Math P. Cuajungco

6.5k citations
56 papers · 5.3k indexed · 2 hit papers · h-index 32
Topics
Trace Elements in Health (28 papers)Alzheimer's disease research and treatments (14 papers)Calcium signaling and nucleotide metabolism (12 papers)

In The Last Decade

Math P. Cuajungco

55 papers receiving 5.3k citations

Hit Papers

The Aβ Peptide of Alzheimer's Disease Directly Produces H...199920262008201719991999250500750

Peers

Math P. Cuajungco
Comparison fields: 5 of 125
  • Physiology 2.2k
  • Nutrition and Dietetics 1.8k
  • Molecular Biology 1.7k
  • Cellular and Molecular Neuroscience 858
  • Health, Toxicology and Mutagenesis 723
Replace Lorella M.T. Canzoniero with:
Lorella M.T. Canzoniero Italy
Sang Won Suh South Korea
Kenneth Hensley United States
Byoung Joo Gwag South Korea
Francisco J. Schöpfer United States
Miloš R. Filipović Germany
Karlene K. Gunter United States
Vera Ádám‐Vizi Hungary
Juan Segura‐Aguilar Chile
Pamela S. Puttfarcken United States
Math P. Cuajungco relative to Lorella M.T. Canzoniero Italy Lorella M.T. Canzoniero's profile →
Citations per field
00.5×1.5×1.8×
Lorella M.T. Canzoniero · 1×
Citations per year

Countries citing papers authored by Math P. Cuajungco

Since Specialization
Citations

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

Fields of papers citing papers by Math P. Cuajungco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Math P. Cuajungco. 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 Math P. Cuajungco. The network helps show where Math P. Cuajungco may publish in the future.

Co-authorship network of co-authors of Math P. Cuajungco

This figure shows the co-authorship network connecting the top 25 collaborators of Math P. Cuajungco. A scholar is included among the top collaborators of Math P. Cuajungco based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Math P. Cuajungco. Math P. Cuajungco is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 8
2 4
3 22
4 18
5 60
6 63
7 43
8 55
9 55
10 51
11 196
12 108
13 24
14 23
15 448
16 167
17 335
18 58
19 98
20 147

About Math P. Cuajungco

Math P. Cuajungco is a scholar working on Physiology, Sensory Systems and Nutrition and Dietetics, having authored 56 papers that have together received 5.3k indexed citations. Recurring topics across this work include Trace Elements in Health (28 papers), Alzheimer's disease research and treatments (14 papers) and Calcium signaling and nucleotide metabolism (12 papers). The work is most often cited by research in Sensory Systems (638 citations), Nutrition and Dietetics (1.8k citations) and Physiology (436 citations). Math P. Cuajungco has collaborated with scholars based in United States, Australia and New Zealand. Frequent co-authors include G.J. Lees, Ashley I. Bush, Xudong Huang, Rudolph E. Tanzi, Craig Atwood, Lee E. Goldstein, James Lim, Robert D. Moir, Richard C. Scarpa and Mariana A. Hartshorn. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Biochemistry.

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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