Daniel T. Passos

32 papers receiving 467 citations

Peers

Daniel T. Passos
Comparison fields: 5 of 71
  • Oncology 114
  • Endocrinology 20
  • Ophthalmology 30
  • Molecular Biology 251
  • Parasitology 24
Replace Emma Abernathy with:
Emma Abernathy United States
Katrina B. Mar United States
David J. Davido United States
Fiorella Kotsias Argentina
João T. Proença United Kingdom
Petra Muenzner Germany
Nina Gratz Austria
Zachary R. Newman United States
Marian Wiegand Germany
Viswas Konasagara Nagaleekar India
Daniel T. Passos relative to Emma Abernathy United States Emma Abernathy's profile →
Citations per field
00.5×1.5×2.4×
Emma Abernathy · 1×
Citations per year

Countries citing papers authored by Daniel T. Passos

Since Specialization
Citations

This map shows the geographic impact of Daniel T. Passos'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 T. Passos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Passos more than expected).

Fields of papers citing papers by Daniel T. Passos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016129
2 201932
3 200930
4 201628
5 201428
6 200726
7 201423
8 200722
9 199919
10 201617
11 201217
12 200811
13 200910
14 200910
15 200710
16 20089
17 20228
18 20157
19 20217
20 20245

About Daniel T. Passos

Daniel T. Passos is a scholar working on Molecular Biology, Oncology, Genetics, Cell Biology and Immunology, having authored 33 papers that have together received 473 indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (7 papers), Salmonella and Campylobacter epidemiology (4 papers), Ocular Oncology and Treatments (4 papers), Aquaculture disease management and microbiota (4 papers), Genetic and phenotypic traits in livestock (3 papers), Leptospirosis research and findings (3 papers), DNA Repair Mechanisms (2 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Oncology (114 citations), Endocrinology (20 citations), Ophthalmology (30 citations), Molecular Biology (251 citations) and Parasitology (24 citations). Daniel T. Passos has collaborated with scholars based in Brazil, Canada and United States. Frequent co-authors include Frederick A. Dick, Matthew J. Cecchini, Christopher J. Howlett, Ian Welch, Aren E. Marshall, Charles A. Ishak, Mellissa R.W. Mann, Seth M. Rubin, William A. MacDonald and Seung J. Kim. Their work appears in journals such as Molecular and Cellular Biology, eLife, Small Ruminant Research, Infection Genetics and Evolution and Molecular Cell.

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.

Explore authors with similar magnitude of impact