Molecular classification of human carcinomas by use of gene expression signatures.
Impact in
- Oncology 124
Classified as
- Journal
- PubMed
In The Last Decade
doi.org/w85558726 →Countries where authors are citing Molecular classification of human carcinomas by use of gene expression signatures.
This map shows the geographic impact of Molecular classification of human carcinomas by use of gene expression signatures.. 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 Molecular classification of human carcinomas by use of gene expression signatures. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Molecular classification of human carcinomas by use of gene expression signatures. more than expected).
Fields of papers citing Molecular classification of human carcinomas by use of gene expression signatures.
This network shows the impact of Molecular classification of human carcinomas by use of gene expression signatures.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Molecular classification of human carcinomas by use of gene expression signatures..
About Molecular classification of human carcinomas by use of gene expression signatures.
This paper, published in 2001, received 506 indexed citations . Written by Andrew I. Su, John Welsh, Lisa M. Sapinoso, S Kern, Hilmar Lapp, Peter G. Schultz, Steven M. Powell, Christopher A. Moskaluk, Henry F. Frierson and Garret M. Hampton covering the research area of Molecular Biology and Cancer Research. It is primarily cited by scholars working on Molecular Biology (347 citations), Oncology (124 citations), Artificial Intelligence (84 citations), Pathology and Forensic Medicine (68 citations) and Cancer Research (67 citations). Published in PubMed.
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.
This paper is also available at doi.org/w85558726.