Jon M. Sutter

1.5k total citations
18 papers, 1.2k citations indexed

About

Jon M. Sutter is a scholar working on Computational Theory and Mathematics, Spectroscopy and Molecular Biology. According to data from OpenAlex, Jon M. Sutter has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computational Theory and Mathematics, 9 papers in Spectroscopy and 5 papers in Molecular Biology. Recurrent topics in Jon M. Sutter's work include Analytical Chemistry and Chromatography (8 papers), Computational Drug Discovery Methods (8 papers) and Advanced Chemical Sensor Technologies (5 papers). Jon M. Sutter is often cited by papers focused on Analytical Chemistry and Chromatography (8 papers), Computational Drug Discovery Methods (8 papers) and Advanced Chemical Sensor Technologies (5 papers). Jon M. Sutter collaborates with scholars based in United States, France and Austria. Jon M. Sutter's co-authors include John H. Kalivas, Peter C. Jurs, Jiabo Li, Patrick Lang, P. C. Jurs, Johannes Kirchmair, Tedman Ehlers, Adrian P. Stevens, Hugues‐Olivier Bertrand and Jamel Meslamani and has published in prestigious journals such as Analytical Chemistry, Analytica Chimica Acta and Biosensors and Bioelectronics.

In The Last Decade

Jon M. Sutter

18 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
Jon M. Sutter United States 15 531 334 316 314 252 18 1.2k
P. C. Jurs United States 24 509 1.0× 404 1.2× 732 2.3× 344 1.1× 551 2.2× 52 1.8k
Bert Skagerberg Sweden 17 486 0.9× 654 2.0× 263 0.8× 579 1.8× 188 0.7× 28 1.7k
C.B. Lucasius Netherlands 19 272 0.5× 455 1.4× 237 0.8× 222 0.7× 192 0.8× 27 1.3k
Botao Fan China 25 737 1.4× 300 0.9× 422 1.3× 538 1.7× 218 0.9× 78 1.9k
Mohsen Kompany‐Zareh Iran 20 127 0.2× 378 1.1× 161 0.5× 364 1.2× 284 1.1× 102 1.4k
Sérgio Clementi Italy 22 922 1.7× 483 1.4× 458 1.4× 722 2.3× 140 0.6× 110 2.2k
Annick Panaye France 18 510 1.0× 172 0.5× 361 1.1× 337 1.1× 136 0.5× 62 1.2k
D.L. Massart Belgium 22 105 0.2× 517 1.5× 281 0.9× 169 0.5× 210 0.8× 47 1.2k
Walter Lindberg Sweden 13 83 0.2× 589 1.8× 367 1.2× 181 0.6× 300 1.2× 26 1.2k
Zhuoyong Zhang China 23 107 0.2× 520 1.6× 210 0.7× 291 0.9× 442 1.8× 99 2.0k

Countries citing papers authored by Jon M. Sutter

Since Specialization
Citations

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

Fields of papers citing papers by Jon M. Sutter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jon M. Sutter

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

All Works

18 of 18 papers shown
1.
Meslamani, Jamel, Jiabo Li, Jon M. Sutter, et al.. (2012). Protein–Ligand-Based Pharmacophores: Generation and Utility Assessment in Computational Ligand Profiling. Journal of Chemical Information and Modeling. 52(4). 943–955. 93 indexed citations
2.
Sutter, Jon M., et al.. (2011). New Features that Improve the Pharmacophore Tools from Accelrys. Current Computer - Aided Drug Design. 7(3). 173–180. 33 indexed citations
3.
Li, Jiabo, et al.. (2007). CAESAR:  A New Conformer Generation Algorithm Based on Recursive Buildup and Local Rotational Symmetry Consideration. Journal of Chemical Information and Modeling. 47(5). 1923–1932. 98 indexed citations
4.
5.
Toba, Samuel, Jayashree Srinivasan, Allister J. Maynard, & Jon M. Sutter. (2006). Using Pharmacophore Models To Gain Insight into Structural Binding and Virtual Screening:  An Application Study with CDK2 and Human DHFR. Journal of Chemical Information and Modeling. 46(2). 728–735. 36 indexed citations
6.
Walt, David R., Todd A. Dickinson, Joel White, et al.. (1998). Optical sensor arrays for odor recognition. Biosensors and Bioelectronics. 13(6). 697–699. 42 indexed citations
7.
Sutter, Jon M. & Peter C. Jurs. (1997). Neural Network Classification and Quantification of Organic Vapors Based on Fluorescence Data from a Fiber-Optic Sensor Array. Analytical Chemistry. 69(5). 856–862. 54 indexed citations
8.
Sutter, Jon M., et al.. (1997). Prediction of gas chromatographic retention indices of alkylbenzenes. Analytica Chimica Acta. 342(2-3). 113–122. 74 indexed citations
9.
Johnson, Stephen R., Jon M. Sutter, Peter C. Jurs, et al.. (1997). Identification of Multiple Analytes Using an Optical Sensor Array and Pattern Recognition Neural Networks. Analytical Chemistry. 69(22). 4641–4648. 60 indexed citations
10.
Wessel, Matthew D., Jon M. Sutter, & Peter C. Jurs. (1996). Prediction of Reduced Ion Mobility Constants of Organic Compounds from Molecular Structure. Analytical Chemistry. 68(23). 4237–4243. 34 indexed citations
11.
Sutter, Jon M. & Peter C. Jurs. (1996). Prediction of Aqueous Solubility for a Diverse Set of Heteroatom-Containing Organic Compounds Using a Quantitative Structure−Property Relationship. Journal of Chemical Information and Computer Sciences. 36(1). 100–107. 73 indexed citations
12.
Sutter, Jon M., et al.. (1995). Automated Descriptor Selection for Quantitative Structure-Activity Relationships Using Generalized Simulated Annealing. Journal of Chemical Information and Computer Sciences. 35(1). 77–84. 179 indexed citations
13.
Sutter, Jon M. & John H. Kalivas. (1993). Comparison of Forward Selection, Backward Elimination, and Generalized Simulated Annealing for Variable Selection. Microchemical Journal. 47(1-2). 60–66. 121 indexed citations
14.
Kalivas, John H., et al.. (1992). Computer‐generated multicomponent calibration designs for optimal analysis sample predictions. Journal of Chemometrics. 6(2). 85–96. 2 indexed citations
15.
Sutter, Jon M., John H. Kalivas, & Patrick Lang. (1992). Which principal components to utilize for principal component regression. Journal of Chemometrics. 6(4). 217–225. 92 indexed citations
16.
Sutter, Jon M. & John H. Kalivas. (1991). Convergence of generalized simulated annealing with variable step size with application towards parameter estimations of linear and nonlinear models. Analytical Chemistry. 63(20). 2383–2386. 30 indexed citations
17.
Kalivas, John H., et al.. (1990). Observations of trends for singular values and eigenvectors from library searching ultraviolet-visible spectra with spectral subtraction. Analytica Chimica Acta. 237. 223–232. 2 indexed citations
18.
Kalivas, John H., et al.. (1989). Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry. Analytical Chemistry. 61(18). 2024–2030. 177 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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