Madhavi Tippani

2.0k citations
17 papers · 776 indexed · 1 hit paper · h-index 8
Topics
Single-cell and spatial transcriptomics (9 papers)Neuroinflammation and Neurodegeneration Mechanisms (5 papers)Cell Image Analysis Techniques (4 papers)
Journals
Nucleic Acids ResearchNeuronSHILAP Revista de lepidopterología
Partner nations
United StatesFranceJapan

In The Last Decade

Madhavi Tippani

16 papers receiving 771 citations

Hit Papers

Transcriptome-scale spatial gene expression in the human ...20212026202220242021100200300400500

Peers

Madhavi Tippani
Comparison fields: 5 of 92
  • Molecular Biology 631
  • Neurology 112
  • Immunology 98
  • Biophysics 84
  • Cancer Research 70
Replace Matthew N. Tran with:
Matthew N. Tran United States
Brianna K. Barry United States
Gwendolyn E. Kaeser United States
Derek Gao United States
Naeem Nadaf United States
Thu Elizabeth Duong United States
Albert Liu United States
Song Chen China
Mohamed Nadhir Djekidel United States
Michael J. McConnell United States
Madhavi Tippani relative to Matthew N. Tran United States Matthew N. Tran's profile →
Citations per field
00.5×1.5×
Matthew N. Tran · 1×
Citations per year

Countries citing papers authored by Madhavi Tippani

Since Specialization
Citations

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

Fields of papers citing papers by Madhavi Tippani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Madhavi Tippani

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 5
2 1
3 1
4 8
5 2
6 6
7 9
8 5
9 10
10 4
11 7
12 2
13 107
14
Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortexbreakdown →
557
15 11
16 41
17 0

About Madhavi Tippani

Madhavi Tippani is a scholar working on Biophysics, Neurology and Developmental Neuroscience, having authored 17 papers that have together received 776 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (9 papers), Neuroinflammation and Neurodegeneration Mechanisms (5 papers) and Cell Image Analysis Techniques (4 papers). The work is most often cited by research in Biophysics (84 citations), Neurology (112 citations) and Biological Psychiatry (32 citations). Madhavi Tippani has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Kristen R. Maynard, Thomas M. Hyde, Keri Martinowich, Andrew E. Jaffe, Joel E. Kleinman, Leonardo Collado‐Torres, Stephanie C. Hicks, Matthew N. Tran, Brianna K. Barry and Lukas M. Weber. Their work appears in journals such as Nucleic Acids Research, Neuron and SHILAP Revista de lepidopterología.

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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