Scott C. Schmidler
- Molecular Biology
- Statistics and Probability top 5%
- Artificial Intelligence top 10%
- Genetics
- Materials Chemistry
- Co-authors
- Douglas L. BrutlagJun S. LiuDawn B. WoodardMark HuberChunlin JiKatia KoelleRotem Ben‐ShacharThomas D. Wu
- Topics
- Protein Structure and Dynamics (11 papers)Bayesian Methods and Mixture Models (8 papers)Markov Chains and Monte Carlo Methods (7 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Scott C. Schmidler
32 papers receiving 699 citations
Peers
Comparison fields: 5 of 129
- Molecular Biology 342
- Statistics and Probability 122
- Artificial Intelligence 112
- Genetics 97
- Materials Chemistry 87
Countries citing papers authored by Scott C. Schmidler
This map shows the geographic impact of Scott C. Schmidler'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 Scott C. Schmidler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott C. Schmidler more than expected).
Fields of papers citing papers by Scott C. Schmidler
This network shows the impact of papers produced by Scott C. Schmidler. 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 Scott C. Schmidler. The network helps show where Scott C. Schmidler may publish in the future.
Co-authorship network of co-authors of Scott C. Schmidler
This figure shows the co-authorship network connecting the top 25 collaborators of Scott C. Schmidler. A scholar is included among the top collaborators of Scott C. Schmidler 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 Scott C. Schmidler. Scott C. Schmidler 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 | 1 | |
| 3 | 8 | |
| 4 | 12 | |
| 5 | 6 | |
| 6 | 9 | |
| 7 | 40 | |
| 8 | 26 | |
| 9 | 40 | |
| 10 | 21 | |
| 11 | 52 | |
| 12 | 8 | |
| 13 | 27 | |
| 14 | 22 | |
| 15 | 28 | |
| 16 | 49 | |
| 17 | 0 | |
| 18 | 16 | |
| 19 | Modeling and superposition of multiple protein structures using affine transformations: analysis of the globins. | 6 |
| 20 | The COLLAGE/KHOROS Link: Planning for Image Processing Tasks | 15 |
About Scott C. Schmidler
Scott C. Schmidler is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology, having authored 33 papers that have together received 727 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (11 papers), Bayesian Methods and Mixture Models (8 papers) and Markov Chains and Monte Carlo Methods (7 papers). The work is most often cited by research in Statistics and Probability (122 citations), Molecular Biology (342 citations) and Artificial Intelligence (112 citations). Scott C. Schmidler has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Douglas L. Brutlag, Jun S. Liu, Dawn B. Woodard, Mark Huber, Chunlin Ji, Katia Koelle, Rotem Ben‐Shachar, Thomas D. Wu, Trevor Hastie and Rolando Estrada. Their work appears in journals such as Journal of the American Chemical Society, The Journal of Chemical Physics and PLoS ONE.
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.