Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis
20072.3k citationsJavier A. Menéndez, Ruth Lupuprofile →
Reciprocal interactions between β1-integrin and epidermal growth factor receptor in three-dimensional basement membrane breast cultures: A different perspective in epithelial biology
This map shows the geographic impact of Ruth Lupu'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 Ruth Lupu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruth Lupu more than expected).
This network shows the impact of papers produced by Ruth Lupu. 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 Ruth Lupu. The network helps show where Ruth Lupu may publish in the future.
Co-authorship network of co-authors of Ruth Lupu
This figure shows the co-authorship network connecting the top 25 collaborators of Ruth Lupu.
A scholar is included among the top collaborators of Ruth Lupu based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Ruth Lupu. Ruth Lupu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Li, Binghui, et al.. (2007). Inhibition of fatty acid synthase induces reactive oxygen species (ROS) to inhibit HER2 overexpressing breast cancer cell growth. Cancer Research. 67. 4462–4462.1 indexed citations
10.
Menéndez, Javier A., Gershon Y. Locker, & Ruth Lupu. (2005). Regulation of Fatty Acid Synthase (FAS) gene expression by Peroxisome Proliferator-activated receptor-gamma (PPARγ) is dependent of Her-2/neu (erbB-2) signaling in breast cancer cells. Cancer Research. 65. 877–877.3 indexed citations
11.
Menéndez, Javier A., et al.. (2005). In support of Fatty Acid Synthase (FAS) as a metabolic oncogene in breast cancer: Extracellular acidosis acts in an epigenetic fashion activating Fatty Acid Synthase (FAS) gene expression in non-cancerous human breast epithelial MCF10A and breast cancer MCF-7 cells. Cancer Research. 65. 655–655.1 indexed citations
Tang, Careen K., et al.. (1996). Involvement of heregulin-beta2 in the acquisition of the hormone-independent phenotype of breast cancer cells.. PubMed. 56(14). 3350–8.103 indexed citations
16.
Ávila, Matías A., et al.. (1995). Hyperactive autocrine loop mediated by a NDF-related factor in neoplastic hamster embryo fibroblasts expressing an activated cph oncogene.. PubMed. 10(5). 963–71.21 indexed citations
17.
Bacus, S S, Andrei V. Gudkov, C R Zelnick, et al.. (1993). Neu differentiation factor (heregulin) induces expression of intercellular adhesion molecule 1: implications for mammary tumors.. PubMed. 53(21). 5251–61.92 indexed citations
18.
Noguchi, Masayuki, Masaaki Murakami, William P. Bennett, et al.. (1993). Biological consequences of overexpression of a transfected c-erbB-2 gene in immortalized human bronchial epithelial cells.. PubMed. 53(9). 2035–43.42 indexed citations
19.
Pérez, Caridad N., et al.. (1993). Characterization and cloning of the gp30 ligand for the erbB-2 receptor, from human breast cancer cells. 34. 97.1 indexed citations
20.
Bacus, S S, Eliezer Huberman, D Chin, et al.. (1992). A ligand for the erbB-2 oncogene product (gp30) induces differentiation of human breast cancer cells.. PubMed. 3(7). 401–11.83 indexed citations
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.