Ganesh Sriram

1.5k total citations
48 papers, 1.1k citations indexed

About

Ganesh Sriram is a scholar working on Molecular Biology, Plant Science and Epidemiology. According to data from OpenAlex, Ganesh Sriram has authored 48 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 7 papers in Plant Science and 5 papers in Epidemiology. Recurrent topics in Ganesh Sriram's work include Microbial Metabolic Engineering and Bioproduction (20 papers), Metabolomics and Mass Spectrometry Studies (11 papers) and Metabolism, Diabetes, and Cancer (6 papers). Ganesh Sriram is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (20 papers), Metabolomics and Mass Spectrometry Studies (11 papers) and Metabolism, Diabetes, and Cancer (6 papers). Ganesh Sriram collaborates with scholars based in United States, India and Russia. Ganesh Sriram's co-authors include William J. Bean, Robert G. Webster, Katrina M. Dipple, Jacqueline V. Shanks, D. Bruce Fulton, James C. Liao, Virginia S. Hinshaw, Edward R.B. McCabe, Julián A. Martínez-Agosto and Vidya Iyer and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and PLANT PHYSIOLOGY.

In The Last Decade

Ganesh Sriram

47 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ganesh Sriram United States 17 705 242 167 98 95 48 1.1k
Alice Schroeder United States 23 971 1.4× 128 0.5× 206 1.2× 42 0.4× 75 0.8× 60 2.4k
Andrea Wagner Germany 21 770 1.1× 133 0.5× 265 1.6× 44 0.4× 302 3.2× 38 1.3k
Angelo Bolchi Italy 24 735 1.0× 272 1.1× 449 2.7× 45 0.5× 38 0.4× 47 1.4k
Vladimir V. Gorn Russia 10 756 1.1× 147 0.6× 84 0.5× 72 0.7× 23 0.2× 28 1.2k
Xin Yao China 17 1.2k 1.8× 115 0.5× 58 0.3× 78 0.8× 26 0.3× 41 1.7k
Elizabeth M. Ryan United States 10 557 0.8× 56 0.2× 207 1.2× 73 0.7× 74 0.8× 14 992
André Wegner Luxembourg 16 860 1.2× 182 0.8× 86 0.5× 90 0.9× 53 0.6× 24 1.5k
Mirtha M. Flawiá Argentina 26 991 1.4× 668 2.8× 158 0.9× 31 0.3× 46 0.5× 52 1.7k
Noriko Nakagawa Japan 23 1.2k 1.7× 83 0.3× 81 0.5× 81 0.8× 138 1.5× 85 1.6k
Francesco M. Mancuso Spain 19 789 1.1× 100 0.4× 218 1.3× 97 1.0× 142 1.5× 42 1.6k

Countries citing papers authored by Ganesh Sriram

Since Specialization
Citations

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

Fields of papers citing papers by Ganesh Sriram

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ganesh Sriram

This figure shows the co-authorship network connecting the top 25 collaborators of Ganesh Sriram. A scholar is included among the top collaborators of Ganesh Sriram 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 Ganesh Sriram. Ganesh Sriram 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
1.
Sriram, Ganesh, et al.. (2022). Isotope-assisted metabolic flux analysis as an equality-constrained nonlinear program for improved scalability and robustness. PLoS Computational Biology. 18(3). e1009831–e1009831. 6 indexed citations
2.
Sriram, Ganesh, et al.. (2020). NetFlow: A tool for isolating carbon flows in genome-scale metabolic networks. Metabolic Engineering Communications. 12. e00154–e00154. 3 indexed citations
3.
Sriram, Ganesh, Wojciech Jankowski, Canan Kasikara, et al.. (2014). Iterative tyrosine phosphorylation controls non-canonical domain utilization in Crk. Oncogene. 34(32). 4260–4269. 8 indexed citations
4.
Rahib, Lola, et al.. (2014). Mathematical modeling of the insulin signal transduction pathway for prediction of insulin sensitivity from expression data. Molecular Genetics and Metabolism. 114(1). 66–72. 12 indexed citations
5.
Misra, Ashish, et al.. (2013). Flux and reflux: metabolite reflux in plant suspension cells and its implications for isotope-assisted metabolic flux analysis. Molecular BioSystems. 10(6). 1496–1508. 17 indexed citations
6.
Misra, Ashish & Ganesh Sriram. (2013). Network component analysis provides quantitative insights on an Arabidopsis transcription factor-gene regulatory network. BMC Systems Biology. 7(1). 126–126. 12 indexed citations
7.
Joffe, Max E., et al.. (2013). Nuclear Magnetic Resonance Methods for Metabolic Fluxomics. Methods in molecular biology. 985. 335–351. 9 indexed citations
8.
Misra, Ashish, et al.. (2013). Metabolic analyses elucidate non-trivial gene targets for amplifying dihydroartemisinic acid production in yeast. Frontiers in Microbiology. 4. 200–200. 11 indexed citations
9.
Zheng, Yuting, Andrew Quinn, & Ganesh Sriram. (2013). Experimental evidence and isotopomer analysis of mixotrophic glucose metabolism in the marine diatom Phaeodactylum tricornutum. Microbial Cell Factories. 12(1). 109–109. 37 indexed citations
10.
Simons, Margaret, Ashish Misra, & Ganesh Sriram. (2013). Genome-Scale Models of Plant Metabolism. Methods in molecular biology. 1083. 213–230. 10 indexed citations
11.
12.
Rahib, Lola, et al.. (2009). Transcriptomic and network component analysis of glycerol kinase in skeletal muscle using a mouse model of glycerol kinase deficiency. Molecular Genetics and Metabolism. 96(3). 106–112. 16 indexed citations
13.
Sriram, Ganesh, Vidya Iyer, D. Bruce Fulton, & Jacqueline V. Shanks. (2007). Identification of hexose hydrolysis products in metabolic flux analytes: A case study of levulinic acid in plant protein hydrolysate. Metabolic Engineering. 9(5-6). 442–451. 19 indexed citations
14.
Sriram, Ganesh, D. Bruce Fulton, & Jacqueline V. Shanks. (2007). Flux quantification in central carbon metabolism of Catharanthus roseus hairy roots by 13C labeling and comprehensive bondomer balancing. Phytochemistry. 68(16-18). 2243–2257. 50 indexed citations
15.
Sriram, Ganesh, et al.. (2007). Global metabolic effects of glycerol kinase overexpression in rat hepatoma cells. Molecular Genetics and Metabolism. 93(2). 145–159. 32 indexed citations
16.
Sriram, Ganesh, et al.. (2006). Determination of Biomass Composition of Catharanthusroseus Hairy Roots for Metabolic Flux Analysis. Biotechnology Progress. 22(6). 1659–1663. 12 indexed citations
17.
Sriram, Ganesh, Julián A. Martínez-Agosto, Edward R.B. McCabe, James C. Liao, & Katrina M. Dipple. (2005). Single-Gene Disorders: What Role Could Moonlighting Enzymes Play?. The American Journal of Human Genetics. 76(6). 911–924. 170 indexed citations
18.
19.
Sriram, Ganesh. (2004). Improvements in metabolic flux analysis using carbon bond labeling experiments: bondomer balancing and Boolean function mapping. Metabolic Engineering. 6(2). 116–132. 35 indexed citations
20.
Webster, Robert G., Virginia S. Hinshaw, William J. Bean, & Ganesh Sriram. (1980). Influenza viruses: transmission between species. Philosophical transactions of the Royal Society of London. Series B, Biological sciences. 288(1029). 439–447. 13 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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