutation, Human genetics, MEDLINE and Genomics in the investigation of issues within Bioinformatics. Many of his studies on Genetics apply to Computational biology as well. His Personalized medicine research is multidisciplinary, incorporating perspectives in Topoisomerase inhibitor and Drug discovery.
Michael F. Berger mainly focuses on Internal medicine, Oncology, Cancer research, Cancer and Pathology. His Internal medicine research is multidisciplinary, relying on both Diabetes mellitus and Endocrinology. His Oncology research focuses on Germline and how it relates to Germline mutation.
His studies in Cancer research integrate themes in fields like Mutation, KRAS, Gene, Somatic cell and Kinase. His Gene research is included under the broader classification of Genetics. His Bioinformatics research extends to Cancer, which is thematically connected.
His primary scientific interests are in Internal medicine, Oncology, Cancer research, Cancer and Germline. Internal medicine is closely attributed to Germline mutation in his study. The various areas that Michael F. Berger examines in his Oncology study include Clinical trial, Disease, Chemotherapy and Cohort.
The Cancer research study which covers Mutation that intersects with Lineage. His Cancer research includes elements of Computational biology, Sequencing data, DNA sequencing and Drug resistance. His Germline research focuses on subjects like Somatic cell, which are linked to Liquid biopsy.
Michael F. Berger focuses on Internal medicine, Oncology, Cancer research, Cancer and Clinical trial. His work on Prospective cohort study, Disease and Chemotherapy as part of general Internal medicine research is frequently linked to In patient, thereby connecting diverse disciplines of science. His Oncology study incorporates themes from MEDLINE, Lynch syndrome, Cohort and Immunotherapy.
Michael F. Berger combines subjects such as Mutation, Gene, Receptor, Targeted therapy and HRAS with his study of Cancer research. His research on Cancer focuses in particular on Esophagogastric cancer. His Clinical trial study combines topics in areas such as Methotrexate, Refractory, Combination therapy and Lymphoma.
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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Jordi Barretina;Giordano Caponigro;Nicolas Stransky;Kavitha Venkatesan.
Comprehensivemolecular characterization of clear cell renal cell carcinoma
Chad J. Creighton;Margaret Morgan;Preethi H. Gunaratne;Preethi H. Gunaratne;David A. Wheeler.
The Mutational Landscape of Head and Neck Squamous Cell Carcinoma
N. Stransky;A. M. Egloff;A. D. Tward;A. D. Kostic.
Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients
Ahmet Zehir;Ryma Benayed;Ronak H Shah;Aijazuddin Syed.
Nature Medicine (2017)
Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing
Garrett M Frampton;Alex Fichtenholtz;Geoff A Otto;Kai Wang.
Nature Biotechnology (2013)
Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A Hybridization Capture-Based Next-Generation Sequencing Clinical Assay for Solid Tumor Molecular Oncology
Donavan T. Cheng;Talia N. Mitchell;Ahmet Zehir;Ronak H. Shah.
The Journal of Molecular Diagnostics (2015)
The genomic complexity of primary human prostate cancer
Michael F. Berger;Michael F. Berger;Michael S. Lawrence;Francesca Demichelis;Yotam Drier.
Punctuated Evolution of Prostate Cancer Genomes
Sylvan C Baca;Davide Prandi;Michael S Lawrence;Juan Miguel Mosquera.
Dissecting therapeutic resistance to RAF inhibition in melanoma by tumor genomic profiling.
Nikhil Wagle;Caroline Emery;Michael F. Berger;Matthew J. Davis.
Journal of Clinical Oncology (2011)
Tumor mutational load predicts survival after immunotherapy across multiple cancer types.
Robert M Samstein;Chung-Han Lee;Chung-Han Lee;Alexander N Shoushtari;Alexander N Shoushtari;Matthew D Hellmann;Matthew D Hellmann.
Nature Genetics (2019)
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