Sankar Mohan

3.5k total citations
43 papers, 1.9k citations indexed

About

Sankar Mohan is a scholar working on Organic Chemistry, Molecular Biology and Epidemiology. According to data from OpenAlex, Sankar Mohan has authored 43 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Organic Chemistry, 17 papers in Molecular Biology and 10 papers in Epidemiology. Recurrent topics in Sankar Mohan's work include Carbohydrate Chemistry and Synthesis (16 papers), Influenza Virus Research Studies (8 papers) and Enzyme Production and Characterization (8 papers). Sankar Mohan is often cited by papers focused on Carbohydrate Chemistry and Synthesis (16 papers), Influenza Virus Research Studies (8 papers) and Enzyme Production and Characterization (8 papers). Sankar Mohan collaborates with scholars based in Canada, United States and Mexico. Sankar Mohan's co-authors include Bernardine M. Pinto, B. Mario Pinto, David R. Rose, Lyann Sim, Kumarasamy Jayakanthan, Ajay Pandita, Hassan Y. Naim, Zora Modrušan, Celina Sanchez Rivers and Eva Lin and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Sankar Mohan

42 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sankar Mohan Canada 23 842 499 360 339 310 43 1.9k
Nam Doo Kim South Korea 32 1.8k 2.1× 454 0.9× 384 1.1× 200 0.6× 71 0.2× 102 2.9k
Amareshwar T.K. Singh United States 17 1.2k 1.5× 208 0.4× 458 1.3× 123 0.4× 120 0.4× 32 2.3k
A.R.M. Ruhul Amin United States 28 1.6k 1.9× 168 0.3× 608 1.7× 179 0.5× 89 0.3× 62 3.0k
Daniel V. LaBarbera United States 24 726 0.9× 184 0.4× 521 1.4× 102 0.3× 475 1.5× 54 1.9k
My‐Hanh Lam United States 21 857 1.0× 238 0.5× 388 1.1× 68 0.2× 210 0.7× 33 2.0k
Dharmalingam Subramaniam United States 29 1.8k 2.2× 153 0.3× 635 1.8× 190 0.6× 120 0.4× 68 2.9k
Thambi Dorai United States 23 1.4k 1.6× 140 0.3× 342 0.9× 322 0.9× 69 0.2× 46 2.2k
Gilda G. Hillman United States 27 883 1.0× 81 0.2× 602 1.7× 435 1.3× 110 0.4× 79 2.4k
Hong Seok Choi South Korea 30 1.6k 1.9× 299 0.6× 522 1.4× 90 0.3× 73 0.2× 88 2.6k
Claudia Ceci Italy 15 1.2k 1.4× 172 0.3× 444 1.2× 134 0.4× 46 0.1× 23 2.1k

Countries citing papers authored by Sankar Mohan

Since Specialization
Citations

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

Fields of papers citing papers by Sankar Mohan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sankar Mohan

