Michael S. Lawless

626 total citations
23 papers, 345 citations indexed

About

Michael S. Lawless is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Michael S. Lawless has authored 23 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Theory and Mathematics, 6 papers in Molecular Biology and 6 papers in Materials Chemistry. Recurrent topics in Michael S. Lawless's work include Computational Drug Discovery Methods (8 papers), Catalytic Processes in Materials Science (4 papers) and Pharmacogenetics and Drug Metabolism (4 papers). Michael S. Lawless is often cited by papers focused on Computational Drug Discovery Methods (8 papers), Catalytic Processes in Materials Science (4 papers) and Pharmacogenetics and Drug Metabolism (4 papers). Michael S. Lawless collaborates with scholars based in United States and Spain. Michael S. Lawless's co-authors include George Blyholder, Robert D. Clark, Marvin Waldman, Robert Fraczkiewicz, David E. Patterson, Richard D. Cramer, Dennis Sprous, R. Kyle Palmer, Dennis S. Marynick and Vijay K. Gombar and has published in prestigious journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and Langmuir.

In The Last Decade

Michael S. Lawless

21 papers receiving 313 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael S. Lawless United States 10 130 117 76 75 49 23 345
Roberta Susnow United States 8 131 1.0× 129 1.1× 77 1.0× 96 1.3× 58 1.2× 11 417
Susanta Das United States 11 62 0.5× 171 1.5× 58 0.8× 91 1.2× 29 0.6× 23 347
Jimmy Kromann Denmark 10 88 0.7× 83 0.7× 110 1.4× 106 1.4× 15 0.3× 12 321
Axel Drefahl Germany 5 199 1.5× 170 1.5× 101 1.3× 115 1.5× 10 0.2× 6 475
Manyi Yang China 9 63 0.5× 86 0.7× 53 0.7× 243 3.2× 72 1.5× 15 430
Alonso J. Argüelles United States 8 82 0.6× 138 1.2× 262 3.4× 134 1.8× 29 0.6× 12 470
Daisy Y. Kyu United States 3 96 0.7× 138 1.2× 84 1.1× 95 1.3× 15 0.3× 4 336
Prithvi Singh India 13 141 1.1× 177 1.5× 154 2.0× 56 0.7× 18 0.4× 71 545
Nicolas Chéron France 11 81 0.6× 231 2.0× 250 3.3× 62 0.8× 14 0.3× 21 484
Eric Fontain Germany 12 173 1.3× 140 1.2× 90 1.2× 82 1.1× 16 0.3× 25 376

Countries citing papers authored by Michael S. Lawless

Since Specialization
Citations

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

Fields of papers citing papers by Michael S. Lawless

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael S. Lawless. 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 Michael S. Lawless. The network helps show where Michael S. Lawless may publish in the future.

Co-authorship network of co-authors of Michael S. Lawless

This figure shows the co-authorship network connecting the top 25 collaborators of Michael S. Lawless. A scholar is included among the top collaborators of Michael S. Lawless 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 Michael S. Lawless. Michael S. Lawless 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.
2.
Bachorz, Rafał A., Michael S. Lawless, David W. Miller, & Jeremy O. Jones. (2025). Multi-Criteria Decision Analysis in Drug Discovery. SHILAP Revista de lepidopterología. 4(1). 2–2.
3.
Liu, Yitong, et al.. (2024). Prediction of physicochemical and pharmacokinetic properties of botanical constituents by computational models. Journal of Applied Toxicology. 44(8). 1236–1245. 3 indexed citations
4.
Jones, Jeremy O., Robert D. Clark, Michael S. Lawless, D. W. Miller, & Marvin Waldman. (2024). The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations. Journal of Computer-Aided Molecular Design. 38(1). 14–14. 14 indexed citations
5.
Clark, Robert D., Gary M. Chinigo, Michael S. Lawless, et al.. (2020). Design and tests of prospective property predictions for novel antimalarial 2-aminopropylaminoquinolones. Journal of Computer-Aided Molecular Design. 34(11). 1117–1132. 7 indexed citations
6.
Lawless, Michael S., et al.. (2016). Modeling ADMET. Methods in molecular biology. 1425. 63–83. 45 indexed citations
7.
Lawless, Michael S., Marvin Waldman, Robert Fraczkiewicz, & Robert D. Clark. (2015). Using Cheminformatics in Drug Discovery. Handbook of experimental pharmacology. 232. 139–168. 16 indexed citations
8.
Clark, Robert D., Wenkel Liang, Adam Lee, et al.. (2014). Using beta binomials to estimate classification uncertainty for ensemble models. Journal of Cheminformatics. 6(1). 34–34. 17 indexed citations
9.
Sprous, Dennis, et al.. (2010). QSAR in the Pharmaceutical Research Setting: QSAR Models for Broad, Large Problems. Current Topics in Medicinal Chemistry. 10(6). 619–637. 50 indexed citations
10.
Cramer, Richard D., et al.. (1998). Virtual Compound Libraries:  A New Approach to Decision Making in Molecular Discovery Research. Journal of Chemical Information and Computer Sciences. 38(6). 1010–1023. 67 indexed citations
11.
Peterson, John, Ted L. Underiner, Richard D. Cramer, et al.. (1996). Solution Phase Synthesis of Chemical Libraries for Lead Discovery. SLAS DISCOVERY. 1(4). 179–186. 14 indexed citations
12.
Blyholder, George & Michael S. Lawless. (1993). A theoretical study of the site of CO dissociation on Fe(100). Surface Science. 290(1-2). 155–162. 28 indexed citations
13.
Blyholder, George & Michael S. Lawless. (1991). Hydrogen-assisted dissociation of carbon monoxide on a catalyst surface. Langmuir. 7(1). 140–141. 15 indexed citations
14.
Lawless, Michael S. & Dennis S. Marynick. (1991). A computational model for the chair-to-chair rearrangement in bis(cyclopentadienyl)pentasulfidotitanium(IV). Inorganic Chemistry. 30(18). 3547–3551. 6 indexed citations
15.
Lawless, Michael S. & Dennis S. Marynick. (1991). Potential energy surfaces for ring-rearrangement processes in tricarbonyl(cyclooctatetraene)chromium(0). Journal of the American Chemical Society. 113(20). 7513–7521. 9 indexed citations
16.
Blyholder, George & Michael S. Lawless. (1990). An energy criterion for determiningd orbital contribution to adsorbate bonding to a transition metal: CO/Fe12. Theoretical Chemistry Accounts. 77(1). 17–28. 2 indexed citations
17.
Blyholder, George & Michael S. Lawless. (1990). CO dissociation site on Fe. Journal of the Chemical Society Chemical Communications. 632–632. 4 indexed citations
18.
Blyholder, George & Michael S. Lawless. (1989). Noncatalyzed, homogeneously catalyzed, and heterogeneously catalyzed formyl formation. Journal of the American Chemical Society. 111(4). 1275–1281. 7 indexed citations
19.
Lawless, Michael S., et al.. (1987). The use of diatomic energies to analyze adsorption and coadsorption of CO and H on an Fe12 cluster. Progress in Surface Science. 26(1-4). 181–199. 8 indexed citations
20.
Blyholder, George, et al.. (1985). Carbonyl insertion reactions. 2. Alkali ion effect on hydride migration in (HFe(CO)4). Organometallics. 4(12). 2170–2173. 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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