José Dávila-Velderrain

11.2k citations
40 papers · 2.8k indexed · 2 hit papers · h-index 20
Topics
Gene Regulatory Network Analysis (11 papers)Single-cell and spatial transcriptomics (10 papers)Neuroinflammation and Neurodegeneration Mechanisms (10 papers)
Partner nations
United StatesMexicoItaly

In The Last Decade

José Dávila-Velderrain

39 papers receiving 2.8k citations

Hit Papers

Single-cell transcriptomic analysis of Alzheimer’s disease2019202620212023201920244008001.2k

Peers

José Dávila-Velderrain
Comparison fields: 5 of 129
  • Molecular Biology 1.5k
  • Neurology 1.0k
  • Physiology 731
  • Cellular and Molecular Neuroscience 365
  • Immunology 341
Replace Hansruedi Mathys with:
Hansruedi Mathys United States
Jeremy A. Miller United States
Brian P. Hafler United States
Zhuyu Peng United States
Cristin McCabe United States
Basavaraj Hooli United States
Lu Sun United States
Eloïse Hudry United States
Özgün Gökçe Germany
Colleen L. Forster United States
José Dávila-Velderrain relative to Hansruedi Mathys United States Hansruedi Mathys's profile →
Citations per field
00.5×1.7×
Hansruedi Mathys · 1×
Citations per year

Countries citing papers authored by José Dávila-Velderrain

Since Specialization
Citations

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

Fields of papers citing papers by José Dávila-Velderrain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Dávila-Velderrain. 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 José Dávila-Velderrain. The network helps show where José Dávila-Velderrain may publish in the future.

Co-authorship network of co-authors of José Dávila-Velderrain

This figure shows the co-authorship network connecting the top 25 collaborators of José Dávila-Velderrain. A scholar is included among the top collaborators of José Dávila-Velderrain 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 José Dávila-Velderrain. José Dávila-Velderrain 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 11
2 17
3 54
4 1
5 58
6 63
7 17
8 87
9 145
10 182
11 2
12 210
13 2
14 3
15 1
16 28
17 6
18 45
19 53
20 16

About José Dávila-Velderrain

José Dávila-Velderrain is a scholar working on Neurology, Biological Psychiatry and Molecular Biology, having authored 40 papers that have together received 2.8k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (11 papers), Single-cell and spatial transcriptomics (10 papers) and Neuroinflammation and Neurodegeneration Mechanisms (10 papers). The work is most often cited by research in Neurology (1.0k citations), Biological Psychiatry (193 citations) and Developmental Neuroscience (172 citations). José Dávila-Velderrain has collaborated with scholars based in United States, Mexico and Italy. Frequent co-authors include Manolis Kellis, Shahin Mohammadi, Li‐Huei Tsai, Madhvi Menon, Brian P. Hafler, Fan Gao, Hansruedi Mathys, Liang He, David A. Bennett and Jennie Z. Young. Their work appears in journals such as Nature, Nucleic Acids Research and Nature Medicine.

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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