Ramesh V. Nair

2.9k citations
26 papers · 1.5k indexed · h-index 18
Topics
Biofuel production and bioconversion (5 papers)Cancer Genomics and Diagnostics (5 papers)Microbial Metabolic Engineering and Bioproduction (4 papers)

In The Last Decade

Ramesh V. Nair

25 papers receiving 1.5k citations

Peers

Ramesh V. Nair
Comparison fields: 5 of 107
  • Molecular Biology 851
  • Pathology and Forensic Medicine 343
  • Biomedical Engineering 326
  • Oncology 322
  • Cancer Research 209
Replace Jorge Lima with:
Jorge Lima Portugal
İlyas Şahin United States
Peter Löser Germany
Jenny Wu United States
Stefanie Löffek Germany
Felix Bachmann Switzerland
Luís Lombardía Spain
Eugen Dhimolea United States
Ming Tang China
Stephan Fricke Germany
Ramesh V. Nair relative to Jorge Lima Portugal Jorge Lima's profile →
Citations per field
00.5×1.5×2.3×
Jorge Lima · 1×
Citations per year

Countries citing papers authored by Ramesh V. Nair

Since Specialization
Citations

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

Fields of papers citing papers by Ramesh V. Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ramesh V. Nair. 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 Ramesh V. Nair. The network helps show where Ramesh V. Nair may publish in the future.

Co-authorship network of co-authors of Ramesh V. Nair

This figure shows the co-authorship network connecting the top 25 collaborators of Ramesh V. Nair. A scholar is included among the top collaborators of Ramesh V. Nair 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 Ramesh V. Nair. Ramesh V. Nair 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 7
2 1
3 6
4 0
5 44
6 3
7 14
8 38
9 24
10 77
11 50
12 61
13 209
14 60
15 22
16 77
17 19
18 120
19 65
20 55

About Ramesh V. Nair

Ramesh V. Nair is a scholar working on Cancer Research, Developmental Neuroscience and Molecular Biology, having authored 26 papers that have together received 1.5k indexed citations. Recurring topics across this work include Biofuel production and bioconversion (5 papers), Cancer Genomics and Diagnostics (5 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). The work is most often cited by research in Pathology and Forensic Medicine (343 citations), Genetics (154 citations) and Cancer Research (209 citations). Ramesh V. Nair has collaborated with scholars based in United States, Spain and Netherlands. Frequent co-authors include Eleftherios T. Papoutsakis, George N. Bennett, Andrew J. Gentles, Emmanuel Cornillot, Philippe Soucaille, Sylvia K. Plevritis, Ash A. Alizadeh, Jonathan M. Irish, Ronald Levy and Michael R. Green. Their work appears in journals such as Proceedings of the National Academy of Sciences, Circulation 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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