D. Domine

930 total citations
28 papers, 636 citations indexed

About

D. Domine is a scholar working on Computational Theory and Mathematics, Spectroscopy and Analytical Chemistry. According to data from OpenAlex, D. Domine has authored 28 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Theory and Mathematics, 12 papers in Spectroscopy and 8 papers in Analytical Chemistry. Recurrent topics in D. Domine's work include Computational Drug Discovery Methods (14 papers), Analytical Chemistry and Chromatography (11 papers) and Spectroscopy and Chemometric Analyses (7 papers). D. Domine is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Analytical Chemistry and Chromatography (11 papers) and Spectroscopy and Chemometric Analyses (7 papers). D. Domine collaborates with scholars based in Italy, France and Netherlands. D. Domine's co-authors include James Devillers, W. Karcher, S. Bintein, Hélène Budzinski, Jacques Connan, P. Garrigues, M. Radke, M. Chastrette, Dennis Church and Cédric Merlot and has published in prestigious journals such as Geochimica et Cosmochimica Acta, The Science of The Total Environment and Chemosphere.

In The Last Decade

D. Domine

28 papers receiving 565 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Domine Italy 14 269 154 146 143 122 28 636
Daniel L. Vassilaros United States 8 33 0.1× 327 2.1× 136 0.9× 48 0.3× 359 2.9× 9 1.1k
Elisabete F. Dias Portugal 9 89 0.3× 151 1.0× 15 0.1× 138 1.0× 41 0.3× 14 587
I. Hazai Hungary 11 51 0.2× 67 0.4× 154 1.1× 112 0.8× 16 0.1× 30 437
Jamie Nuñez United States 13 70 0.3× 65 0.4× 27 0.2× 331 2.3× 43 0.4× 22 737
Yury Kostyukevich Russia 26 69 0.3× 369 2.4× 97 0.7× 565 4.0× 62 0.5× 103 1.7k
Kjell Tjessem Norway 12 23 0.1× 201 1.3× 29 0.2× 78 0.5× 101 0.8× 25 595
Franklin R. Guenther United States 13 26 0.1× 218 1.4× 33 0.2× 31 0.2× 130 1.1× 36 801
Armand Buchs Switzerland 15 15 0.1× 93 0.6× 180 1.2× 146 1.0× 7 0.1× 55 647
Pierrette Bouvier‐Navé France 17 40 0.1× 50 0.3× 320 2.2× 952 6.7× 6 0.0× 23 1.5k
Serge Neunlist France 16 10 0.0× 77 0.5× 490 3.4× 345 2.4× 18 0.1× 27 1.0k

Countries citing papers authored by D. Domine

Since Specialization
Citations

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

Fields of papers citing papers by D. Domine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Domine

This figure shows the co-authorship network connecting the top 25 collaborators of D. Domine. A scholar is included among the top collaborators of D. Domine 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 D. Domine. D. Domine 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.
Westen, Gerard J. P. van, et al.. (2016). Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound–Kinase Activities: A Way toward Selective Promiscuity by Design?. Journal of Chemical Information and Modeling. 56(9). 1654–1675. 35 indexed citations
2.
Merlot, Cédric, et al.. (2003). Chemical substructures in drug discovery. Drug Discovery Today. 8(13). 594–602. 58 indexed citations
3.
Devillers, James, et al.. (1998). Simulating Lipophilicity of Organic Molecules with a Back-Propagation Neural Network. Journal of Pharmaceutical Sciences. 87(9). 1086–1090. 24 indexed citations
4.
Domine, D., et al.. (1998). Nonlinear Neural Mapping Analysis of the Adverse Effects of Drugs. SAR and QSAR in environmental research. 8(1-2). 109–120. 4 indexed citations
5.
Devillers, James, et al.. (1998). Autocorrelation modeling of lipophilicity with a back-propagation neural network. European Journal of Medicinal Chemistry. 33(7-8). 659–664. 14 indexed citations
6.
Devillers, James, S. Bintein, & D. Domine. (1997). Modeling the Environmental Fate of Atrazine. SAR and QSAR in environmental research. 6(1-2). 63–79. 3 indexed citations
7.
Domine, D., James Devillers, D. Wienke, & L.M.C. Buydens. (1997). ART 2-A for Optimal Test Series Design in QSAR. Journal of Chemical Information and Computer Sciences. 37(1). 10–17. 10 indexed citations
8.
Devillers, James & D. Domine. (1997). Comparison of Reliability of log P Values Calculated from a Group Contribution Approach and from the Autocorrelation Method. SAR and QSAR in environmental research. 7(1-4). 195–232. 15 indexed citations
9.
Devillers, James, et al.. (1997). Prediction of Partition Coefficients (LOGPoct) Using Autocorrelation Descriptors. SAR and QSAR in environmental research. 7(1-4). 151–172. 26 indexed citations
10.
Devillers, James, S. Bintein, & D. Domine. (1996). Comparison of BCF models based on log P. Chemosphere. 33(6). 1047–1065. 77 indexed citations
11.
Devillers, James, D. Domine, & W. Karcher. (1996). Estimating then-Octanol/Water Partition Coefficients of Polycyclic Aromatic Compounds with Autologp (2.11). Polycyclic aromatic compounds. 11(1-4). 211–217. 3 indexed citations
12.
Devillers, James, S. Bintein, D. Domine, & W. Karcher. (1995). A General QSAR Model for Predicting the Toxicity of Organic Chemicals to Luminescent Bacteria (Microtox® test). SAR and QSAR in environmental research. 4(1). 29–38. 21 indexed citations
13.
Domine, D. & James Devillers. (1995). Nonlinear Multivariate SAR of Lepidoptera Pheromones. SAR and QSAR in environmental research. 4(1). 51–58. 3 indexed citations
14.
Devillers, James, D. Domine, & W. Karcher. (1995). Estimatingn-Octanol/Water Partition Coefficients from the Autocorrelation Method. SAR and QSAR in environmental research. 3(4). 301–306. 10 indexed citations
15.
Domine, D., James Devillers, & M. Chastrette. (1994). A Nonlinear Map of Substituent Constants for Selecting Test Series and Deriving Structure-Activity Relationships. II. Aliphatic Series. Journal of Medicinal Chemistry. 37(7). 981–987. 8 indexed citations
16.
Domine, D., James Devillers, & M. Chastrette. (1994). A Nonlinear Map of Substituent Constants for Selecting Test Series and Deriving Structure-Activity Relationships. I. Aromatic Series. Journal of Medicinal Chemistry. 37(7). 973–980. 6 indexed citations
17.
Devillers, James, D. Domine, & S. Bintein. (1994). Multivariate Analysis of the First 10 MEIC Chemicals. SAR and QSAR in environmental research. 2(4). 261–270. 7 indexed citations
18.
Domine, D., James Devillers, Philippe Garrigues, et al.. (1994). Chemometrical evaluation of the PAH contamination in the sediments of the Gulf of Lion (France). The Science of The Total Environment. 155(1). 9–24. 14 indexed citations
19.
Domine, D., James Devillers, M. Chastrette, & W. Karcher. (1993). Estimating Pesticide Field Half-lives from a Backpropagation Neural Network. SAR and QSAR in environmental research. 1(2-3). 211–219. 21 indexed citations
20.
Domine, D., James Devillers, M. Chastrette, & W. Karcher. (1992). Multivariate structure‐property relationships (MSPR) of pesticides. Pesticide Science. 35(1). 73–82. 15 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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