Deepa Thaloor

1.4k total citations
8 papers, 1.2k citations indexed

About

Deepa Thaloor is a scholar working on Molecular Biology, Surgery and Rehabilitation. According to data from OpenAlex, Deepa Thaloor has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Surgery and 2 papers in Rehabilitation. Recurrent topics in Deepa Thaloor's work include Muscle Physiology and Disorders (5 papers), Tissue Engineering and Regenerative Medicine (3 papers) and Knee injuries and reconstruction techniques (2 papers). Deepa Thaloor is often cited by papers focused on Muscle Physiology and Disorders (5 papers), Tissue Engineering and Regenerative Medicine (3 papers) and Knee injuries and reconstruction techniques (2 papers). Deepa Thaloor collaborates with scholars based in United States. Deepa Thaloor's co-authors include Grace K. Pavlath, Gurmel S. Sidhu, Radha K. Maheshwari, Gyanendra K. Patnaik, Krishna Banaudha, R.C. Srimal, Anoop Singh, Karen L. Abbott, Thomas J. Murphy and Bret B. Friday and has published in prestigious journals such as Molecular Biology of the Cell, American Journal of Physiology-Cell Physiology and Journal of Cellular Physiology.

In The Last Decade

Deepa Thaloor

8 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Deepa Thaloor United States	8	727	300	209	173	140	8	1.2k
Elahe Mahdipour Iran	17	431 0.6×	132 0.4×	200 1.0×	97 0.6×	194 1.4×	33	921
Franziska Busch Germany	7	405 0.6×	179 0.6×	32 0.2×	117 0.7×	77 0.6×	10	1.0k
Suk-Jae Chung South Korea	15	297 0.4×	35 0.1×	76 0.4×	153 0.9×	187 1.3×	21	1.1k
Ki‐Sook Park South Korea	22	648 0.9×	20 0.1×	103 0.5×	112 0.6×	141 1.0×	64	1.3k
Takako Maruyama Japan	12	508 0.7×	36 0.1×	96 0.5×	127 0.7×	26 0.2×	27	1.2k
Hee Seok Yang South Korea	22	428 0.6×	22 0.1×	142 0.7×	189 1.1×	71 0.5×	49	1.3k
Masoud Darabi Iran	24	617 0.8×	46 0.2×	28 0.1×	267 1.5×	57 0.4×	108	1.8k
Pankaj Chaturvedi United States	22	953 1.3×	49 0.2×	47 0.2×	91 0.5×	21 0.1×	45	1.5k
Saeed Khodayari Iran	14	385 0.5×	105 0.3×	26 0.1×	79 0.5×	47 0.3×	33	898
Thangavelu Soundara Rajan Italy	26	691 1.0×	25 0.1×	62 0.3×	238 1.4×	463 3.3×	48	1.9k

Countries citing papers authored by Deepa Thaloor

Since Specialization

Citations

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

Fields of papers citing papers by Deepa Thaloor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepa Thaloor

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

All Works

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8 of 8 papers shown

1.

Thaloor, Deepa, et al.. (2000). Hepatocyte growth factor affects satellite cell activation and differentiation in regenerating skeletal muscle. American Journal of Physiology-Cell Physiology. 278(1). C174–C181. 198 indexed citations

2.

Thaloor, Deepa, et al.. (1999). Systemic administration of the NF-κB inhibitor curcumin stimulates muscle regeneration after traumatic injury. American Journal of Physiology-Cell Physiology. 277(2). C320–C329. 186 indexed citations

3.

Sidhu, Gurmel S., Anoop Singh, Deepa Thaloor, et al.. (1998). Enhancement of wound healing by curcumin in animals. Wound Repair and Regeneration. 6(2). 167–177. 309 indexed citations

4.

Thaloor, Deepa, Anoop K. Singh, Gurmel S. Sidhu, et al.. (1998). Inhibition of angiogenic differentiation of human umbilical vein endothelial cells by curcumin.. PubMed. 9(4). 305–12. 149 indexed citations

5.

Abbott, Karen L., Bret B. Friday, Deepa Thaloor, Thomas J. Murphy, & Grace K. Pavlath. (1998). Activation and Cellular Localization of the Cyclosporine A-sensitive Transcription Factor NF-AT in Skeletal Muscle Cells. Molecular Biology of the Cell. 9(10). 2905–2916. 193 indexed citations

6.

Pavlath, Grace K., et al.. (1998). Heterogeneity among muscle precursor cells in adult skeletal muscles with differing regenerative capacities. Developmental Dynamics. 212(4). 495–508. 7 indexed citations

7.

Pavlath, Grace K., et al.. (1998). Heterogeneity among muscle precursor cells in adult skeletal muscles with differing regenerative capacities. Developmental Dynamics. 212(4). 495–508. 141 indexed citations

8.

Sidhu, Gurmel S., Deepa Thaloor, Anoop Singh, Puthiyaveettil N. Raghunath, & Radha K. Maheshwari. (1996). Enhanced biosynthesis of extracellular matrix proteins and TGF-β1 by polyinosinic-polycytidylic acid during cutaneous wound healing in vivo. Journal of Cellular Physiology. 169(1). 108–114. 12 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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