Shuba Gopal

3.2k total citations
11 papers, 425 citations indexed

About

Shuba Gopal is a scholar working on Molecular Biology, Social Psychology and Sociology and Political Science. According to data from OpenAlex, Shuba Gopal has authored 11 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 1 paper in Social Psychology and 1 paper in Sociology and Political Science. Recurrent topics in Shuba Gopal's work include RNA and protein synthesis mechanisms (5 papers), Genomics and Phylogenetic Studies (3 papers) and Genomics and Chromatin Dynamics (1 paper). Shuba Gopal is often cited by papers focused on RNA and protein synthesis mechanisms (5 papers), Genomics and Phylogenetic Studies (3 papers) and Genomics and Chromatin Dynamics (1 paper). Shuba Gopal collaborates with scholars based in United States and Spain. Shuba Gopal's co-authors include Terry Gaasterland, Monica Riley, Margrethe H. Serres, Ping Liang, Laila Alves Nahum, Clary B. Clish, Amy Deik, Franco Giulianini, Dong D. Wang and Kevin Bullock and has published in prestigious journals such as Circulation, Nature Genetics and Journal of Clinical Oncology.

In The Last Decade

Shuba Gopal

10 papers receiving 419 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuba Gopal United States	8	346	65	56	49	40	11	425
E. Anne Bergner United States	6	267 0.8×	51 0.8×	73 1.3×	53 1.1×	28 0.7×	8	523
Paulina Samczuk Poland	12	280 0.8×	69 1.1×	104 1.9×	58 1.2×	30 0.8×	18	441
Byung Hun Jeon South Korea	12	159 0.5×	34 0.5×	27 0.5×	61 1.2×	40 1.0×	22	437
Changlu Qi China	9	433 1.3×	36 0.6×	60 1.1×	23 0.5×	55 1.4×	19	539
Paul Lee United States	12	127 0.4×	37 0.6×	50 0.9×	56 1.1×	29 0.7×	22	466
Juliette Martin Switzerland	9	208 0.6×	46 0.7×	32 0.6×	41 0.8×	39 1.0×	13	328
Tim Hull United States	3	247 0.7×	23 0.4×	47 0.8×	48 1.0×	40 1.0×	4	367
Karolina Pietrowska Poland	12	229 0.7×	57 0.9×	28 0.5×	50 1.0×	52 1.3×	31	398
Clément Frainay France	11	434 1.3×	25 0.4×	106 1.9×	34 0.7×	60 1.5×	23	653
Rintu Kutum India	12	149 0.4×	30 0.5×	58 1.0×	68 1.4×	26 0.7×	25	361

Countries citing papers authored by Shuba Gopal

Since Specialization

Citations

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

Fields of papers citing papers by Shuba Gopal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuba Gopal

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

All Works

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11 of 11 papers shown

1.

Gopal, Shuba, et al.. (2023). Extend that “job honeymoon:” acknowledging it is hard to start a job can help. Strategic HR Review. 22(4). 110–114.

2.

Paynter, Nina P., Raji Balasubramanian, Franco Giulianini, et al.. (2018). Metabolic Predictors of Incident Coronary Heart Disease in Women. Circulation. 137(8). 841–853. 143 indexed citations

3.

Giannakis, Marios, Haoxin Li, Chelsea Jin, et al.. (2017). Metabolomic correlates of response in nivolumab-treated renal cell carcinoma and melanoma patients.. Journal of Clinical Oncology. 35(15_suppl). 3036–3036. 14 indexed citations

4.

Shao, Diane D., Aviad Tsherniak, Shuba Gopal, et al.. (2012). ATARiS: Computational quantification of gene suppression phenotypes from multisample RNAi screens. Genome Research. 23(4). 665–678. 78 indexed citations

5.

Gopal, Shuba, et al.. (2008). BioInformatics: A Computing Perspective. Medical Entomology and Zoology. 8 indexed citations

6.

Gopal, Shuba. (2008). Computational Prediction of RNA Editing Sites: Successes and Challenges Ahead. Current Bioinformatics. 3(3). 162–177. 1 indexed citations

7.

Thompson, James & Shuba Gopal. (2006). Genetic algorithm learning as a robust approach to RNA editing site prediction. BMC Bioinformatics. 7(1). 145–145. 12 indexed citations

8.

Gopal, Shuba, et al.. (2005). A computational investigation of kinetoplastid trans-splicing. Genome biology. 6(11). R95–R95. 21 indexed citations

9.

Serres, Margrethe H., Shuba Gopal, Laila Alves Nahum, et al.. (2001). A functional update of the Escherichia coliK-12 genome. Genome biology. 2(9). RESEARCH0035–RESEARCH0035. 104 indexed citations

10.

Gopal, Shuba, Mark Schroeder, Ursula Pieper, et al.. (2001). Homology-based annotation yields 1,042 new candidate genes in the Drosophila melanogaster genome. Nature Genetics. 27(3). 337–340. 43 indexed citations

11.

Gopal, Shuba. (2000). Mapping replication origins. Genome biology. 1(1). 1 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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