Dina Aggad

1.4k citations
27 papers · 1.0k · h-index 17

Impact in

  • Aging top 2%
    • Genetics, Aging, and Longevity in Model Organisms
  • Immunology top 10%
    • interferon and immune responses
    • Aquaculture disease management and microbiota
    • Immune Response and Inflammation

Papers in

Dina Aggad

26 papers receiving 1.0k citations

Peers

Dina Aggad
Comparison fields: 5 of 94
  • Aging 100
  • Immunology 297
  • Neurology 181
  • Genetics 83
  • Cell Biology 130
Replace C Molina with:
C Molina United Kingdom
Inês Mendes Pinto Portugal
Yingli Wang China
David J. Peeler United States
Jiafu Long China
Michaël Trichet France
Wei Yue China
Sunaina Surana United Kingdom
Pengli Zheng China
Dina Aggad relative to C Molina United Kingdom C Molina's profile →
Citations per field
00.5×5.8×
C Molina · 1×
Citations per year

Countries citing papers authored by Dina Aggad

Since Specialization
Citations

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

Fields of papers citing papers by Dina Aggad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009213
2 2013111
3 201096
4 201294
5 201783
6 201647
7 201742
8 201741
9 201738
10 201636
11 201435
12 201733
13 201630
14 201928
15 201819
16 201719
17 201817
18 202314
19 202311
20 201911

About Dina Aggad

Dina Aggad is a scholar working on Biomedical Engineering, Materials Chemistry, Molecular Biology, Biomaterials and Pulmonary and Respiratory Medicine, having authored 27 papers that have together received 1.0k indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (9 papers), Nanoparticle-Based Drug Delivery (6 papers), Porphyrin and Phthalocyanine Chemistry (5 papers), Photodynamic Therapy Research Studies (5 papers), Amyotrophic Lateral Sclerosis Research (4 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers), RNA Interference and Gene Delivery (3 papers) and Mesoporous Materials and Catalysis (2 papers). The work is most often cited by research in Aging (100 citations), Immunology (297 citations), Neurology (181 citations), Genetics (83 citations) and Cell Biology (130 citations). Dina Aggad has collaborated with scholars based in France, United States and Canada. Frequent co-authors include J. Alex Parker, Pierre Drapeau, Pierre Boudinot, Georges Lutfalla, Martine Mazel, Philippe Herbomel, Jean‐Pierre Levraud, Alexandra Vaccaro, Magali Gary‐Bobo and Arnaud Tauffenberger. Their work appears in journals such as Journal of Materials Chemistry B, Molecules, The Journal of Immunology, ChemNanoMat and Journal of Agricultural and Food Chemistry.

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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