Len Trigg
Impact in
- Cancer Research top 10%
- Cancer Genomics and Diagnostics
- Molecular Biology top 10%
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
Papers in
- Genetics 4
- Genomics and Rare Diseases 4
- Genetic Associations and Epidemiology 2
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- Machine Learning and Data Classification 2
- Data Stream Mining Techniques 2
- Anomaly Detection Techniques and Applications 2
- Co-authors
- Geoffrey Holmes (5 shared papers)Ian H. Witten (3 shared papers)Eibe Frank (3 shared papers)Mark Michael Hall (2 shared papers)Richard Kirkby (2 shared papers)Bernhard Pfahringer (2 shared papers)Francisco M. De La Vega (3 shared papers)Rebecca Truty (2 shared papers)
- Journals
- Nature Biotechnology (2 papers)Genome biology (1 paper)Journal of Biomolecular Techniques JBT (1 paper)Bioinformatics (1 paper)Journal of Computational Biology (1 paper)
- Partner nations
- New ZealandUnited StatesCanada
In The Last Decade
Len Trigg
11 papers receiving 1.7k citations
Len Trigg's Hit Papers
Peers
Comparison fields: 5 of 164
- Cancer Research 189
- Molecular Biology 774
- Genetics 304
- Health Information Management 36
- Artificial Intelligence 278
Countries citing papers authored by Len Trigg
This map shows the geographic impact of Len Trigg'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 Len Trigg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Len Trigg more than expected).
Fields of papers citing papers by Len Trigg
This network shows the impact of papers produced by Len Trigg. 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 Len Trigg. The network helps show where Len Trigg may publish in the future.
Co-authors
The 25 scholars most cited alongside Len Trigg, 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 | Data mining in bioinformatics using Weka Hit paper breakdown → | 2004 | 751 |
| 2 | 2009 | 353 | |
| 3 | 2019 | 248 | |
| 4 | 2019 | 210 | |
| 5 | 2006 | 95 | |
| 6 | 2014 | 61 | |
| 7 | 2022 | 27 | |
| 8 | 2003 | 6 | |
| 9 | 2006 | 4 | |
| 10 | Quantitative Analysis of Shotgun Metagenomic Data with the Real Time Genomics Platform | 2013 | 2 |
| 11 | 2024 | 1 |
About Len Trigg
Len Trigg is a scholar working on Genetics, Artificial Intelligence, Molecular Biology, Signal Processing and Cancer Research, having authored 11 papers that have together received 1.8k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Genomics and Rare Diseases (4 papers), Machine Learning and Data Classification (2 papers), Data Stream Mining Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Genetic Associations and Epidemiology (2 papers), Cancer Genomics and Diagnostics (1 paper) and Microbial Metabolic Engineering and Bioproduction (1 paper). The work is most often cited by research in Cancer Research (189 citations), Molecular Biology (774 citations), Genetics (304 citations), Health Information Management (36 citations) and Artificial Intelligence (278 citations). Len Trigg has collaborated with scholars based in New Zealand, United States and Canada. Frequent co-authors include Geoffrey Holmes, Ian H. Witten, Eibe Frank, Mark Michael Hall, Richard Kirkby, Bernhard Pfahringer, Francisco M. De La Vega, Rebecca Truty, Marc Salit and Justin M. Zook. Their work appears in journals such as Nature Biotechnology, Genome biology, Journal of Biomolecular Techniques JBT, Bioinformatics and Journal of Computational 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.