Johan Hartman

11.5k total citations · 2 hit papers
113 papers, 6.7k citations indexed

About

Johan Hartman is a scholar working on Cancer Research, Oncology and Molecular Biology. According to data from OpenAlex, Johan Hartman has authored 113 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Cancer Research, 53 papers in Oncology and 44 papers in Molecular Biology. Recurrent topics in Johan Hartman's work include Breast Cancer Treatment Studies (27 papers), Cancer Genomics and Diagnostics (24 papers) and Estrogen and related hormone effects (21 papers). Johan Hartman is often cited by papers focused on Breast Cancer Treatment Studies (27 papers), Cancer Genomics and Diagnostics (24 papers) and Estrogen and related hormone effects (21 papers). Johan Hartman collaborates with scholars based in Sweden, United States and Finland. Johan Hartman's co-authors include Anders Ström, Jan-Ακε Gustafsson, Mattias Rantalainen, Balázs Ács, Jonas Bergh, Sandra Andersson, Jason Matthews, Margaret Warner, Guojun Cheng and Eckardt Treuter and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Johan Hartman

101 papers receiving 6.6k 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.

Estrogen Receptors: How Do They Signal and What Are Their Targets

2007 1.4k citations Johan Hartman, Anders Ström et al. profile →
Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing

2018 699 citations Johan Hartman, Nicola Crosetto et al. profile →

Peers

Johan Hartman

ONCOL

GENET

RNMI

Takanori Ishida Japan

Suzanne D. Conzen United States

Dilip D. Giri United States

Yudong D. He United States

Angelo Paradiso Italy

Shridar Ganesan United States

Graham Ball United Kingdom

Sampsa Hautaniemi Finland

Janine Salter United Kingdom

Els M.J.J. Berns Netherlands

Takanori Ishida Japan

Johan Hartman

2.0k ×0.8

2.3k ×0.9

ONCOL

1.1k ×0.6

GENET

1.8k ×1.0

746 ×0.9

RNMI

Citations per year, relative to Johan Hartman Johan Hartman (= 1×) peers Takanori Ishida

Countries citing papers authored by Johan Hartman

Since Specialization

Citations

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

Fields of papers citing papers by Johan Hartman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johan Hartman

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

All Works

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20 of 20 papers shown

Sifakis, Emmanouil G., et al.. (2025). Transcriptomic profiles of endocrine-resistant breast cancer. BMC Cancer. 25(1). 1556–1556.

Ács, Balázs, Johan Hartman, Irma Fredriksson, et al.. (2024). Immune cell infiltrate in ductal carcinoma in situ and the risk of dying from breast cancer: case–control study. British journal of surgery. 111(2). 2 indexed citations

Tsiknakis, Nikos, Georgios C. Manikis, Kang Wang, et al.. (2024). Unveiling the Power of Model-Agnostic Multiscale Analysis for Enhancing Artificial Intelligence Models in Breast Cancer Histopathology Images. IEEE Journal of Biomedical and Health Informatics. 28(9). 5312–5322. 3 indexed citations

Tsiknakis, Nikos, Johan Staaf, Ana Bosch, et al.. (2024). The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?. EClinicalMedicine. 78. 102928–102928. 6 indexed citations

Wang, Yinxi, Wenwen Sun, Emelié Karlsson, et al.. (2024). Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay. Breast Cancer Research and Treatment. 206(1). 163–175. 4 indexed citations

Marchi, Tommaso De, Anna Ehinger, Johan Hartman, et al.. (2023). Comparison of SP142 and 22C3 PD-L1 assays in a population-based cohort of triple-negative breast cancer patients in the context of their clinically established scoring algorithms. Breast Cancer Research. 25(1). 123–123. 14 indexed citations

Collodet, Caterina, et al.. (2023). Development and characterization of a recombinant silk network for 3D culture of immortalized and fresh tumor‐derived breast cancer cells. Bioengineering & Translational Medicine. 8(5). e10537–e10537. 6 indexed citations

Engblom, Camilla, Kim Thrane, Alma Andersson, et al.. (2023). Spatial transcriptomics of B cell and T cell receptors reveals lymphocyte clonal dynamics. Science. 382(6675). eadf8486–eadf8486. 59 indexed citations

Bai, Yalai, Kimberly Cole, Sandra Martínez-Morilla, et al.. (2021). An Open-Source, Automated Tumor-Infiltrating Lymphocyte Algorithm for Prognosis in Triple-Negative Breast Cancer. Clinical Cancer Research. 27(20). 5557–5565. 38 indexed citations

10.

Wang, Yinxi, Kimmo Kartasalo, Balázs Ács, et al.. (2021). Predicting Molecular Phenotypes from Histopathology Images: A Transcriptome-Wide Expression–Morphology Analysis in Breast Cancer. Cancer Research. 81(19). 5115–5126. 41 indexed citations

11.

Stantic, Marina, et al.. (2021). TAp73 represses NF-κB–mediated recruitment of tumor-associated macrophages in breast cancer. Proceedings of the National Academy of Sciences. 118(10). 31 indexed citations

12.

Peuget, Sylvain, Jiawei Zhu, Gema Sanz, et al.. (2020). Thermal Proteome Profiling Identifies Oxidative-Dependent Inhibition of the Transcription of Major Oncogenes as a New Therapeutic Mechanism for Select Anticancer Compounds. Cancer Research. 80(7). 1538–1550. 14 indexed citations

13.

Zhang, Xiaolu, Silvano Garnerone, Marcin Nicoś, et al.. (2019). CUTseq is a versatile method for preparing multiplexed DNA sequencing libraries from low-input samples. Nature Communications. 10(1). 4732–4732. 8 indexed citations

14.

Robertson, Stephanie, et al.. (2019). Re-testing of predictive biomarkers on surgical breast cancer specimens is clinically relevant. Breast Cancer Research and Treatment. 174(3). 795–805. 35 indexed citations

15.

Zhang, Yunjian, Sharon Lim, Kayoko Hosaka, et al.. (2017). A Zebrafish Model Discovers a Novel Mechanism of Stromal Fibroblast-Mediated Cancer Metastasis. Clinical Cancer Research. 23(16). 4769–4779. 66 indexed citations

16.

Li, Jingmei, Emma Ivansson, Daniel Klevebring, et al.. (2016). Molecular Differences between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes. Clinical Cancer Research. 23(10). 2584–2592. 15 indexed citations

17.

Bartish, Margarita, Jeanette Östling, Artur Mezheyeuski, et al.. (2016). Guidance Molecule SEMA3A Restricts Tumor Growth by Differentially Regulating the Proliferation of Tumor-Associated Macrophages. Cancer Research. 76(11). 3166–3178. 46 indexed citations

18.

Wang, Jian, Ziquan Cao, Xing‐Mei Zhang, et al.. (2014). Novel Mechanism of Macrophage-Mediated Metastasis Revealed in a Zebrafish Model of Tumor Development. Cancer Research. 75(2). 306–315. 113 indexed citations

19.

Hartman, Johan, Karin Edvardsson, Karolina Lindberg, et al.. (2009). Tumor Repressive Functions of Estrogen Receptor β in SW480 Colon Cancer Cells. Cancer Research. 69(15). 6100–6106. 172 indexed citations

20.

Hartman, Johan, Patrick Müller, James S. Foster, et al.. (2004). HES-1 inhibits 17β-estradiol and heregulin-β1-mediated upregulation of E2F-1. Oncogene. 23(54). 8826–8833. 52 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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