Keyla Perez

37 papers receiving 2.1k citations

Peers

Keyla Perez
Comparison fields: 5 of 100
  • Physiology 1.4k
  • Aging 91
  • Nutrition and Dietetics 382
  • Neurology 166
  • Pharmacology 301
Replace Deborah J. Tew with:
Deborah J. Tew Australia
Dirk Beher United States
Roberta Cascella Italy
William P. Esler United States
Leila M. Luheshi United Kingdom
Michael Lee Australia
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Cristina Cecchi Italy
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Keyla Perez relative to Deborah J. Tew Australia Deborah J. Tew's profile →
Citations per field
00.5×
Deborah J. Tew · 1×
Citations per year

Countries citing papers authored by Keyla Perez

Since Specialization
Citations

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

Fields of papers citing papers by Keyla Perez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009242
2 2008223
3 2008187
4 2008180
5 2006166
6 2007128
7 2009102
8 200994
9 201080
10 200975
11 201375
12 201062
13 201360
14 201756
15
The Caenorhabditis elegans A beta(1-42) Model of Alzheimer Disease Predominantly Expresses A beta(3-42)
200955
16 200948
17 201444
18 200743
19 202137
20 201232

About Keyla Perez

Keyla Perez is a scholar working on Physiology, Pharmacology, Molecular Biology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience, having authored 41 papers that have together received 2.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (36 papers), Cholinesterase and Neurodegenerative Diseases (13 papers), Computational Drug Discovery Methods (6 papers), Trace Elements in Health (5 papers), Drug Transport and Resistance Mechanisms (4 papers), Advanced Proteomics Techniques and Applications (3 papers), S100 Proteins and Annexins (3 papers) and Prion Diseases and Protein Misfolding (3 papers). The work is most often cited by research in Physiology (1.4k citations), Aging (91 citations), Nutrition and Dietetics (382 citations), Neurology (166 citations) and Pharmacology (301 citations). Keyla Perez has collaborated with scholars based in Australia, United States and Japan. Frequent co-authors include Kevin J. Barnham, Colin L. Masters, Roberto Cappai, Deborah J. Tew, Ashley I. Bush, Robert A. Cherny, Giuseppe D. Ciccotosto, Lin W. Hung, John D. Wade and Andrew F. Hill. Their work appears in journals such as Journal of Alzheimer s Disease, Alzheimer s & Dementia, Journal of Neuroscience, Acta Neuropathologica and ACS Chemical Neuroscience.

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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