Lay Kodama

2.2k citations
13 papers · 1.1k indexed · 1 hit paper · h-index 11
Topics
Neuroinflammation and Neurodegeneration Mechanisms (9 papers)Immune cells in cancer (3 papers)Neurological Disease Mechanisms and Treatments (2 papers)

In The Last Decade

Lay Kodama

13 papers receiving 1.1k citations

Hit Papers

Microglial NF-κB drives tau spreading and toxicity in a m...2022202620232024202250100150

Peers

Lay Kodama
Comparison fields: 5 of 79
  • Neurology 583
  • Cellular and Molecular Neuroscience 370
  • Physiology 293
  • Immunology 257
  • Molecular Biology 247
Replace Alexandra E. Münch with:
Alexandra E. Münch United States
Lavinia Albéri Switzerland
Christiane Frahm Germany
Maria Amalia Di Castro Italy
Adeline Rachalski Canada
María Dolores López-Ávalos Spain
Zhonghua Lu China
Dimitrije Krstic Switzerland
Pedro Lax Spain
Romina Vuono United Kingdom
Lay Kodama relative to Alexandra E. Münch United States Alexandra E. Münch's profile →
Citations per field
00.5×3.5×
Alexandra E. Münch · 1×
Citations per year

Countries citing papers authored by Lay Kodama

Since Specialization
Citations

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

Fields of papers citing papers by Lay Kodama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lay Kodama

This figure shows the co-authorship network connecting the top 25 collaborators of Lay Kodama. A scholar is included among the top collaborators of Lay Kodama 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 Lay Kodama. Lay Kodama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1 6
2 2
3
Microglial NF-κB drives tau spreading and toxicity in a mouse model of tauopathybreakdown →
186
4 123
5 42
6 54
7 109
8 79
9 89
10 42
11 126
12 81
13 202

About Lay Kodama

Lay Kodama is a scholar working on Neurology, Developmental Neuroscience and Biological Psychiatry, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (9 papers), Immune cells in cancer (3 papers) and Neurological Disease Mechanisms and Treatments (2 papers). The work is most often cited by research in Neurology (583 citations), Biological Psychiatry (113 citations) and Developmental Neuroscience (101 citations). Lay Kodama has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Li Gan, Qili Liu, Mark N. Wu, Sha Liu, Lihong Zhan, Yaqiao Li, Yungui Zhou, David Le, Faten A. Sayed and Claire D. Clelland. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

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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