Robert Farber
Impact in
- Artificial Intelligence top 5%
- Neural Networks and Applications
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- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- Fractal and DNA sequence analysis
- Machine Learning in Bioinformatics
Papers in
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- Parallel Computing and Optimization Techniques 2
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- Protein Structure and Dynamics 3
- Genomics and Phylogenetic Studies 2
- Fractal and DNA sequence analysis 2
- Machine Learning in Bioinformatics 2
- Co-authors
- Alan S. Lapedes (9 shared papers)Karl M. Sirotkin (2 shared papers)Peter Florian Stadler (1 shared paper)Ivo L. Hofacker (1 shared paper)Christian Burks (1 shared paper)Lynn L. Trease (1 shared paper)Harold E. Trease (1 shared paper)
- Journals
- Journal of Theoretical Biology (2 papers)Physica D Nonlinear Phenomena (1 paper)Journal of Molecular Biology (1 paper)Linux journal (1 paper)Routledge eBooks (1 paper)
- Partner nations
- United StatesAustriaCanada
In The Last Decade
Robert Farber
12 papers receiving 527 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 209
- Molecular Biology 135
- Epidemiology 64
- Management Science and Operations Research 33
- Genetics 37
Countries citing papers authored by Robert Farber
This map shows the geographic impact of Robert Farber'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 Robert Farber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Farber more than expected).
Fields of papers citing papers by Robert Farber
This network shows the impact of papers produced by Robert Farber. 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 Robert Farber. The network helps show where Robert Farber may publish in the future.
Co-authors
The 7 scholars most cited alongside Robert Farber, 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 | 1989 | 246 | |
| 2 | 2001 | 93 | |
| 3 | 1992 | 88 | |
| 4 | 1986 | 56 | |
| 5 | 2001 | 44 | |
| 6 | 1986 | 23 | |
| 7 | Neural net representations of empirical protein potentials. | 1995 | 13 |
| 8 | 2010 | 5 | |
| 9 | 2018 | 3 | |
| 10 | An Expression of Interest to Construct a Major SSC Detector | 1991 | 2 |
| 11 | Neural Network Definitions of Highly Predictable Protein Secondary Structure Classes | 1993 | 2 |
| 12 | Unstructured data analysis of streaming video using parallel, high-throughput algorithms | 2007 | 2 |
| 13 | Massively parallel Linux laptops, workstations and clusters with CUDA | 2008 | 0 |
About Robert Farber
Robert Farber is a scholar working on Hardware and Architecture, Molecular Biology, Artificial Intelligence, Nuclear and High Energy Physics and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 577 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Neural Networks and Applications (3 papers), Parallel Computing and Optimization Techniques (2 papers), Genomics and Phylogenetic Studies (2 papers), Fractal and DNA sequence analysis (2 papers), Machine Learning in Bioinformatics (2 papers), Artificial Immune Systems Applications (1 paper) and Particle Detector Development and Performance (1 paper). The work is most often cited by research in Artificial Intelligence (209 citations), Molecular Biology (135 citations), Epidemiology (64 citations), Management Science and Operations Research (33 citations) and Genetics (37 citations). Robert Farber has collaborated with scholars based in United States, Austria and Canada. Frequent co-authors include Alan S. Lapedes, Karl M. Sirotkin, Peter Florian Stadler, Ivo L. Hofacker, Christian Burks, Lynn L. Trease and Harold E. Trease. Their work appears in journals such as Journal of Theoretical Biology, Physica D Nonlinear Phenomena, Journal of Molecular Biology, Linux journal and Routledge eBooks.
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.