Julia Chifman
Impact in
- Genetics top 2%
- Genetic diversity and population structure
- Ecological Modeling top 5%
- Species Distribution and Climate Change
Papers in
-
- Inflammation biomarkers and pathways 2
- Co-authors
- Laura Kubatko (6 shared papers)Paul D. Blischak (1 shared paper)Andrea D. Wolfe (1 shared paper)Reinhard Laubenbacher (5 shared papers)Suzy V. Torti (4 shared papers)Lance D. Miller (7 shared papers)Ashok Pullikuth (7 shared papers)Davide Bedognetti (4 shared papers)
- Journals
- Journal of Theoretical Biology (3 papers)Cancer Research (3 papers)Bioinformatics (2 papers)PLoS Computational Biology (2 papers)Journal of Translational Medicine (1 paper)
- Partner nations
- United StatesNew ZealandQatar
In The Last Decade
Julia Chifman
18 papers receiving 1.7k citations
Julia Chifman's Hit Papers
Peers
Comparison fields: 5 of 109
- Genetics 758
- Ecological Modeling 119
- Paleontology 189
- Ecology, Evolution, Behavior and Systematics 412
- Nature and Landscape Conservation 157
Countries citing papers authored by Julia Chifman
This map shows the geographic impact of Julia Chifman'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 Julia Chifman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Chifman more than expected).
Fields of papers citing papers by Julia Chifman
This network shows the impact of papers produced by Julia Chifman. 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 Julia Chifman. The network helps show where Julia Chifman may publish in the future.
Co-authors
The 25 scholars most cited alongside Julia Chifman, 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 | Quartet Inference from SNP Data Under the Coalescent Model Hit paper breakdown → | 2014 | 873 |
| 2 | 2015 | 198 | |
| 3 | 2018 | 194 | |
| 4 | 2014 | 126 | |
| 5 | 2016 | 78 | |
| 6 | 2016 | 65 | |
| 7 | 2019 | 46 | |
| 8 | 2021 | 25 | |
| 9 | 2012 | 21 | |
| 10 | 2017 | 20 | |
| 11 | 2020 | 11 | |
| 12 | 2022 | 6 | |
| 13 | 2024 | 3 | |
| 14 | 2024 | 2 | |
| 15 | 2022 | 2 | |
| 16 | 2014 | 2 | |
| 17 | 2017 | 1 | |
| 18 | 2018 | 1 | |
| 19 | 2009 | 1 | |
| 20 | 2019 | 0 |
About Julia Chifman
Julia Chifman is a scholar working on Immunology, Molecular Biology, Oncology, Genetics and Pulmonary and Respiratory Medicine, having authored 20 papers that have together received 1.7k indexed citations. Recurring topics across this work include Ferroptosis and cancer prognosis (3 papers), Cancer Immunotherapy and Biomarkers (3 papers), Trace Elements in Health (3 papers), Iron Metabolism and Disorders (3 papers), Cancer Genomics and Diagnostics (2 papers), Inflammation biomarkers and pathways (2 papers), Evolution and Genetic Dynamics (2 papers) and Evolution and Paleontology Studies (2 papers). The work is most often cited by research in Genetics (758 citations), Ecological Modeling (119 citations), Paleontology (189 citations), Ecology, Evolution, Behavior and Systematics (412 citations) and Nature and Landscape Conservation (157 citations). Julia Chifman has collaborated with scholars based in United States, New Zealand and Qatar. Frequent co-authors include Laura Kubatko, Paul D. Blischak, Andrea D. Wolfe, Reinhard Laubenbacher, Suzy V. Torti, Lance D. Miller, Ashok Pullikuth, Davide Bedognetti, Jeff W. Chou and Cristin G. Print. Their work appears in journals such as Journal of Theoretical Biology, Cancer Research, Bioinformatics, PLoS Computational Biology and Journal of Translational Medicine.
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.