Heidi J. Sofia
Impact in
- Cancer Research top 0.01%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- Oncology top 0.05%
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Cancer Genomics and Diagnostics 41
- Genetics 17
- Genomic variations and chromosomal abnormalities 8
- Bacterial Genetics and Biotechnology 7
- Co-authors
- Heinz Körner (1 shared paper)Walter G. Zumft (1 shared paper)Donna L. Daniels (3 shared papers)Guy Plunkett (3 shared papers)Valerie Burland (3 shared papers)Frederick R. Blattner (1 shared paper)Luke E. Ulrich (1 shared paper)Thorsten Mascher (1 shared paper)
- Journals
- Nature (17 papers)Cell (17 papers)Cell Reports (15 papers)Cancer Cell (13 papers)Nature Communications (11 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Heidi J. Sofia
118 papers receiving 80.2k citations
Heidi J. Sofia's Hit Papers
Peers
Comparison fields: 5 of 178
- Cancer Research 18.2k
- Oncology 16.6k
- Genetics 5.2k
- Pulmonary and Respiratory Medicine 14.1k
- Molecular Biology 21.7k
Countries citing papers authored by Heidi J. Sofia
This map shows the geographic impact of Heidi J. Sofia'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 Heidi J. Sofia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heidi J. Sofia more than expected).
Fields of papers citing papers by Heidi J. Sofia
This network shows the impact of papers produced by Heidi J. Sofia. 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 Heidi J. Sofia. The network helps show where Heidi J. Sofia may publish in the future.
Co-authors
The 25 scholars most cited alongside Heidi J. Sofia, 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 119 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comprehensive molecular characterization of gastric adenocarcinoma Hit paper breakdown → | 2014 | 5244 |
| 2 | Comprehensive molecular profiling of lung adenocarcinoma Hit paper breakdown → | 2014 | 4597 |
| 3 | The Immune Landscape of Cancer Hit paper breakdown → | 2018 | 4385 |
| 4 | The Somatic Genomic Landscape of Glioblastoma Hit paper breakdown → | 2013 | 4012 |
| 5 | Comprehensive genomic characterization of squamous cell lung cancers Hit paper breakdown → | 2012 | 3326 |
| 6 | Comprehensive molecular characterization of clear cell renal cell carcinoma Hit paper breakdown → | 2013 | 2853 |
| 7 | An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Hit paper breakdown → | 2018 | 2633 |
| 8 | Genomic Classification of Cutaneous Melanoma Hit paper breakdown → | 2015 | 2540 |
| 9 | The Molecular Taxonomy of Primary Prostate Cancer Hit paper breakdown → | 2015 | 2464 |
| 10 | Integrated Genomic Characterization of Papillary Thyroid Carcinoma Hit paper breakdown → | 2014 | 2459 |
| 11 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2401 |
| 12 | Oncogenic Signaling Pathways in The Cancer Genome Atlas Hit paper breakdown → | 2018 | 2371 |
| 13 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2169 |
| 14 | Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma Hit paper breakdown → | 2017 | 1989 |
| 15 | Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer Hit paper breakdown → | 2017 | 1951 |
| 16 | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hit paper breakdown → | 2018 | 1758 |
| 17 | Comprehensive Characterization of Cancer Driver Genes and Mutations Hit paper breakdown → | 2018 | 1748 |
| 18 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Hit paper breakdown → | 2016 | 1659 |
| 19 | Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Hit paper breakdown → | 2018 | 1634 |
| 20 | Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma Hit paper breakdown → | 2017 | 1585 |
About Heidi J. Sofia
Heidi J. Sofia is a scholar working on Cancer Research, Genetics, Molecular Biology, Information Systems and Management and Pulmonary and Respiratory Medicine, having authored 119 papers that have together received 81.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (41 papers), Genomic variations and chromosomal abnormalities (8 papers), Bacterial Genetics and Biotechnology (7 papers), Scientific Computing and Data Management (6 papers), Genomics and Phylogenetic Studies (6 papers), Bioinformatics and Genomic Networks (5 papers), Privacy-Preserving Technologies in Data (4 papers) and Chromatin Remodeling and Cancer (4 papers). The work is most often cited by research in Cancer Research (18.2k citations), Oncology (16.6k citations), Genetics (5.2k citations), Pulmonary and Respiratory Medicine (14.1k citations) and Molecular Biology (21.7k citations). Heidi J. Sofia has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Heinz Körner, Walter G. Zumft, Donna L. Daniels, Guy Plunkett, Valerie Burland, Frederick R. Blattner, Luke E. Ulrich, Thorsten Mascher, Anna Staroń and Sascha Dietrich. Their work appears in journals such as Nature, Cell, Cell Reports, Cancer Cell and Nature Communications.
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.