Nilsa C. Ramirez
Impact in
- Cancer Research top 0.02%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- Oncology top 0.05%
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Cancer Genomics and Diagnostics 31
- Oncology 25
- Cancer-related Molecular Pathways 6
- Co-authors
- Venu Raman (1 shared paper)Brett M. Hall (1 shared paper)Amy Kate Sasser (1 shared paper)Tatiana M. Oberyszyn (1 shared paper)Amy E. Axel (1 shared paper)Nicholas J. Sullivan (1 shared paper)Farhad Vesuna (1 shared paper)Heather A. Lankes (13 shared papers)
- Journals
- Cell (16 papers)Cell Reports (15 papers)Cancer Cell (13 papers)Gynecologic Oncology (13 papers)Journal of Clinical Oncology (6 papers)
- Partner nations
- United StatesCanadaJapan
In The Last Decade
Nilsa C. Ramirez
111 papers receiving 57.1k citations
Nilsa C. Ramirez's Hit Papers
Peers
Comparison fields: 5 of 175
- Cancer Research 15.3k
- Oncology 15.5k
- Pulmonary and Respiratory Medicine 11.7k
- Molecular Biology 24.1k
- Immunology 5.2k
Countries citing papers authored by Nilsa C. Ramirez
This map shows the geographic impact of Nilsa C. Ramirez'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 Nilsa C. Ramirez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nilsa C. Ramirez more than expected).
Fields of papers citing papers by Nilsa C. Ramirez
This network shows the impact of papers produced by Nilsa C. Ramirez. 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 Nilsa C. Ramirez. The network helps show where Nilsa C. Ramirez may publish in the future.
Co-authors
The 25 scholars most cited alongside Nilsa C. Ramirez, 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 114 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comprehensive molecular characterization of gastric adenocarcinoma Hit paper breakdown → | 2014 | 5209 |
| 2 | The Immune Landscape of Cancer Hit paper breakdown → | 2018 | 4331 |
| 3 | An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Hit paper breakdown → | 2018 | 2602 |
| 4 | Genomic Classification of Cutaneous Melanoma Hit paper breakdown → | 2015 | 2509 |
| 5 | Integrated Genomic Characterization of Papillary Thyroid Carcinoma Hit paper breakdown → | 2014 | 2442 |
| 6 | The Molecular Taxonomy of Primary Prostate Cancer Hit paper breakdown → | 2015 | 2435 |
| 7 | Comprehensive molecular characterization of urothelial bladder carcinoma Hit paper breakdown → | 2014 | 2419 |
| 8 | Oncogenic Signaling Pathways in The Cancer Genome Atlas Hit paper breakdown → | 2018 | 2334 |
| 9 | Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma Hit paper breakdown → | 2017 | 1970 |
| 10 | Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer Hit paper breakdown → | 2017 | 1931 |
| 11 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1720 |
| 12 | Comprehensive Characterization of Cancer Driver Genes and Mutations Hit paper breakdown → | 2018 | 1714 |
| 13 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Hit paper breakdown → | 2016 | 1643 |
| 14 | Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Hit paper breakdown → | 2018 | 1617 |
| 15 | Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma Hit paper breakdown → | 2017 | 1559 |
| 16 | Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer Hit paper breakdown → | 2015 | 1471 |
| 17 | Integrated genomic and molecular characterization of cervical cancer Hit paper breakdown → | 2017 | 1221 |
| 18 | Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas Hit paper breakdown → | 2018 | 810 |
| 19 | Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images Hit paper breakdown → | 2018 | 761 |
| 20 | Genomic and Functional Approaches to Understanding Cancer Aneuploidy Hit paper breakdown → | 2018 | 749 |
About Nilsa C. Ramirez
Nilsa C. Ramirez is a scholar working on Cancer Research, Oncology, Obstetrics and Gynecology, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 114 papers that have together received 57.8k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (31 papers), Genetic factors in colorectal cancer (8 papers), Endometrial and Cervical Cancer Treatments (8 papers), RNA modifications and cancer (8 papers), Ovarian cancer diagnosis and treatment (7 papers), Ferroptosis and cancer prognosis (7 papers), Cancer-related Molecular Pathways (6 papers) and Epigenetics and DNA Methylation (6 papers). The work is most often cited by research in Cancer Research (15.3k citations), Oncology (15.5k citations), Pulmonary and Respiratory Medicine (11.7k citations), Molecular Biology (24.1k citations) and Immunology (5.2k citations). Nilsa C. Ramirez has collaborated with scholars based in United States, Canada and Japan. Frequent co-authors include Venu Raman, Brett M. Hall, Amy Kate Sasser, Tatiana M. Oberyszyn, Amy E. Axel, Nicholas J. Sullivan, Farhad Vesuna, Heather A. Lankes, David E. Cohn and Paul DiSilvestro. Their work appears in journals such as Cell, Cell Reports, Cancer Cell, Gynecologic Oncology and Journal of Clinical Oncology.
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.