Michaela Spitzer
Impact in
- Health Informatics top 1%
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in
-
- Bioinformatics and Genomic Networks 3
- Genetics, Bioinformatics, and Biomedical Research 1
-
- Microbial Natural Products and Biosynthesis 4
- Co-authors
- Ian Dunham (3 shared papers)Jessica Vamathevan (1 shared paper)George Lee (1 shared paper)Bin Li (1 shared paper)Dominic A. Clark (1 shared paper)Edgardo A. Ferrán (1 shared paper)Paul Czodrowski (1 shared paper)Shanrong Zhao (1 shared paper)
- Journals
- Disease Models & Mechanisms (1 paper)Molecular and Cellular Biology (1 paper)Scientific Data (1 paper)Nature Reviews Drug Discovery (1 paper)Cell chemical biology (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Michaela Spitzer
17 papers receiving 3.0k citations
Michaela Spitzer's Hit Papers
Peers
Comparison fields: 5 of 174
- Health Informatics 119
- Computational Theory and Mathematics 1.0k
- Infectious Diseases 357
- Molecular Biology 1.4k
- Biophysics 112
Countries citing papers authored by Michaela Spitzer
This map shows the geographic impact of Michaela Spitzer'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 Michaela Spitzer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michaela Spitzer more than expected).
Fields of papers citing papers by Michaela Spitzer
This network shows the impact of papers produced by Michaela Spitzer. 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 Michaela Spitzer. The network helps show where Michaela Spitzer may publish in the future.
Co-authors
The 25 scholars most cited alongside Michaela Spitzer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Applications of machine learning in drug discovery and development Hit paper breakdown → | 2019 | 1948 |
| 2 | 2018 | 292 | |
| 3 | 2016 | 166 | |
| 4 | 2011 | 156 | |
| 5 | 2013 | 155 | |
| 6 | 2015 | 91 | |
| 7 | 2015 | 63 | |
| 8 | 2012 | 42 | |
| 9 | 2010 | 37 | |
| 10 | 2016 | 31 | |
| 11 | 2019 | 29 | |
| 12 | 2022 | 29 | |
| 13 | 2013 | 18 | |
| 14 | 2016 | 12 | |
| 15 | 2014 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 1985 | 1 |
About Michaela Spitzer
Michaela Spitzer is a scholar working on Molecular Biology, Pharmacology, Epidemiology, Computational Theory and Mathematics and Infectious Diseases, having authored 17 papers that have together received 3.1k indexed citations. Recurring topics across this work include Fungal Infections and Studies (4 papers), Computational Drug Discovery Methods (4 papers), Microbial Natural Products and Biosynthesis (4 papers), Antifungal resistance and susceptibility (3 papers), Bioinformatics and Genomic Networks (3 papers), Infectious Diseases and Mycology (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper) and Trypanosoma species research and implications (1 paper). The work is most often cited by research in Health Informatics (119 citations), Computational Theory and Mathematics (1.0k citations), Infectious Diseases (357 citations), Molecular Biology (1.4k citations) and Biophysics (112 citations). Michaela Spitzer has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Ian Dunham, Jessica Vamathevan, George Lee, Bin Li, Dominic A. Clark, Edgardo A. Ferrán, Paul Czodrowski, Shanrong Zhao, Anant Madabhushi and Parantu K. Shah. Their work appears in journals such as Disease Models & Mechanisms, Molecular and Cellular Biology, Scientific Data, Nature Reviews Drug Discovery and Cell chemical biology.
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.