Matthew C. Schmidt

402 citations
41 papers · 233 · h-index 7

Impact in

Papers in

    • Advanced Radiotherapy Techniques 17
    • Bioinformatics and Genomic Networks 8
    • Gene expression and cancer classification 4
    • Microbial Metabolic Engineering and Bioproduction 3

Matthew C. Schmidt

35 papers receiving 223 citations

Peers

Matthew C. Schmidt
Comparison fields: 5 of 49
  • Radiation 65
  • Statistical and Nonlinear Physics 63
  • Computational Theory and Mathematics 34
  • Computer Networks and Communications 42
  • Computer Vision and Pattern Recognition 35
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Citations per field
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Citations per year

Countries citing papers authored by Matthew C. Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by Matthew C. Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew C. Schmidt. 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 Matthew C. Schmidt. The network helps show where Matthew C. Schmidt may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew C. Schmidt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew C. Schmidt Line = papers co-authored together Matthew C. Schmidt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200996
2 201519
3 201215
4 202212
5 20217
6 20107
7 20246
8 20186
9 20236
10 20086
11 20224
12 20224
13 20104
14 20213
15 20123
16 20113
17 20083
18 20093
19
A Fast, Accurate Algorithm for Identifying Functional Modules Through Pairwise Local Alignment of Protein Interaction Networks.
20092
20 20202

About Matthew C. Schmidt

Matthew C. Schmidt is a scholar working on Radiation, Molecular Biology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Statistical and Nonlinear Physics, having authored 41 papers that have together received 233 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (17 papers), Bioinformatics and Genomic Networks (8 papers), Gene expression and cancer classification (4 papers), Complex Network Analysis Techniques (4 papers), Radiation Therapy and Dosimetry (3 papers), Algorithms and Data Compression (3 papers), Advanced Graph Neural Networks (3 papers) and Microbial Metabolic Engineering and Bioproduction (3 papers). The work is most often cited by research in Radiation (65 citations), Statistical and Nonlinear Physics (63 citations), Computational Theory and Mathematics (34 citations), Computer Networks and Communications (42 citations) and Computer Vision and Pattern Recognition (35 citations). Matthew C. Schmidt has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Nagiza F. Samatova, Kevin W. Thomas, Byung Hoon Park, David M. Brizel, Nadya Bliss, William Hendrix, Joseph Y. Lo, Nels Knutson, Shiva K. Das and Baozhou Sun. Their work appears in journals such as Journal of Applied Clinical Medical Physics, Medical Physics, Theoretical Computer Science, BMC Bioinformatics and Journal of Parallel and Distributed Computing.

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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