Jane Estell

2.3k citations
16 papers · 216 · h-index 7

Impact in

  • Hematology top 5%
    • Multiple Myeloma Research and Treatments
    • Peptidase Inhibition and Analysis
    • CAR-T cell therapy research

Papers in

    • Multiple Myeloma Research and Treatments 9
    • CAR-T cell therapy research 2

Jane Estell

16 papers receiving 209 citations

Peers

Jane Estell
Comparison fields: 5 of 28
  • Hematology 169
  • Oncology 91
  • Genetics 22
  • Molecular Biology 96
  • Physiology 6
Replace Pia Sondergeld with:
Pia Sondergeld Germany
Wolney Barreto Brazil
Francesca Bonello Italy
Joan Bladé Spain
Katarina Uttervall Sweden
Laura Moreno Spain
Engin Gul Canada
Laura Rosiñol Spain
Sonia Morè Italy
Sunil Gandhi United States
Jane Estell relative to Pia Sondergeld Germany Pia Sondergeld's profile →
Citations per field
00.5×6.3×
Pia Sondergeld · 1×
Citations per year

Countries citing papers authored by Jane Estell

Since Specialization
Citations

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

Fields of papers citing papers by Jane Estell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jane Estell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jane Estell Line = papers co-authored together Jane Estell links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201997
2 201629
3 201926
4 202316
5 202110
6 20108
7 20188
8 20166
9 20166
10 20214
11 20201
12 20141
13 20081
14 20211
15 20081
16 20221

About Jane Estell

Jane Estell is a scholar working on Hematology, Oncology, Organic Chemistry, Pathology and Forensic Medicine and Molecular Biology, having authored 16 papers that have together received 216 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (9 papers), Lymphoma Diagnosis and Treatment (2 papers), Ovarian cancer diagnosis and treatment (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Synthesis and Biological Evaluation (2 papers), CAR-T cell therapy research (2 papers), Cancer Mechanisms and Therapy (1 paper) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Hematology (169 citations), Oncology (91 citations), Genetics (22 citations), Molecular Biology (96 citations) and Physiology (6 citations). Jane Estell has collaborated with scholars based in Australia, United States and Belgium. Frequent co-authors include Wolney Barreto, Ajay K. Nooka, María‐Victoria Mateos, Paolo Corradini, Eva Medvedova, Xiang Qin, Vânia Hungria, Himal Amin, Katja Weisel and Jordan M. Schecter. Their work appears in journals such as Blood, British Journal of Haematology, American Journal of Hematology, Haematologica and Journal of Clinical Oncology.

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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