Amy M.B. McCorry

632 total citations
7 papers, 192 citations indexed

About

Amy M.B. McCorry is a scholar working on Oncology, Pathology and Forensic Medicine and Molecular Biology. According to data from OpenAlex, Amy M.B. McCorry has authored 7 papers receiving a total of 192 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 4 papers in Pathology and Forensic Medicine and 2 papers in Molecular Biology. Recurrent topics in Amy M.B. McCorry's work include Genetic factors in colorectal cancer (4 papers), Colorectal Cancer Treatments and Studies (4 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Amy M.B. McCorry is often cited by papers focused on Genetic factors in colorectal cancer (4 papers), Colorectal Cancer Treatments and Studies (4 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Amy M.B. McCorry collaborates with scholars based in United Kingdom, Italy and Bangladesh. Amy M.B. McCorry's co-authors include Philip D. Dunne, Mark Lawler, Maurice B. Loughrey, Daniel B. Longley, Susan D. Richman, Darragh G. McArt, Tim Maughan, Jacqueline A. James, Manuel Salto‐Tellez and Peter W. Hamilton and has published in prestigious journals such as Nature Communications, Cancer Research and The Journal of Pathology.

In The Last Decade

Amy M.B. McCorry

7 papers receiving 192 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Amy M.B. McCorry United Kingdom	6	134	66	57	57	31	7	192
Ivan Jelas Germany	8	134 1.0×	44 0.7×	43 0.8×	38 0.7×	33 1.1×	22	200
Clarissa Filorizzo Italy	9	110 0.8×	66 1.0×	110 1.9×	61 1.1×	26 0.8×	16	294
Hazem Khout United Kingdom	9	108 0.8×	38 0.6×	43 0.8×	85 1.5×	24 0.8×	21	222
Olivia L. Snir United States	7	66 0.5×	48 0.7×	76 1.3×	45 0.8×	37 1.2×	11	249
Mark D. McKee United States	7	137 1.0×	47 0.7×	80 1.4×	107 1.9×	39 1.3×	9	259
Ann Christina Eriksen Denmark	7	152 1.1×	80 1.2×	110 1.9×	103 1.8×	35 1.1×	9	283
Zorka Inić Serbia	5	92 0.7×	24 0.4×	55 1.0×	69 1.2×	29 0.9×	16	183
Sofie Palmans Belgium	5	250 1.9×	118 1.8×	62 1.1×	71 1.2×	53 1.7×	9	325
Ji‐Hye Oh South Korea	9	92 0.7×	28 0.4×	91 1.6×	72 1.3×	59 1.9×	14	220
Xavier Andreu Spain	10	84 0.6×	54 0.8×	49 0.9×	78 1.4×	45 1.5×	20	210

Countries citing papers authored by Amy M.B. McCorry

Since Specialization

Citations

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

Fields of papers citing papers by Amy M.B. McCorry

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amy M.B. McCorry. 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 Amy M.B. McCorry. The network helps show where Amy M.B. McCorry may publish in the future.

Co-authorship network of co-authors of Amy M.B. McCorry

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

All Works

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7 of 7 papers shown

McCorry, Amy M.B., Keara L. Redmond, Victoria Bingham, et al.. (2019). Fibroblast-derived Gremlin1 localises to epithelial cells at the base of the intestinal crypt. Oncotarget. 10(45). 4630–4639. 14 indexed citations

McCorry, Amy M.B., Maurice B. Loughrey, Daniel B. Longley, Mark Lawler, & Philip D. Dunne. (2018). Epithelial‐to‐mesenchymal transition signature assessment in colorectal cancer quantifies tumour stromal content rather than true transition. The Journal of Pathology. 246(4). 422–426. 18 indexed citations

Loughrey, Maurice B., Peter Bankhead, Helen G. Coleman, et al.. (2018). Validation of the systematic scoring of immunohistochemically stained tumour tissue microarrays using QuPath digital image analysis. Histopathology. 73(2). 327–338. 59 indexed citations

Richman, Susan D., Simon Gollins, Peter Stewart, et al.. (2018). Prospective patient stratification into robust cancer‐cell intrinsic subtypes from colorectal cancer biopsies. The Journal of Pathology. 245(1). 19–28. 40 indexed citations

Dunne, Philip D., Helen G. Coleman, Peter Bankhead, et al.. (2018). Bcl-xL as a poor prognostic biomarker and predictor of response to adjuvant chemotherapy specifically in BRAF -mutant stage II and III colon cancer. Oncotarget. 9(17). 13834–13847. 7 indexed citations

Richman, Susan D., Simon Gollins, Peter Stewart, et al.. (2018). Abstract 5365: Prospective patient stratification into robust cancer-cell intrinsic subtypes from colorectal cancer biopsies. Cancer Research. 78(13_Supplement). 5365–5365. 1 indexed citations

Dunne, Philip D., Paul G. O’Reilly, Amy M.B. McCorry, et al.. (2017). Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification. Nature Communications. 8(1). 15657–15657. 53 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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