Michael S. Lajiness
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Spectroscopy top 10%
- Organic Chemistry
- Pharmacology top 10%
- Co-authors
- Gerald M. MaggioraJohn H. Van DrieVeerabahu ShanmugasundaramMichal ViethJon A. EricksonLisa PeltasonRajarshi GuhaMathias J. Wawer
- Topics
- Computational Drug Discovery Methods (12 papers)Analytical Chemistry and Chromatography (5 papers)Biomedical Text Mining and Ontologies (4 papers)
- Partner nations
- United StatesGermanySouth Korea
In The Last Decade
Michael S. Lajiness
21 papers receiving 693 citations
Peers
Comparison fields: 5 of 98
- Computational Theory and Mathematics 506
- Molecular Biology 372
- Spectroscopy 124
- Organic Chemistry 121
- Pharmacology 103
Countries citing papers authored by Michael S. Lajiness
This map shows the geographic impact of Michael S. Lajiness'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. Lajiness 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. Lajiness more than expected).
Fields of papers citing papers by Michael S. Lajiness
This network shows the impact of papers produced by Michael S. Lajiness. 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. Lajiness. The network helps show where Michael S. Lajiness may publish in the future.
Co-authorship network of co-authors of Michael S. Lajiness
This figure shows the co-authorship network connecting the top 25 collaborators of Michael S. Lajiness. A scholar is included among the top collaborators of Michael S. Lajiness 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. Lajiness. Michael S. Lajiness is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 44 | |
| 3 | 14 | |
| 4 | 28 | |
| 5 | 1 | |
| 6 | 134 | |
| 7 | 19 | |
| 8 | Molecular properties that influence oral drug-like behavior. | 81 |
| 9 | 96 | |
| 10 | 2 | |
| 11 | 25 | |
| 12 | 57 | |
| 13 | 39 | |
| 14 | 25 | |
| 15 | 2 | |
| 16 | Molecular similarity-based methods for selecting compounds for screening | 32 |
| 17 | Molecular similarity: a basis for designing drug screening programs. | 34 |
| 18 | 6 | |
| 19 | 3 | |
| 20 | 52 |
About Michael S. Lajiness
Michael S. Lajiness is a scholar working on Computational Theory and Mathematics, Applied Microbiology and Biotechnology and Spectroscopy, having authored 21 papers that have together received 735 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Analytical Chemistry and Chromatography (5 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Computational Theory and Mathematics (506 citations), Pharmacology (69 citations) and Spectroscopy (124 citations). Michael S. Lajiness has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include Gerald M. Maggiora, John H. Van Drie, Veerabahu Shanmugasundaram, Michal Vieth, Jon A. Erickson, Lisa Peltason, Rajarshi Guha, Mathias J. Wawer, Jürgen Bajorath and Mark A. Johnson. Their work appears in journals such as Journal of Medicinal Chemistry, BMC Bioinformatics and Drug Discovery Today.
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.