Brian Kelley

60 papers receiving 3.5k citations

Hit Papers

Analyzing Learned Molecular Representations for Property Prediction 2019 · 1.1k citations
1.1k20192026202120232505007501000

Peers

Brian Kelley
Comparison fields: 5 of 170
  • Computational Theory and Mathematics 1.5k
  • Molecular Biology 1.9k
  • Materials Chemistry 877
  • Anesthesiology and Pain Medicine 78
  • Cancer Research 205
Replace Yasushi Okuno with:
Yasushi Okuno Japan
Susan L. McGovern United States
Shengyong Yang China
Volker M. Lauschke Sweden
Robert N. Jorissen Australia
Rita Santos United Kingdom
Xian Zeng China
Simon Zhou United States
Anneli Karlsson Sweden
Paolo Vicini United States
Brian Kelley relative to Yasushi Okuno Japan Yasushi Okuno's profile →
Citations per field
00.5×5.6×
Yasushi Okuno · 1×
Citations per year

Countries citing papers authored by Brian Kelley

Since Specialization
Citations

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

Fields of papers citing papers by Brian Kelley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian Kelley. 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 Brian Kelley. The network helps show where Brian Kelley may publish in the future.

Co-authors

The 25 scholars most cited alongside Brian Kelley, 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 Brian Kelley Line = papers co-authored together Brian Kelley links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Analyzing Learned Molecular Representations for Property Prediction
Hit paper breakdown →
20191081
2 2003335
3 2004274
4 2010254
5 2013150
6 2004136
7 2010129
8 2012118
9 2005115
10 2015108
11 201489
12 200372
13 201659
14 202056
15 201047
16 201141
17 201836
18 200235
19 201033
20 201531

About Brian Kelley

Brian Kelley is a scholar working on Developmental Biology, Health Informatics, Computational Theory and Mathematics, Medical Laboratory Technology and Surgery, having authored 61 papers that have together received 3.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Reconstructive Surgery and Microvascular Techniques (7 papers), Protein Structure and Dynamics (7 papers), Bioinformatics and Genomic Networks (6 papers), Machine Learning in Materials Science (5 papers), Breast Implant and Reconstruction (4 papers), Cardiac Structural Anomalies and Repair (3 papers) and Surgical Sutures and Adhesives (3 papers). The work is most often cited by research in Computational Theory and Mathematics (1.5k citations), Molecular Biology (1.9k citations), Materials Chemistry (877 citations), Anesthesiology and Pain Medicine (78 citations) and Cancer Research (205 citations). Brian Kelley has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Brent R. Stockwell, Trey Ideker, Roded Sharan, David E. Root, Kevin C. Chung, Gregory L. Warren, Wengong Jin, Miriam Mathea, Klavs F. Jensen and Richard M. Karp. Their work appears in journals such as Plastic & Reconstructive Surgery, Journal of Chemical Information and Modeling, Journal of Bone and Mineral Research, Hand and Annals of Surgical Oncology.

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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