Dimple Chakravarty

14.8k citations
31 papers · 1.0k · h-index 16

Impact in

    • Cancer Genomics and Diagnostics
    • Cancer-related molecular mechanisms research
    • Cancer, Lipids, and Metabolism
  • Genetics top 5%
    • Estrogen and related hormone effects

Papers in

    • Estrogen and related hormone effects 14
    • HER2/EGFR in Cancer Research 4
    • COVID-19 and healthcare impacts 3
    • Cytokine Signaling Pathways and Interactions 2

Dimple Chakravarty

31 papers receiving 1.0k citations

Peers

Dimple Chakravarty
Comparison fields: 5 of 86
  • Cancer Research 298
  • Genetics 343
  • Oncology 270
  • Molecular Biology 603
  • Obstetrics and Gynecology 54
Replace Ge Wu with:
Ge Wu China
Jean C. Tien United States
Semir Beyaz United States
Sitharthan Kamalakaran United States
Lesley Lomo United States
Damien A. Leach United Kingdom
Huihui Chen China
Olaf Hellwinkel Germany
Laudine Communal Canada
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Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Dimple Chakravarty

Since Specialization
Citations

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

Fields of papers citing papers by Dimple Chakravarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dimple Chakravarty, 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 Dimple Chakravarty Line = papers co-authored together Dimple Chakravarty links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016315
2 202091
3 201089
4 201076
5 201062
6 201143
7 200837
8 201136
9 201035
10 200928
11 200827
12 200724
13 201723
14 202119
15 200916
16 202116
17 201113
18 200913
19 202011
20 200810

About Dimple Chakravarty

Dimple Chakravarty is a scholar working on Genetics, Oncology, Molecular Biology, Pulmonary and Respiratory Medicine and Cancer Research, having authored 31 papers that have together received 1.0k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (14 papers), Prostate Cancer Treatment and Research (6 papers), HER2/EGFR in Cancer Research (4 papers), RNA Research and Splicing (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), COVID-19 Clinical Research Studies (3 papers), COVID-19 and healthcare impacts (3 papers) and Cytokine Signaling Pathways and Interactions (2 papers). The work is most often cited by research in Cancer Research (298 citations), Genetics (343 citations), Oncology (270 citations), Molecular Biology (603 citations) and Obstetrics and Gynecology (54 citations). Dimple Chakravarty has collaborated with scholars based in United States, India and Italy. Frequent co-authors include Francesca Demichelis, Mark A. Rubin, Ekta Khurana, Ratna K. Vadlamudi, Mark Gerstein, Yao Fu, Rajeshwar R. Tekmal, Sujit S. Nair, Binoj C. Nair and Ashutosh Tewari. Their work appears in journals such as Cancer Research, Molecular Cancer Research, Acta Histochemica, Cancers and Clinical Cancer Research.

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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