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

All Works

20 of 20 papers shown
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Sukumaran, Sunil K., Karen K. Yee, Shusuke Iwata, et al.. (2016). Taste cell-expressed α-glucosidase enzymes contribute to gustatory responses to disaccharides. Proceedings of the National Academy of Sciences. 113(21). 6035–6040. 83 indexed citations
4.
Mohan, Sankar, et al.. (2015). Mechanism-based candidate inhibitors of uridine diphosphate galactopyranose mutase (UGM). Carbohydrate Research. 419. 1–7. 3 indexed citations
5.
Spoerke, Jill M., Carol O’Brien, Ling Huw, et al.. (2012). Phosphoinositide 3-Kinase (PI3K) Pathway Alterations Are Associated with Histologic Subtypes and Are Predictive of Sensitivity to PI3K Inhibitors in Lung Cancer Preclinical Models. Clinical Cancer Research. 18(24). 6771–6783. 149 indexed citations
6.
Vitari, Alberto C., Kevin G. Leong, Kim Newton, et al.. (2011). COP1 is a tumour suppressor that causes degradation of ETS transcription factors. Nature. 474(7351). 403–406. 138 indexed citations
7.
Niikura, Masahiro, et al.. (2011). Replication inhibition activity of carbocycles related to oseltamivir on influenza A virus in vitro. Antiviral Research. 90(3). 160–163. 14 indexed citations
8.
Fernández‐Herrera, María A., Hugo López‐Muñoz, Sankar Mohan, et al.. (2011). Synthesis and biological evaluation of the glycoside (25R)-3β,16β-diacetoxy-22-oxocholest-5-en-26-yl β-d-glucopyranoside: A selective anticancer agent in cervicouterine cell lines. European Journal of Medicinal Chemistry. 46(9). 3877–3886. 24 indexed citations
9.
Jones, Kyra, Lyann Sim, Sankar Mohan, et al.. (2011). Mapping the intestinal alpha-glucogenic enzyme specificities of starch digesting maltase-glucoamylase and sucrase-isomaltase. Bioorganic & Medicinal Chemistry. 19(13). 3929–3934. 72 indexed citations
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Mohan, Sankar & B. Mario Pinto. (2010). Towards the elusive structure of kotalanol, a naturally occurring glucosidase inhibitor. Natural Product Reports. 27(4). 481–481. 16 indexed citations
12.
Fernández‐Herrera, María A., Sankar Mohan, Hugo López‐Muñoz, et al.. (2010). Synthesis of the steroidal glycoside (25R)-3β,16β-diacetoxy-12,22-dioxo-5α-cholestan-26-yl β-d-glucopyranoside and its anti-cancer properties on cervicouterine HeLa, CaSki, and ViBo cells. European Journal of Medicinal Chemistry. 45(11). 4827–4837. 29 indexed citations
13.
Sim, Lyann, et al.. (2010). Structural Basis for Substrate Selectivity in Human Maltase-Glucoamylase and Sucrase-Isomaltase N-terminal Domains. Journal of Biological Chemistry. 285(23). 17763–17770. 190 indexed citations
14.
Lin, Eva, Li Li, Yinghui Guan, et al.. (2009). Exon Array Profiling Detects EML4-ALK Fusion in Breast, Colorectal, and Non–Small Cell Lung Cancers. Molecular Cancer Research. 7(9). 1466–1476. 231 indexed citations
15.
Modrek, Barmak, Lin Ge, Ajay Pandita, et al.. (2009). Oncogenic Activating Mutations Are Associated with Local Copy Gain. Molecular Cancer Research. 7(8). 1244–1252. 51 indexed citations
16.
Mohan, Sankar, Lyann Sim, David R. Rose, & Bernardine M. Pinto. (2007). Synthesis of S-alkylated sulfonium-ions and their glucosidase inhibitory activities against recombinant human maltase glucoamylase. Carbohydrate Research. 342(7). 901–912. 28 indexed citations
17.
Mohan, Sankar & B. Mario Pinto. (2007). Zwitterionic glycosidase inhibitors: salacinol and related analogues. Carbohydrate Research. 342(12-13). 1551–1580. 95 indexed citations
18.
Landis, Charles, Kosho Yamanouchi, Hongchao Zhou, et al.. (2006). Noninvasive evaluation of liver repopulation by transplanted hepatocytes using 31P MRS imaging in mice. Hepatology. 44(5). 1250–1258. 21 indexed citations
19.
Guha, Chandan, Sankar Mohan, Namita Roy‐Chowdhury, & Jayanta Roy‐Chowdhury. (2004). Cell Culture and Animal Models of Viral Hepatitis. Part I: Hepatitis B. Lab Animal. 33(7). 37–46. 22 indexed citations
20.
Mohan, Sankar & Robert D. Burk. (2003). von Hippel–Lindau protein complex is regulated by cell density. Oncogene. 22(34). 5270–5280. 10 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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