Erika Mehl

2.7k total citations · 1 hit paper
8 papers, 1.5k citations indexed

About

Erika Mehl is a scholar working on Reproductive Medicine, Cancer Research and Molecular Biology. According to data from OpenAlex, Erika Mehl has authored 8 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Reproductive Medicine, 3 papers in Cancer Research and 2 papers in Molecular Biology. Recurrent topics in Erika Mehl's work include Ovarian cancer diagnosis and treatment (5 papers), Breast Cancer Treatment Studies (2 papers) and Endometrial and Cervical Cancer Treatments (2 papers). Erika Mehl is often cited by papers focused on Ovarian cancer diagnosis and treatment (5 papers), Breast Cancer Treatment Studies (2 papers) and Endometrial and Cervical Cancer Treatments (2 papers). Erika Mehl collaborates with scholars based in Canada, United States and Germany. Erika Mehl's co-authors include Samuel Leung, C. Blake Gilks, Steve E. Kalloger, Martin Köbel, David G. Huntsman, Ashish Rajput, Torsten O. Nielsen, Jennifer L. Santos, Steven McKinney and Leah Prentice and has published in prestigious journals such as JNCI Journal of the National Cancer Institute, PLoS Medicine and BMC Medicine.

In The Last Decade

Erika Mehl

8 papers receiving 1.4k citations

Hit Papers

Ovarian Carcinoma Subtype... 2008 2026 2014 2020 2008 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erika Mehl Canada 8 585 570 513 508 222 8 1.5k
Brant G. Wang United States 14 432 0.7× 637 1.1× 434 0.8× 625 1.2× 316 1.4× 43 1.5k
Boris Winterhoff United States 21 418 0.7× 554 1.0× 462 0.9× 749 1.5× 138 0.6× 56 1.5k
Tomás Bonome United States 15 643 1.1× 731 1.3× 457 0.9× 1.2k 2.4× 211 1.0× 23 2.0k
Elisabeth Wik Norway 23 382 0.7× 378 0.7× 401 0.8× 584 1.1× 140 0.6× 60 1.5k
Nadia Traficante Australia 8 499 0.9× 611 1.1× 466 0.9× 899 1.8× 109 0.5× 12 1.6k
Daryl Johnson Australia 3 408 0.7× 493 0.9× 331 0.6× 527 1.0× 98 0.4× 4 1.3k
Jennifer L. Santos Canada 13 527 0.9× 1.3k 2.2× 416 0.8× 809 1.6× 180 0.8× 21 2.0k
Susanna L. Cooke United Kingdom 16 481 0.8× 337 0.6× 473 0.9× 583 1.1× 364 1.6× 21 1.3k
Stefanie Avril United States 22 418 0.7× 264 0.5× 801 1.6× 649 1.3× 126 0.6× 45 1.7k
Bianca Locandro Australia 2 430 0.7× 538 0.9× 346 0.7× 568 1.1× 106 0.5× 2 1.1k

Countries citing papers authored by Erika Mehl

Since Specialization
Citations

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

Fields of papers citing papers by Erika Mehl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Erika Mehl

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

All Works

8 of 8 papers shown
1.
Polley, Mei‐Yin C., Samuel Leung, Lisa M. McShane, et al.. (2013). An International Ki67 Reproducibility Study. JNCI Journal of the National Cancer Institute. 105(24). 1897–1906. 429 indexed citations
2.
Tabrizi, Ali Dastranj, Steve E. Kalloger, Martin Köbel, et al.. (2010). Primary Ovarian Mucinous Carcinoma of Intestinal Type: Significance of Pattern of Invasion and Immunohistochemical Expression Profile in a Series of 31 Cases. International Journal of Gynecological Pathology. 29(2). 99–107. 63 indexed citations
3.
Kalloger, Steve E., Martin Köbel, Samuel Leung, et al.. (2010). Calculator for ovarian carcinoma subtype prediction. Modern Pathology. 24(4). 512–521. 68 indexed citations
4.
Liu, Shuzhen, Stephen Chia, Erika Mehl, et al.. (2009). Progesterone receptor is a significant factor associated with clinical outcomes and effect of adjuvant tamoxifen therapy in breast cancer patients. Breast Cancer Research and Treatment. 119(1). 53–61. 93 indexed citations
5.
Köbel, Martin, Haodong Xu, Patricia Bourne, et al.. (2009). IGF2BP3 (IMP3) expression is a marker of unfavorable prognosis in ovarian carcinoma of clear cell subtype. Modern Pathology. 22(3). 469–475. 110 indexed citations
6.
Cheng, Hongwei, Erika Mehl, Shuzhen Liu, et al.. (2009). Validation of immature adipogenic status and identification of prognostic biomarkers in myxoid liposarcoma using tissue microarrays. Human Pathology. 40(9). 1244–1251. 39 indexed citations
7.
Köbel, Martin, Steve E. Kalloger, Niki Boyd, et al.. (2008). Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies. PLoS Medicine. 5(12). e232–e232. 618 indexed citations breakdown →
8.
Prentice, Leah, Christian Klausen, Steve E. Kalloger, et al.. (2007). Kisspeptin and GPR54 immunoreactivity in a cohort of 518 patients defines favourable prognosis and clear cell subtype in ovarian carcinoma. BMC Medicine. 5(1). 33–33. 51 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026