Shanta Nag

1.2k total citations
10 papers, 913 citations indexed

About

Shanta Nag is a scholar working on Epidemiology, Cell Biology and Molecular Biology. According to data from OpenAlex, Shanta Nag has authored 10 papers receiving a total of 913 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Epidemiology, 6 papers in Cell Biology and 3 papers in Molecular Biology. Recurrent topics in Shanta Nag's work include Autophagy in Disease and Therapy (8 papers), Cellular transport and secretion (3 papers) and Endoplasmic Reticulum Stress and Disease (3 papers). Shanta Nag is often cited by papers focused on Autophagy in Disease and Therapy (8 papers), Cellular transport and secretion (3 papers) and Endoplasmic Reticulum Stress and Disease (3 papers). Shanta Nag collaborates with scholars based in United States, France and Japan. Shanta Nag's co-authors include Thomas J. Melia, Karlina J. Kauffman, Alf Håkon Lystad, Tyler J. Moss, Fulvio Reggiori, Misuzu Baba, James A. McNew, Jiefei Geng, Usha Nair and Ke Wang and has published in prestigious journals such as Cell, Journal of Biological Chemistry and The Journal of Cell Biology.

In The Last Decade

Shanta Nag

10 papers receiving 908 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shanta Nag United States	9	705	380	359	136	114	10	913
Päivi Ylä‐Anttila Sweden	10	805 1.1×	376 1.0×	421 1.2×	143 1.1×	103 0.9×	11	1.1k
Andrea Gubaš Germany	10	790 1.1×	372 1.0×	453 1.3×	183 1.3×	132 1.2×	14	1.1k
Samuel G. Crawshaw United Kingdom	7	582 0.8×	397 1.0×	400 1.1×	134 1.0×	83 0.7×	8	857
Hallvard Lauritz Olsvik Norway	7	546 0.8×	466 1.2×	444 1.2×	177 1.3×	108 0.9×	9	934
Yakubu Princely Abudu Norway	12	642 0.9×	276 0.7×	434 1.2×	153 1.1×	90 0.8×	14	924
Christine Abert Austria	7	679 1.0×	347 0.9×	440 1.2×	108 0.8×	68 0.6×	9	837
Monica Fengsrud Norway	10	609 0.9×	352 0.9×	303 0.8×	98 0.7×	134 1.2×	11	834
Zhenyuan Tang United States	10	437 0.6×	305 0.8×	309 0.9×	86 0.6×	80 0.7×	11	681
Kazuaki Matoba Japan	9	492 0.7×	282 0.7×	329 0.9×	87 0.6×	61 0.5×	19	665
Daniel Papinski Austria	11	781 1.1×	469 1.2×	523 1.5×	157 1.2×	97 0.9×	12	1.0k

Countries citing papers authored by Shanta Nag

Since Specialization

Citations

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

Fields of papers citing papers by Shanta Nag

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanta Nag

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

All Works

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10 of 10 papers shown

Wu, Yumei, Shenliang Yu, Shanta Nag, et al.. (2023). ATG9 vesicles comprise the seed membrane of mammalian autophagosomes. The Journal of Cell Biology. 222(7). 62 indexed citations

Omrane, Mohyeddine, Kalthoum Ben M’Barek, Alexandre Santinho, et al.. (2023). LC3B is lipidated to large lipid droplets during prolonged starvation for noncanonical autophagy. Developmental Cell. 58(14). 1266–1281.e7. 23 indexed citations

Nguyen, Nathan, Jiaxin Jin, Shenliang Yu, et al.. (2020). The insufficiency of ATG4A in macroautophagy. Journal of Biological Chemistry. 295(39). 13584–13600. 9 indexed citations

Lystad, Alf Håkon, Sven R. Carlsson, Laura Rodríguez de la Ballina, et al.. (2019). Distinct functions of ATG16L1 isoforms in membrane binding and LC3B lipidation in autophagy-related processes. Nature Cell Biology. 21(3). 372–383. 144 indexed citations

Kauffman, Karlina J., Shenliang Yu, Jiaxin Jin, et al.. (2018). Delipidation of mammalian Atg8-family proteins by each of the four ATG4 proteases. Autophagy. 14(6). 1–19. 72 indexed citations

Nath, Sangeeta, Julia Dancourt, Vladimir Shteyn, et al.. (2014). Lipidation of the LC3/GABARAP family of autophagy proteins relies on a membrane-curvature-sensing domain in Atg3. Nature Cell Biology. 16(5). 415–424. 201 indexed citations

Nath, Sangeeta, Julia Dancourt, Shanta Nag, et al.. (2013). The Lipidation Machinery Involved in Autophagosome Growth is Only Functional on Highly Curved Membranes. Biophysical Journal. 104(2). 97a–97a. 1 indexed citations

Nair, Usha, Jiefei Geng, Noor Gammoh, et al.. (2011). SNARE Proteins Are Required for Macroautophagy. Cell. 146(2). 290–302. 356 indexed citations

Devine, Lesley, Deepshi Thakral, Shanta Nag, et al.. (2006). Mapping the Binding Site on CD8β for MHC Class I Reveals Mutants with Enhanced Binding. The Journal of Immunology. 177(6). 3930–3938. 15 indexed citations

10.

Greally, John M., et al.. (2002). Identification of a Candidate Regulatory Region in the Human CD8 Gene Complex by Colocalization of DNase I Hypersensitive Sites and Matrix Attachment Regions Which Bind SATB1 and GATA-3. The Journal of Immunology. 168(8). 3915–3922. 30 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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