Vaskar Mukherjee

709 total citations
8 papers, 513 citations indexed

About

Vaskar Mukherjee is a scholar working on Molecular Biology, Food Science and Biomedical Engineering. According to data from OpenAlex, Vaskar Mukherjee has authored 8 papers receiving a total of 513 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Food Science and 5 papers in Biomedical Engineering. Recurrent topics in Vaskar Mukherjee's work include Fungal and yeast genetics research (7 papers), Biofuel production and bioconversion (5 papers) and Fermentation and Sensory Analysis (5 papers). Vaskar Mukherjee is often cited by papers focused on Fungal and yeast genetics research (7 papers), Biofuel production and bioconversion (5 papers) and Fermentation and Sensory Analysis (5 papers). Vaskar Mukherjee collaborates with scholars based in Belgium, Sweden and United States. Vaskar Mukherjee's co-authors include Johan M. Thevelein, Kevin J. Verstrepen, Bart Lievens, Sylvester Holt, María R. Foulquié-Moreno, Guido Aerts, Stefan Ruyters, Kris Willems, Alex Verplaetse and Jan Steensels and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Microbiology and Biotechnology and Food Microbiology.

In The Last Decade

Vaskar Mukherjee

8 papers receiving 503 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vaskar Mukherjee Belgium 6 328 289 247 124 68 8 513
Esther Meersman Belgium 9 361 1.1× 511 1.8× 148 0.6× 184 1.5× 93 1.4× 9 682
Sofia Dashko Netherlands 8 335 1.0× 243 0.8× 87 0.4× 139 1.1× 50 0.7× 11 512
Martina Picca Nicolino Belgium 3 305 0.9× 240 0.8× 128 0.5× 123 1.0× 59 0.9× 3 417
Sebastián N. Mendoza Chile 11 400 1.2× 143 0.5× 154 0.6× 66 0.5× 26 0.4× 18 513
Yoshinori Wakai Japan 14 293 0.9× 355 1.2× 81 0.3× 202 1.6× 103 1.5× 43 572
C. A. Magnus Canada 8 296 0.9× 320 1.1× 166 0.7× 106 0.9× 75 1.1× 10 478
Angus H. Forgan Australia 8 382 1.2× 444 1.5× 77 0.3× 336 2.7× 39 0.6× 10 590
Fernanda Cristina Bezerra Leite Brazil 12 279 0.9× 252 0.9× 167 0.7× 108 0.9× 22 0.3× 18 406
Yoshifumi Kiyokawa Japan 10 199 0.6× 242 0.8× 51 0.2× 158 1.3× 66 1.0× 26 390
Carla Pataro Brazil 7 152 0.5× 266 0.9× 69 0.3× 80 0.6× 24 0.4× 8 324

Countries citing papers authored by Vaskar Mukherjee

Since Specialization
Citations

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

Fields of papers citing papers by Vaskar Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vaskar Mukherjee

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

All Works

8 of 8 papers shown
1.
Mukherjee, Vaskar, et al.. (2023). CRISPRi screen highlights chromatin regulation to be involved in formic acid tolerance in Saccharomyces cerevisiae. SHILAP Revista de lepidopterología. 3(2). 100076–100076. 3 indexed citations
2.
Mukherjee, Vaskar, Ulrika Lind, Robert P. St.Onge, Anders Blomberg, & Yvonne Nygård. (2021). A CRISPR Interference Screen of Essential Genes Reveals that Proteasome Regulation Dictates Acetic Acid Tolerance in Saccharomyces cerevisiae. mSystems. 6(4). e0041821–e0041821. 24 indexed citations
3.
Holt, Sylvester, Vaskar Mukherjee, Bart Lievens, Kevin J. Verstrepen, & Johan M. Thevelein. (2017). Bioflavoring by non-conventional yeasts in sequential beer fermentations. Food Microbiology. 72. 55–66. 139 indexed citations
4.
Mukherjee, Vaskar, et al.. (2017). Phenotypic landscape of non-conventional yeast species for different stress tolerance traits desirable in bioethanol fermentation. Biotechnology for Biofuels. 10(1). 216–216. 90 indexed citations
5.
Mukherjee, Vaskar, et al.. (2015). Looking beyondSaccharomyces: the potential of non-conventional yeast species for desirable traits in bioethanol fermentation. FEMS Yeast Research. 15(6). fov053–fov053. 140 indexed citations
6.
Ruyters, Stefan, Vaskar Mukherjee, Kevin J. Verstrepen, et al.. (2014). Assessing the potential of wild yeasts for bioethanol production. Journal of Industrial Microbiology & Biotechnology. 42(1). 39–48. 55 indexed citations
7.
Mukherjee, Vaskar, Jan Steensels, Bart Lievens, et al.. (2014). Phenotypic evaluation of natural and industrial Saccharomyces yeasts for different traits desirable in industrial bioethanol production. Applied Microbiology and Biotechnology. 98(22). 9483–9498. 61 indexed citations
8.
Mukherjee, Vaskar, Jan Steensels, Ilse Van De Voorde, et al.. (2013). High throughput screening of yeast strains for desirable stress tolerant traits for bioethanol production. Lirias (KU Leuven). 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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2026