Cheryl Gillet

1.5k total citations · 1 hit paper
6 papers, 1.0k citations indexed

About

Cheryl Gillet is a scholar working on Molecular Biology, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Cheryl Gillet has authored 6 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in Oncology and 1 paper in Pathology and Forensic Medicine. Recurrent topics in Cheryl Gillet's work include Gene expression and cancer classification (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Advanced Breast Cancer Therapies (1 paper). Cheryl Gillet is often cited by papers focused on Gene expression and cancer classification (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Advanced Breast Cancer Therapies (1 paper). Cheryl Gillet collaborates with scholars based in United Kingdom, Belgium and Switzerland. Cheryl Gillet's co-authors include Gianluca Bontempi, Mauro Delorenzi, Martine Piccart, Christos Sotiriou, Benjamin Haibe‐Kains, Françoise Lallemand, Sherene Loi, John A. Foekens, Peter Ellis and Christine Desmedt and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and BMC Genomics.

In The Last Decade

Cheryl Gillet

6 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

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.

Definition of Clinically Distinct Molecular Subtypes in Estrogen Receptor–Positive Breast Carcinomas Through Genomic Grade

2007 599 citations Sherene Loi, Benjamin Haibe‐Kains et al. Journal of Clinical Oncology profile →

Peers

Countries citing papers authored by Cheryl Gillet

Since Specialization

Citations

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

Fields of papers citing papers by Cheryl Gillet

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheryl Gillet

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

All Works

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6 of 6 papers shown

#	Work	Indexed citations
1	Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentation 2022 ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Fangfang Liu, Cheryl Gillet, Swapnil Rane, Anita Grigoriadis, Amit Sethi	4
2	Use of Raman Spectroscopy in Characterizing Formalin-Fixed, Paraffin-Embedded Breast Tumor Samples (abstract) 2009 ·AIP conference proceedings ·(unknown), Nicholas I. Cade, (unknown), (unknown), Cheryl Gillet, David Richards, Frederic Festy, Beverly Karplus Hartline, (unknown), (unknown)	2
3	PIK3CA mutation-associated gene expression signature correlates with deactivation of the PI3K pathway and predicts benefit to endocrine therapy in high-risk ER+ (luminal B) breast cancers (BC). 2009 ·Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) ·Christos Sotiriou, Sherene Loi, Benjamin Haibe‐Kains, Françoise Lallemand, Lajos Pusztai, (unknown), Philippe L. Bédard, Cheryl Gillet, Peter Ellis, Wayne A. Phillips, Martine Piccart, Grant A. McArthur	1
4	Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen 2008 ·BMC Genomics ·Sherene Loi, Benjamin Haibe‐Kains, Christine Desmedt, Pratyaksha Wirapati, Françoise Lallemand, (unknown), Cheryl Gillet, Peter Ellis, K W Ryder, James F. Reid, Maria Grazia Daidone, Marco A. Pierotti, Els M.J.J. Berns, Maurice P.H.M. Jansen, John A. Foekens, Mauro Delorenzi, Gianluca Bontempi, Martine Piccart, Christos Sotiriou	281
5	Definition of Clinically Distinct Molecular Subtypes in Estrogen Receptor–Positive Breast Carcinomas Through Genomic Grade breakdown → 2007 ·Journal of Clinical Oncology ·Sherene Loi, Benjamin Haibe‐Kains, Christine Desmedt, Françoise Lallemand, (unknown), Cheryl Gillet, Peter Ellis, Adrian L. Harris, Jonas Bergh, John A. Foekens, Jan G.M. Klijn, Denis Larsimont, Marc Buyse, Gianluca Bontempi, Mauro Delorenzi, Martine Piccart, Christos Sotiriou	599
6	APC mutations are sufficient for the growth of early colorectal adenomas 2000 ·Proceedings of the National Academy of Sciences ·Hanan Lamlum, (unknown), Mohammad Ilyas, Andrew Rowan, Cheryl Gillet, Andrew M. Hanby, Ian Talbot, Walter F. Bodmer, Ian Tomlinson	134

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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