Daniel Mazal

720 citations
13 papers · 583 · h-index 9

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 5
    • Signaling Pathways in Disease 2
    • Galectins and Cancer Biology 6
    • Toxin Mechanisms and Immunotoxins 2

Daniel Mazal

13 papers receiving 577 citations

Peers

Daniel Mazal
Comparison fields: 5 of 74
  • Immunology 307
  • Biological Psychiatry 20
  • Molecular Biology 388
  • Parasitology 26
  • Oncology 108
Replace Luis Ubillos with:
Luis Ubillos Uruguay
Rachid Zagani United States
Silvia Sedda Italy
Meghan L. Marré United States
Raquel Duque do Nascimento Arifa Brazil
Seok‐Ho Kim South Korea
Hongxiang Sun China
Raki Sudan United States
Angela Santoni Italy
Lina Wang China
Daniel Mazal relative to Luis Ubillos Uruguay Luis Ubillos's profile →
Citations per field
00.5×1.5×2.5×
Luis Ubillos · 1×
Citations per year

Countries citing papers authored by Daniel Mazal

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Mazal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2012216
2 2005133
3 200564
4 201546
5 201334
6 200529
7 201016
8 201312
9 20049
10 20158
11 20207
12 20186
13 20213

About Daniel Mazal

Daniel Mazal is a scholar working on Molecular Biology, Immunology, Organic Chemistry, Pharmacology and Oncology, having authored 13 papers that have together received 583 indexed citations. Recurring topics across this work include Galectins and Cancer Biology (6 papers), Glycosylation and Glycoproteins Research (5 papers), Signaling Pathways in Disease (2 papers), Toxin Mechanisms and Immunotoxins (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Chemokine receptors and signaling (1 paper), Coccidia and coccidiosis research (1 paper) and Connective tissue disorders research (1 paper). The work is most often cited by research in Immunology (307 citations), Biological Psychiatry (20 citations), Molecular Biology (388 citations), Parasitology (26 citations) and Oncology (108 citations). Daniel Mazal has collaborated with scholars based in Uruguay, France and United States. Frequent co-authors include Eduardo Osinaga, Luis Ubillos, Gabriel A. Rabinovich, Sebastián Dergan‐Dylon, Mariana Salatino, Tomás Dalotto‐Moreno, Juan C. Stupirski, Marta A. Toscano, Juan P. Cerliani and Diego O. Croci. Their work appears in journals such as Journal of Histochemistry & Cytochemistry, Cancers, Scientific Reports, Breast Cancer Research and Treatment and Parasitology 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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