C. Moeder

768 total citations
9 papers, 584 citations indexed

About

C. Moeder is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, C. Moeder has authored 9 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Oncology and 3 papers in Cancer Research. Recurrent topics in C. Moeder's work include HER2/EGFR in Cancer Research (4 papers), Advanced Biosensing Techniques and Applications (3 papers) and Breast Cancer Treatment Studies (3 papers). C. Moeder is often cited by papers focused on HER2/EGFR in Cancer Research (4 papers), Advanced Biosensing Techniques and Applications (3 papers) and Breast Cancer Treatment Studies (3 papers). C. Moeder collaborates with scholars based in United States, Canada and France. C. Moeder's co-authors include David L. Rimm, Jennifer M. Giltnane, Robert L. Camp, Harriet M. Kluger, Yuval Kluger, Elah Pick, Malini Harigopal, Andrew Robinson, Annette M. Molinaro and Karen Gelmon and has published in prestigious journals such as Journal of Clinical Oncology, Cancer and Cancer Research.

In The Last Decade

C. Moeder

9 papers receiving 575 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
C. Moeder United States	8	393	225	114	111	68	9	584
Hannah Linden United States	5	300 0.8×	220 1.0×	53 0.5×	58 0.5×	41 0.6×	12	457
John D. Bentley Australia	14	620 1.6×	140 0.6×	126 1.1×	83 0.7×	50 0.7×	19	788
Maria Quanz France	10	391 1.0×	160 0.7×	54 0.5×	139 1.3×	67 1.0×	12	506
Kelly L. Slocum United States	7	405 1.0×	121 0.5×	40 0.4×	194 1.7×	44 0.6×	10	560
Nataly Kravchenko‐Balasha Israel	16	421 1.1×	154 0.7×	19 0.2×	117 1.1×	73 1.1×	38	648
Sonnet J.H. Arlander United States	9	713 1.8×	243 1.1×	25 0.2×	99 0.9×	120 1.8×	9	765
Beth Cooper United States	6	504 1.3×	122 0.5×	31 0.3×	68 0.6×	201 3.0×	6	818
Jon Travers United Kingdom	9	501 1.3×	270 1.2×	17 0.1×	80 0.7×	53 0.8×	23	659
Roberto Bitton United States	9	427 1.1×	107 0.5×	96 0.8×	36 0.3×	68 1.0×	10	556
Virginia Morello Italy	9	400 1.0×	120 0.5×	54 0.5×	151 1.4×	120 1.8×	12	605

Countries citing papers authored by C. Moeder

Since Specialization

Citations

This map shows the geographic impact of C. Moeder'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 C. Moeder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Moeder more than expected).

Fields of papers citing papers by C. Moeder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. Moeder. 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 C. Moeder. The network helps show where C. Moeder may publish in the future.

Co-authorship network of co-authors of C. Moeder

This figure shows the co-authorship network connecting the top 25 collaborators of C. Moeder. A scholar is included among the top collaborators of C. Moeder 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 C. Moeder. C. Moeder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

André, Fabrice, Rosa Conforti, C. Moeder, et al.. (2012). Association between the nuclear to cytoplasmic ratio of p27 and the efficacy of adjuvant polychemotherapy in early breast cancer. Annals of Oncology. 23(8). 2059–2064. 10 indexed citations

Welsh, Allison W., C. Moeder, Peter Gershkovich, et al.. (2011). Standardization of Estrogen Receptor Measurement in Breast Cancer Suggests False-Negative Results Are a Function of Threshold Intensity Rather Than Percentage of Positive Cells. Journal of Clinical Oncology. 29(22). 2978–2984. 60 indexed citations

Giltnane, Jennifer M., C. Moeder, Robert L. Camp, & David L. Rimm. (2009). Quantitative multiplexed analysis of ErbB family coexpression for primary breast cancer prognosis in a large retrospective cohort. Cancer. 115(11). 2400–2409. 42 indexed citations

Moeder, C., et al.. (2009). Quantitative, Fluorescence-Based In-Situ Assessment of Protein Expression. Methods in molecular biology. 520. 163–175. 30 indexed citations

Giltnane, Jennifer M., C. Moeder, Robert L. Camp, et al.. (2009). Construction of a five-marker protein-based model for stage-independent assessment of prognosis in breast cancer. Journal of Clinical Oncology. 27(15_suppl). 11013–11013. 1 indexed citations

Nadler, Yasmine, Robert L. Camp, Jennifer M. Giltnane, et al.. (2008). Expression patterns and prognostic value of Bag-1 and Bcl-2 in breast cancer. Breast Cancer Research. 10(2). R35–R35. 55 indexed citations

Rothberg, Bonnie E. Gould, C. Moeder, Harriet M. Kluger, et al.. (2008). Nuclear to non-nuclear Pmel17/gp100 expression (HMB45 staining) as a discriminator between benign and malignant melanocytic lesions. Modern Pathology. 21(9). 1121–1129. 25 indexed citations

Moeder, C., Jennifer M. Giltnane, Malini Harigopal, et al.. (2007). Quantitative Justification of the Change From 10% to 30% for Human Epidermal Growth Factor Receptor 2 Scoring in the American Society of Clinical Oncology/College of American Pathologists Guidelines: Tumor Heterogeneity in Breast Cancer and Its Implications for Tissue Microarray–Based Assessment of Outcome. Journal of Clinical Oncology. 25(34). 5418–5425. 95 indexed citations

Pick, Elah, Yuval Kluger, Jennifer M. Giltnane, et al.. (2007). High HSP90 Expression Is Associated with Decreased Survival in Breast Cancer. Cancer Research. 67(7). 2932–2937. 266 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.

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