Milen Todorov

637 citations
22 papers · 320 indexed · h-index 11
Topics
Computational Drug Discovery Methods (13 papers)Carcinogens and Genotoxicity Assessment (5 papers)Effects and risks of endocrine disrupting chemicals (4 papers)

In The Last Decade

Milen Todorov

20 papers receiving 307 citations

Peers

Milen Todorov
Comparison fields: 5 of 72
  • Computational Theory and Mathematics 163
  • Molecular Biology 82
  • Cancer Research 71
  • Health, Toxicology and Mutagenesis 68
  • Plant Science 53
Replace Michael C. Laufersweiler with:
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Milen Todorov relative to Michael C. Laufersweiler United States Michael C. Laufersweiler's profile →
Citations per field
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Michael C. Laufersweiler · 1×
Citations per year

Countries citing papers authored by Milen Todorov

Since Specialization
Citations

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

Fields of papers citing papers by Milen Todorov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milen Todorov

This figure shows the co-authorship network connecting the top 25 collaborators of Milen Todorov. A scholar is included among the top collaborators of Milen Todorov 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 Milen Todorov. Milen Todorov 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
#WorkIndexed citations
1 2
2 16
3 4
4 8
5
IN SILICO IDENTIFICATION OF HUMAN PREGNANE X RECEPTOR ACTIVATORS
2
6
COMPUTATIONAL TOOLS FOR PREDICTION OF NUCLEAR RECEPTOR MEDIATED EFFECTS
5
7 18
8
A QSAR evaluation of glucocorticoid receptor binding
1
9 33
10 17
11 23
12 9
13 19
14 5
15 25
16 60
17 23
18 1
19 31
20 15

About Milen Todorov

Milen Todorov is a scholar working on Computational Theory and Mathematics, Human-Computer Interaction and Cancer Research, having authored 22 papers that have together received 320 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Carcinogens and Genotoxicity Assessment (5 papers) and Effects and risks of endocrine disrupting chemicals (4 papers). The work is most often cited by research in Chemical Health and Safety (7 citations), Computational Theory and Mathematics (163 citations) and Small Animals (44 citations). Milen Todorov has collaborated with scholars based in Bulgaria, United States and Japan. Frequent co-authors include Ovanes Mekenyan, Elard Jacob, Aynur O. Aptula, Gergana Dimitrova, P. Petkov, S. Dimitrov, Grace Patlewicz, Todor Pavlov, Erica Donner and Patricia K. Schmieder. Their work appears in journals such as Chemical Research in Toxicology, Journal of Chemical Information and Modeling and Bioorganic & Medicinal Chemistry Letters.

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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