Brian Patrick O’Neill
Impact in
- Genetics top 0.02%
- Glioma Diagnosis and Treatment
- Cancer Research top 0.05%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- Breast Cancer Treatment Studies
Papers in
- Co-authors
- Derek Richard Johnson (3 shared papers)David Schiff (14 shared papers)Judith Rich O'Fallon (16 shared papers)Bernd Walter Scheithauer (18 shared papers)Caterina Giannini (16 shared papers)Paul J. Kurtin (13 shared papers)David W. Kimmel (6 shared papers)Robert P. Dinapoli (9 shared papers)
- Journals
- Neurology (21 papers)Neuro-Oncology (20 papers)Mayo Clinic Proceedings (15 papers)Cancer (14 papers)Cell Reports (12 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Brian Patrick O’Neill
237 papers receiving 52.9k citations
Brian Patrick O’Neill's Hit Papers
Peers
Comparison fields: 5 of 176
- Genetics 10.1k
- Cancer Research 11.5k
- Oncology 9.5k
- Neurology 4.4k
- Molecular Biology 11.6k
Countries citing papers authored by Brian Patrick O’Neill
This map shows the geographic impact of Brian Patrick O’Neill's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Brian Patrick O’Neill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Patrick O’Neill more than expected).
Fields of papers citing papers by Brian Patrick O’Neill
This network shows the impact of papers produced by Brian Patrick O’Neill. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Brian Patrick O’Neill. The network helps show where Brian Patrick O’Neill may publish in the future.
Co-authors
The 25 scholars most cited alongside Brian Patrick O’Neill, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 250 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The Immune Landscape of Cancer Hit paper breakdown → | 2018 | 4385 |
| 2 | The Somatic Genomic Landscape of Glioblastoma Hit paper breakdown → | 2013 | 4012 |
| 3 | An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Hit paper breakdown → | 2018 | 2633 |
| 4 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2401 |
| 5 | Oncogenic Signaling Pathways in The Cancer Genome Atlas Hit paper breakdown → | 2018 | 2371 |
| 6 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2169 |
| 7 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1758 |
| 8 | Comprehensive Characterization of Cancer Driver Genes and Mutations Hit paper breakdown → | 2018 | 1748 |
| 9 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Hit paper breakdown → | 2016 | 1659 |
| 10 | Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Hit paper breakdown → | 2018 | 1634 |
| 11 | Glioma Groups Based on 1p/19q, IDH , and TERT Promoter Mutations in Tumors Hit paper breakdown → | 2015 | 1623 |
| 12 | Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas Hit paper breakdown → | 2018 | 824 |
| 13 | Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images Hit paper breakdown → | 2018 | 771 |
| 14 | Genomic and Functional Approaches to Understanding Cancer Aneuploidy Hit paper breakdown → | 2018 | 768 |
| 15 | Report of an International Workshop to Standardize Baseline Evaluation and Response Criteria for Primary CNS Lymphoma Hit paper breakdown → | 2005 | 734 |
| 16 | The evolutionary history of 2,658 cancers Hit paper breakdown → | 2020 | 730 |
| 17 | Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients Hit paper breakdown → | 2018 | 696 |
| 18 | Glioblastoma survival in the United States before and during the temozolomide era Hit paper breakdown → | 2011 | 630 |
| 19 | Pathogenic Germline Variants in 10,389 Adult Cancers Hit paper breakdown → | 2018 | 617 |
| 20 | Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines Hit paper breakdown → | 2018 | 598 |
About Brian Patrick O’Neill
Brian Patrick O’Neill is a scholar working on Neurology, Genetics, Cancer Research, Clinical Biochemistry and Pulmonary and Respiratory Medicine, having authored 250 papers that have together received 54.2k indexed citations. Recurring topics across this work include CNS Lymphoma Diagnosis and Treatment (65 papers), Glioma Diagnosis and Treatment (47 papers), Cancer Genomics and Diagnostics (36 papers), Metabolism and Genetic Disorders (13 papers), Autoimmune Neurological Disorders and Treatments (13 papers), Cardiac Valve Diseases and Treatments (12 papers), Brain Metastases and Treatment (11 papers) and Lymphoma Diagnosis and Treatment (10 papers). The work is most often cited by research in Genetics (10.1k citations), Cancer Research (11.5k citations), Oncology (9.5k citations), Neurology (4.4k citations) and Molecular Biology (11.6k citations). Brian Patrick O’Neill has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Derek Richard Johnson, David Schiff, Judith Rich O'Fallon, Bernd Walter Scheithauer, Caterina Giannini, Paul J. Kurtin, David W. Kimmel, Robert P. Dinapoli, Paul D. Brown and Jan C. Buckner. Their work appears in journals such as Neurology, Neuro-Oncology, Mayo Clinic Proceedings, Cancer and Cell Reports.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.