Nicholas A. Cilfone
- Infectious Diseases top 5%
- Tuberculosis Research and Epidemiology 6
- Immunology top 10%
- Atherosclerosis and Cardiovascular Diseases 3
- Immune Cell Function and Interaction 2
- Epidemiology top 10%
- Mycobacterium research and diagnosis 3
- Adipokines, Inflammation, and Metabolic Diseases 3
- Pneumonia and Respiratory Infections 2
- Modeling and Simulation top 10%
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- Computational Drug Discovery Methods 2
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- Antibiotic Resistance in Bacteria 2
- Co-authors
- Denise E. KirschnerJennifer J. LindermanJoshua T. MattilaSimeone MarinoJoAnne L. FlynnJeffrey R. GulcherThomas W. ChittendenJavier L. Baylon
- Journals
- The Journal of Experimental Medicine (1 paper)The Journal of Immunology (2 papers)PLoS ONE (1 paper)
- Partner nations
- United StatesFrance
In The Last Decade
Nicholas A. Cilfone
17 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 131
- Infectious Diseases 324
- Immunology 341
- Epidemiology 286
- Modeling and Simulation 35
- Computational Theory and Mathematics 86
Countries citing papers authored by Nicholas A. Cilfone
This map shows the geographic impact of Nicholas A. Cilfone'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 Nicholas A. Cilfone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas A. Cilfone more than expected).
Fields of papers citing papers by Nicholas A. Cilfone
This network shows the impact of papers produced by Nicholas A. Cilfone. 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 Nicholas A. Cilfone. The network helps show where Nicholas A. Cilfone may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nicholas A. Cilfone, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 21 | |
| 2 | 2020 | 2 | |
| 3 | Unconventional machine learning of genome-wide human cancer data | 2019 | 3 |
| 4 | 2019 | 48 | |
| 5 | 2019 | 80 | |
| 6 | 2018 | 108 | |
| 7 | 2018 | 233 | |
| 8 | Th17 cytokines differentiate obesity from obesity-associated type 2 diabetes and promote TNFα production | 2015 | 38 |
| 9 | 2015 | 1 | |
| 10 | 2015 | 109 | |
| 11 | 2015 | 27 | |
| 12 | 2014 | 57 | |
| 13 | 2014 | 60 | |
| 14 | 2014 | 73 | |
| 15 | 2014 | 2 | |
| 16 | 2014 | 139 | |
| 17 | 2013 | 98 |
About Nicholas A. Cilfone
Nicholas A. Cilfone is a scholar working on Molecular Medicine, Infectious Diseases and Immunology, having authored 17 papers that have together received 1.1k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (6 papers), Atherosclerosis and Cardiovascular Diseases (3 papers), Mycobacterium research and diagnosis (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Pneumonia and Respiratory Infections (2 papers), Computational Drug Discovery Methods (2 papers), Antibiotic Resistance in Bacteria (2 papers) and Immune Cell Function and Interaction (2 papers). The work is most often cited by research in Infectious Diseases (324 citations), Immunology (341 citations) and Epidemiology (286 citations). Nicholas A. Cilfone has collaborated with scholars based in United States and France. Frequent co-authors include Denise E. Kirschner, Jennifer J. Linderman, Joshua T. Mattila, Simeone Marino, JoAnne L. Flynn, Jeffrey R. Gulcher, Thomas W. Chittenden, Javier L. Baylon, Stephanie Evans and Louis R. Joslyn. Their work appears in journals such as The Journal of Experimental Medicine, The Journal of Immunology and PLoS ONE.
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.