Thomas M. Ehrman

430 total citations
9 papers, 326 citations indexed

About

Thomas M. Ehrman is a scholar working on Molecular Biology, Pharmacology and Computational Theory and Mathematics. According to data from OpenAlex, Thomas M. Ehrman has authored 9 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Pharmacology and 4 papers in Computational Theory and Mathematics. Recurrent topics in Thomas M. Ehrman's work include Pharmacological Effects of Natural Compounds (5 papers), Computational Drug Discovery Methods (4 papers) and Synthesis and biological activity (3 papers). Thomas M. Ehrman is often cited by papers focused on Pharmacological Effects of Natural Compounds (5 papers), Computational Drug Discovery Methods (4 papers) and Synthesis and biological activity (3 papers). Thomas M. Ehrman collaborates with scholars based in United Kingdom and Italy. Thomas M. Ehrman's co-authors include David J. Barlow, Peter J. Hylands, Alessandro Buriani, E. Bosisio, Ivano Eberini, Silvia Paoletta, Dirk Wildeboer and Glyn B. Steventon and has published in prestigious journals such as Journal of Ethnopharmacology, Bioorganic & Medicinal Chemistry and Current Pharmaceutical Design.

In The Last Decade

Thomas M. Ehrman

9 papers receiving 316 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas M. Ehrman United Kingdom 7 175 141 107 62 59 9 326
Liansheng Qiao China 12 197 1.1× 83 0.6× 75 0.7× 51 0.8× 37 0.6× 44 378
Piar Ali Shar Pakistan 9 197 1.1× 141 1.0× 98 0.9× 67 1.1× 77 1.3× 21 368
Su‐Sen Chang Taiwan 8 190 1.1× 121 0.9× 64 0.6× 53 0.9× 35 0.6× 10 357
Praveen Kumar Pasala India 10 109 0.6× 84 0.6× 43 0.4× 52 0.8× 55 0.9× 53 352
Hong Ji China 14 272 1.6× 48 0.3× 94 0.9× 46 0.7× 55 0.9× 29 508
Lan-Ting Xin China 6 197 1.1× 43 0.3× 113 1.1× 81 1.3× 88 1.5× 8 353
Arumugam Madeswaran India 12 118 0.7× 98 0.7× 60 0.6× 83 1.3× 53 0.9× 36 378
Yuquan Zhou China 4 157 0.9× 153 1.1× 42 0.4× 45 0.7× 16 0.3× 6 362

Countries citing papers authored by Thomas M. Ehrman

Since Specialization
Citations

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

Fields of papers citing papers by Thomas M. Ehrman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas M. Ehrman. 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 Thomas M. Ehrman. The network helps show where Thomas M. Ehrman may publish in the future.

Co-authorship network of co-authors of Thomas M. Ehrman

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

All Works

9 of 9 papers shown
1.
Barlow, David J., Alessandro Buriani, Thomas M. Ehrman, et al.. (2012). In-silico studies in Chinese herbal medicines’ research: Evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date. Journal of Ethnopharmacology. 140(3). 526–534. 48 indexed citations
2.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2010). Phytochemical Informatics and Virtual Screening of Herbs Used in Chinese Medicine. Current Pharmaceutical Design. 16(15). 1785–1798. 10 indexed citations
3.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2010). In silico search for multi-target anti-inflammatories in Chinese herbs and formulas. Bioorganic & Medicinal Chemistry. 18(6). 2204–2218. 46 indexed citations
4.
Paoletta, Silvia, Glyn B. Steventon, Dirk Wildeboer, et al.. (2008). Screening of herbal constituents for aromatase inhibitory activity. Bioorganic & Medicinal Chemistry. 16(18). 8466–8470. 37 indexed citations
5.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2007). Virtual Screening of Chinese Herbs with Random Forest. Journal of Chemical Information and Modeling. 47(2). 264–278. 63 indexed citations
6.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2007). Phytochemical Informatics of Traditional Chinese Medicine and Therapeutic Relevance. Journal of Chemical Information and Modeling. 47(6). 2316–2334. 51 indexed citations
7.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2007). Virtual Screening of Chinese Herbs with Random Forest.. ChemInform. 38(24). 1 indexed citations
8.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2007). Phytochemical Databases of Chinese Herbal Constituents and Bioactive Plant Compounds with Known Target Specificities. Journal of Chemical Information and Modeling. 47(2). 254–263. 66 indexed citations
9.
Ehrman, Thomas M., David J. Barlow, & Peter J. Hylands. (2007). Phytochemical Databases of Chinese Herbal Constituents and Bioactive Plant Compounds with Known Target Specificities.. ChemInform. 38(24). 4 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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