Sameeksha Chopra

10 papers receiving 483 citations

Sameeksha Chopra's Hit Papers

Matrix Metalloproteinases: From Molecular Mechanisms to Physiology, Pathophysiology, and Pharmacology 2022 · 341 citations
3410+1+2Years since publication100200300

Peers

Sameeksha Chopra
Comparison fields: 5 of 87
  • Cancer Research 116
  • Developmental Neuroscience 18
  • Oncology 87
  • Neurology 27
  • Immunology and Allergy 18
Replace Ling Zhou with:
Ling Zhou China
Roberta Angioni Italy
I‐Neng Lee Taiwan
Jessica Neil United States
Stéphane Jemelin Switzerland
Karolina Łuczkowska Poland
Jing Bai China
Heike Meýborg Germany
Toshiko Sugimoto Japan
Meng Xie China
Sameeksha Chopra relative to Ling Zhou China Ling Zhou's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sameeksha Chopra

Since Specialization
Citations

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

Fields of papers citing papers by Sameeksha Chopra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1
Matrix Metalloproteinases: From Molecular Mechanisms to Physiology, Pathophysiology, and Pharmacology
Hit paper breakdown →
2022341
2 201943
3 201926
4 202123
5 202119
6 202415
7 20229
8 20255
9 20253
10 20212
11 20260
12 20250

About Sameeksha Chopra

Sameeksha Chopra is a scholar working on Molecular Biology, Immunology, Hematology, Oncology and Neurology, having authored 12 papers that have together received 486 indexed citations. Recurring topics across this work include IL-33, ST2, and ILC Pathways (3 papers), Advanced Proteomics Techniques and Applications (2 papers), Peptidase Inhibition and Analysis (2 papers), Gut microbiota and health (2 papers), Blood Coagulation and Thrombosis Mechanisms (2 papers), Protease and Inhibitor Mechanisms (2 papers), Mass Spectrometry Techniques and Applications (1 paper) and Neurogenesis and neuroplasticity mechanisms (1 paper). The work is most often cited by research in Cancer Research (116 citations), Developmental Neuroscience (18 citations), Oncology (87 citations), Neurology (27 citations) and Immunology and Allergy (18 citations). Sameeksha Chopra has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Antoine Dufour, Daniel Young, Luiz G. Almeida, Sean E. Gill, Laurent Devel, Christopher M. Overall, Michael R. Hughes, Kelly M. McNagny, Hans J. Vogel and Yicong Li. Their work appears in journals such as ACS Chemical Biology, BioTechniques, Mucosal Immunology, Cell Reports and The Journal of Experimental Medicine.

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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