Pavithran T. Ravindran

819 total citations
9 papers, 343 citations indexed

About

Pavithran T. Ravindran is a scholar working on Molecular Biology, Mechanical Engineering and Pathology and Forensic Medicine. According to data from OpenAlex, Pavithran T. Ravindran has authored 9 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Mechanical Engineering and 1 paper in Pathology and Forensic Medicine. Recurrent topics in Pavithran T. Ravindran's work include Single-cell and spatial transcriptomics (2 papers), Gene Regulatory Network Analysis (2 papers) and Receptor Mechanisms and Signaling (2 papers). Pavithran T. Ravindran is often cited by papers focused on Single-cell and spatial transcriptomics (2 papers), Gene Regulatory Network Analysis (2 papers) and Receptor Mechanisms and Signaling (2 papers). Pavithran T. Ravindran collaborates with scholars based in United States. Pavithran T. Ravindran's co-authors include Jared E. Toettcher, Maxwell Z. Wilson, Wendell A. Lim, Agnieszka A. Gil, César Carrasco‐López, Alexander G. Goglia, José L. Avalos‬, Evan M. Zhao, Liyuan Zhu and Xiaoqing Rong and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Pavithran T. Ravindran

9 papers receiving 343 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Pavithran T. Ravindran United States	7	233	78	67	50	34	9	343
Steven J. Mayerl United States	6	523 2.2×	108 1.4×	33 0.5×	27 0.5×	11 0.3×	7	548
Ling-chun Chen United States	10	374 1.6×	39 0.5×	30 0.4×	74 1.5×	16 0.5×	10	467
Matthew D. Weitzman United States	8	179 0.8×	61 0.8×	25 0.4×	53 1.1×	21 0.6×	10	314
Sandra Münch Germany	10	196 0.8×	22 0.3×	27 0.4×	37 0.7×	20 0.6×	13	359
Spencer C. Alford Canada	10	326 1.4×	113 1.4×	21 0.3×	24 0.5×	81 2.4×	12	439
Aerielle E. Matsangos United States	7	261 1.1×	34 0.4×	10 0.1×	41 0.8×	25 0.7×	11	411
N. T. Hang Pham Canada	8	512 2.2×	94 1.2×	30 0.4×	50 1.0×	13 0.4×	12	612
Lucy S. Chong United States	7	373 1.6×	17 0.2×	50 0.7×	43 0.9×	13 0.4×	7	462
Tessa Campbell Canada	11	250 1.1×	84 1.1×	20 0.3×	33 0.7×	16 0.5×	25	424
Laura B. Chipman United States	6	584 2.5×	74 0.9×	27 0.4×	22 0.4×	8 0.2×	7	650

Countries citing papers authored by Pavithran T. Ravindran

Since Specialization

Citations

This map shows the geographic impact of Pavithran T. Ravindran'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 Pavithran T. Ravindran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavithran T. Ravindran more than expected).

Fields of papers citing papers by Pavithran T. Ravindran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pavithran T. Ravindran. 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 Pavithran T. Ravindran. The network helps show where Pavithran T. Ravindran may publish in the future.

Co-authorship network of co-authors of Pavithran T. Ravindran

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

All Works

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9 of 9 papers shown

Ravindran, Pavithran T., et al.. (2026). AP-1 mediates cellular adaptation and memory formation. Nature Communications. 1 indexed citations

Piraner, Dan I., Mohamad H. Abedi, Annie Lin, et al.. (2024). Engineered receptors for soluble cellular communication and disease sensing. Nature. 638(8051). 805–813. 16 indexed citations

Ravindran, Pavithran T., et al.. (2021). A synthetic gene circuit for imaging-free detection of signaling pulses. Cell Systems. 13(2). 131–142.e13. 14 indexed citations

Nerger, Bryan A., Katharine Goodwin, Sandra B. Lemke, et al.. (2021). Stress ball morphogenesis: How the lizard builds its lung. Science Advances. 7(52). eabk0161–eabk0161. 15 indexed citations

Ravindran, Pavithran T., et al.. (2020). Engineering combinatorial and dynamic decoders using synthetic immediate-early genes. Communications Biology. 3(1). 9 indexed citations

Gil, Agnieszka A., César Carrasco‐López, Liyuan Zhu, et al.. (2020). Optogenetic control of protein binding using light-switchable nanobodies. Nature Communications. 11(1). 4044–4044. 100 indexed citations

Leeman, Jonathan E., Yi Li, Andrew Bell, et al.. (2019). Human papillomavirus 16 promotes microhomology-mediated end-joining. Proceedings of the National Academy of Sciences. 116(43). 21573–21579. 66 indexed citations

Wilson, Maxwell Z., Pavithran T. Ravindran, Wendell A. Lim, & Jared E. Toettcher. (2017). Tracing Information Flow from Erk to Target Gene Induction Reveals Mechanisms of Dynamic and Combinatorial Control. Molecular Cell. 67(5). 757–769.e5. 116 indexed citations

Ravindran, Pavithran T. & Nadarajah Vasanthan. (2015). Formation of Poly(3-hydroxybutyrate) (PHB) Inclusion Compound with Urea and Unusual Crystallization Behavior of Coalesced PHB. Macromolecules. 48(9). 3080–3087. 6 indexed citations

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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