David J. Baumler

1.6k total citations
43 papers, 1.2k citations indexed

About

David J. Baumler is a scholar working on Molecular Biology, Food Science and Endocrinology. According to data from OpenAlex, David J. Baumler has authored 43 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 10 papers in Food Science and 9 papers in Endocrinology. Recurrent topics in David J. Baumler's work include Genomics and Phylogenetic Studies (6 papers), Escherichia coli research studies (6 papers) and Bacteriophages and microbial interactions (6 papers). David J. Baumler is often cited by papers focused on Genomics and Phylogenetic Studies (6 papers), Escherichia coli research studies (6 papers) and Bacteriophages and microbial interactions (6 papers). David J. Baumler collaborates with scholars based in United States, India and Mexico. David J. Baumler's co-authors include Charles W. Kaspar, Sang Ho Choi, Kamal Dev, Anuradha Sourirajan, Kwang Cheol Jeong, Rajan Rolta, Deeksha Salaria, Jillian F. Banfield, Martha M. Vestling and Timothy J. Johnson and has published in prestigious journals such as PLoS ONE, Applied and Environmental Microbiology and Food Chemistry.

In The Last Decade

David J. Baumler

42 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
David J. Baumler United States 18 447 250 169 165 148 43 1.2k
Ryan C. Fink United States 23 478 1.1× 400 1.6× 367 2.2× 267 1.6× 137 0.9× 36 1.5k
Jingjing Sun China 14 567 1.3× 144 0.6× 83 0.5× 183 1.1× 118 0.8× 29 1.3k
Hee Jung Lee South Korea 20 438 1.0× 123 0.5× 169 1.0× 154 0.9× 137 0.9× 76 1.2k
Wai-Fong Yin Malaysia 20 944 2.1× 253 1.0× 229 1.4× 355 2.2× 159 1.1× 30 1.6k
David Daudé France 18 766 1.7× 82 0.3× 196 1.2× 137 0.8× 103 0.7× 43 1.2k
Anthony R. Ball United States 12 557 1.2× 450 1.8× 120 0.7× 571 3.5× 187 1.3× 12 2.1k
Yunhui Zhang China 22 774 1.7× 134 0.5× 81 0.5× 55 0.3× 105 0.7× 67 1.3k
Imtiaj Hasan Bangladesh 24 600 1.3× 103 0.4× 168 1.0× 120 0.7× 72 0.5× 76 1.5k
Emanuele Bosi Italy 21 705 1.6× 102 0.4× 230 1.4× 105 0.6× 312 2.1× 57 1.3k
Yoshimitsu Masuda Japan 30 667 1.5× 696 2.8× 135 0.8× 185 1.1× 470 3.2× 136 2.4k

Countries citing papers authored by David J. Baumler

Since Specialization
Citations

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

Fields of papers citing papers by David J. Baumler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Baumler. 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 David J. Baumler. The network helps show where David J. Baumler may publish in the future.

Co-authorship network of co-authors of David J. Baumler

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Baumler. A scholar is included among the top collaborators of David J. Baumler 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 David J. Baumler. David J. Baumler 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.
Bernau, Vivian, Anna McCormick, Michael B. Kantar, et al.. (2023). Population structure in diverse pepper (Capsicum spp.) accessions. BMC Research Notes. 16(1). 20–20. 7 indexed citations
2.
Mao, Qingqing, Juer Liu, Dongjie Chen, et al.. (2021). Identification of Quinone Degradation as a Triggering Event for Intense Pulsed Light-Elicited Metabolic Changes in Escherichia coli by Metabolomic Fingerprinting. Metabolites. 11(2). 102–102. 9 indexed citations
3.
Rolta, Rajan, Deeksha Salaria, Bhanu Sharma, et al.. (2021). Phytocompounds of Rheum emodi, Thymus serpyllum, and Artemisia annua Inhibit Spike Protein of SARS-CoV-2 Binding to ACE2 Receptor: In Silico Approach. Current Pharmacology Reports. 7(4). 135–149. 70 indexed citations
4.
Rolta, Rajan, Rohitash Yadav, Deeksha Salaria, et al.. (2020). In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: an approach to prevent virus assembly. Journal of Biomolecular Structure and Dynamics. 39(18). 7017–7034. 92 indexed citations
5.
Rolta, Rajan, Deeksha Salaria, Vikas Kumar, et al.. (2020). Molecular docking studies of phytocompounds of Rheum emodi Wall with proteins responsible for antibiotic resistance in bacterial and fungal pathogens: in silico approach to enhance the bio-availability of antibiotics. Journal of Biomolecular Structure and Dynamics. 40(8). 3789–3803. 29 indexed citations
6.
Chen, Dongjie, Peng Peng, Min Min, et al.. (2020). Effects of intense pulsed light and gamma irradiation on Bacillus cereus spores in mesquite pod flour. Food Chemistry. 344. 128675–128675. 14 indexed citations
7.
Chen, Dongjie, Peng Peng, Yanling Cheng, et al.. (2020). Catalytic intense pulse light inactivation of Cronobacter sakazakii and other pathogens in non-fat dry milk and wheat flour. Food Chemistry. 332. 127420–127420. 15 indexed citations
8.
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10.
Dev, Kamal, Paul Chen, Chi Chen, et al.. (2019). Evaluation of Methods for Inoculating Dry Powder Foods with Salmonella enterica, Enterococcus faecium, or Cronobacter sakazakii. Journal of Food Protection. 82(6). 1082–1088. 18 indexed citations
11.
Sharma, Parul, et al.. (2018). Identification of thermophilic Flavobacterium and Anoxybacillus in unexplored tatapani hot spring of Kishtwar District of Jammu and Kashmir: A North Western Himalayan State. 12(3). 245–256. 1 indexed citations
12.
Baumler, David J., et al.. (2018). Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes. PLoS ONE. 13(6). e0198584–e0198584. 6 indexed citations
13.
14.
Kantar, Michael B., Justin Anderson, Sarah Lucht, et al.. (2016). Vitamin Variation in Capsicum Spp. Provides Opportunities to Improve Nutritional Value of Human Diets. PLoS ONE. 11(8). e0161464–e0161464. 92 indexed citations
15.
Baumler, David J., Bing Ma, Jennifer L. Reed, & Nicole T. Perna. (2013). Inferring ancient metabolism using ancestral core metabolic models of enterobacteria. BMC Systems Biology. 7(1). 46–46. 13 indexed citations
16.
Baumler, David J., et al.. (2011). The evolution of metabolic networks of E. coli. BMC Systems Biology. 5(1). 182–182. 54 indexed citations
17.
Baumler, David J., et al.. (2007). Production of methanethiol and volatile sulfur compounds by the archaeon “Ferroplasma acidarmanus”. Extremophiles. 11(6). 841–851. 17 indexed citations
18.
Jeong, Kwangcheol Casey, David J. Baumler, & Charles W. Kaspar. (2006). dps expression in Escherichia coli O157:H7 requires an extended −10 region and is affected by the cAMP receptor protein. Biochimica et Biophysica Acta (BBA) - Gene Structure and Expression. 1759(1-2). 51–59. 18 indexed citations
19.
Baumler, David J., et al.. (2006). Enhancement of Acid Tolerance in Zymomonas mobilis by a Proton-Buffering Peptide. Applied Biochemistry and Biotechnology. 134(1). 15–26. 13 indexed citations
20.
Macalady, Jennifer L., et al.. (2004). Tetraether-linked membrane monolayers in Ferroplasma spp: a key to survival in acid. Extremophiles. 8(5). 411–419. 123 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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