Karma Dacosta

408 citations
13 papers · 157 · h-index 6

Impact in

    • Immunotherapy and Immune Responses
    • Immune Cell Function and Interaction
    • Immune cells in cancer
    • T-cell and B-cell Immunology
    • Cancer Immunotherapy and Biomarkers
    • CAR-T cell therapy research

Papers in

    • CAR-T cell therapy research 4
    • Cancer Immunotherapy and Biomarkers 4
    • Cancer Cells and Metastasis 2
    • Immunotherapy and Immune Responses 3
    • T-cell and B-cell Immunology 2
    • Immune Cell Function and Interaction 2

Karma Dacosta

12 papers receiving 154 citations

Peers

Karma Dacosta
Comparison fields: 5 of 35
  • Immunology 85
  • Oncology 99
  • Health Informatics 2
  • Biophysics 7
  • Physiology 5
Replace Auriole Tamegnon with:
Auriole Tamegnon United States
Shamin Li United States
Tupitsyn Nn Russia
Marie Mack United States
Kit Fuhrman United States
Tarsem Moudgil United States
Kees Bisschop Netherlands
Alexandra Roux France
Luca Paruzzo Italy
Gert Van den Eyden Belgium
Karma Dacosta relative to Auriole Tamegnon United States Auriole Tamegnon's profile →
Citations per field
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Auriole Tamegnon · 1×
Citations per year

Countries citing papers authored by Karma Dacosta

Since Specialization
Citations

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

Fields of papers citing papers by Karma Dacosta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 201869
2 201926
3 201621
4 201914
5 201710
6 20227
7 20195
8 20241
9 20211
10 20101
11 20201
12 20221
13 20250

About Karma Dacosta

Karma Dacosta is a scholar working on Oncology, Immunology, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 13 papers that have together received 157 indexed citations. Recurring topics across this work include CAR-T cell therapy research (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Immunotherapy and Immune Responses (3 papers), Cancer Cells and Metastasis (2 papers), T-cell and B-cell Immunology (2 papers), Immune Cell Function and Interaction (2 papers), Diabetes and associated disorders (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Immunology (85 citations), Oncology (99 citations), Health Informatics (2 citations), Biophysics (7 citations) and Physiology (5 citations). Karma Dacosta has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Charles O. Brown, Keith E. Steele, Rubén Cárdenes, Gianluca Carlesso, Tobias Wiestler, Moritz Widmaier, Tze Heng Tan, Johannes Zimmermann, Jiping Zha and Ronald Herbst. Their work appears in journals such as Journal of Visualized Experiments, Cancer Research, The Journal of Immunology, Journal of Histochemistry & Cytochemistry and Reproductive Toxicology.

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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