Deepika Calidas

1.0k total citations · 1 hit paper
6 papers, 708 citations indexed

About

Deepika Calidas is a scholar working on Molecular Biology, Aging and Genetics. According to data from OpenAlex, Deepika Calidas has authored 6 papers receiving a total of 708 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Aging and 2 papers in Genetics. Recurrent topics in Deepika Calidas's work include RNA Research and Splicing (4 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and RNA modifications and cancer (3 papers). Deepika Calidas is often cited by papers focused on RNA Research and Splicing (4 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and RNA modifications and cancer (3 papers). Deepika Calidas collaborates with scholars based in United States, United Kingdom and Taiwan. Deepika Calidas's co-authors include Jarrett Smith, Helen Schmidt, Géraldine Seydoux, Dominique Rasoloson, Alexandre Paix, Tu Lu, Bramwell G. Lambrus, Jennifer T. Wang, Bi‐Chang Chen and Eric Betzig and has published in prestigious journals such as Genetics, The FASEB Journal and eLife.

In The Last Decade

Deepika Calidas

6 papers receiving 699 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Regulation of RNA granule dynamics by phosphorylation of serine-rich, intrinsically disordered proteins in C. elegans

2014 294 citations Jennifer T. Wang, Jarrett Smith et al. eLife profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Deepika Calidas United States	5	639	222	77	68	46	6	708
Tu Lu United States	6	502 0.8×	211 1.0×	79 1.0×	51 0.8×	15 0.3×	7	572
Chih-Yung S. Lee United States	9	361 0.6×	169 0.8×	56 0.7×	47 0.7×	17 0.4×	11	429
Julia Tischler United Kingdom	5	574 0.9×	245 1.1×	37 0.5×	154 2.3×	10 0.2×	7	719
Jarrett Smith United States	10	1.3k 2.0×	266 1.2×	92 1.2×	193 2.8×	79 1.7×	14	1.4k
Christian A Grove United States	8	661 1.0×	337 1.5×	24 0.3×	83 1.2×	12 0.3×	11	812
Thomas M. Brodigan United States	9	540 0.8×	271 1.2×	35 0.5×	36 0.5×	5 0.1×	10	646
Michelle A. Mondoux United States	11	287 0.4×	135 0.6×	31 0.4×	25 0.4×	21 0.5×	15	433
Fabrice Caudron Switzerland	10	637 1.0×	64 0.3×	301 3.9×	48 0.7×	17 0.4×	17	700
Caroline L. Dahlberg United States	10	363 0.6×	80 0.4×	43 0.6×	51 0.8×	4 0.1×	23	512
Coralia Pérez Spain	12	292 0.5×	29 0.1×	58 0.8×	102 1.5×	13 0.3×	16	477

Countries citing papers authored by Deepika Calidas

Since Specialization

Citations

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

Fields of papers citing papers by Deepika Calidas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepika Calidas

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Seydoux, Géraldine, Jarrett Smith, Deepika Calidas, Helen Schmidt, & Dominique Rasoloson. (2017). Organelles without membranes: intrinsically‐disordered proteins bring order to the cytoplasm. The FASEB Journal. 31(S1). 1 indexed citations

2.

Smith, Jarrett, Deepika Calidas, Helen Schmidt, et al.. (2016). Spatial patterning of P granules by RNA-induced phase separation of the intrinsically-disordered protein MEG-3. eLife. 5. 171 indexed citations

3.

Calidas, Deepika, et al.. (2014). The N-terminal extension of S12 influences small ribosomal subunit assembly in Escherichia coli. RNA. 20(3). 321–330. 17 indexed citations

4.

Paix, Alexandre, Yuemeng Wang, Harold E. Smith, et al.. (2014). Scalable and Versatile Genome Editing Using Linear DNAs with Microhomology to Cas9 Sites inCaenorhabditis elegans. Genetics. 198(4). 1347–1356. 217 indexed citations

5.

Wang, Jennifer T., Jarrett Smith, Bi‐Chang Chen, et al.. (2014). Regulation of RNA granule dynamics by phosphorylation of serine-rich, intrinsically disordered proteins in C. elegans. eLife. 3. e04591–e04591. 294 indexed citations breakdown →

6.

Calidas, Deepika & Gloria M. Culver. (2010). Interdependencies govern multidomain architecture in ribosomal small subunit assembly. RNA. 17(2). 263–277. 8 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.

Explore authors with similar magnitude of impact