Len Trigg

3.0k total citations · 1 hit paper
8 papers, 1.1k citations indexed

About

Len Trigg is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Len Trigg has authored 8 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Artificial Intelligence. Recurrent topics in Len Trigg's work include Genomics and Phylogenetic Studies (4 papers), Genomics and Rare Diseases (3 papers) and Genetic Associations and Epidemiology (2 papers). Len Trigg is often cited by papers focused on Genomics and Phylogenetic Studies (4 papers), Genomics and Rare Diseases (3 papers) and Genetic Associations and Epidemiology (2 papers). Len Trigg collaborates with scholars based in New Zealand, United States and Canada. Len Trigg's co-authors include Geoffrey Holmes, Eibe Frank, Ian H. Witten, Mark Hall, Francisco M. De La Vega, Rebecca Truty, Justin M. Zook, Marc Salit, Sean A. Irvine and Cory Y. McLean and has published in prestigious journals such as Nature Biotechnology, Bioinformatics and Journal of Computational Biology.

In The Last Decade

Len Trigg

6 papers receiving 1.1k citations

Hit Papers

Data mining in bioinformatics using Weka 2004 2026 2011 2018 2004 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Data mining in bioinformatics using Weka
    2004 712 citations Eibe Frank, Mark Hall et al. Bioinformatics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Len Trigg New Zealand 5 735 259 178 105 100 8 1.1k
Misha Kapushesky United Kingdom 17 1.4k 2.0× 219 0.8× 175 1.0× 142 1.4× 93 0.9× 24 1.8k
Michael M. Hoffman Canada 17 1.5k 2.1× 311 1.2× 228 1.3× 169 1.6× 76 0.8× 37 2.0k
Gwan‐Su Yi South Korea 20 1.2k 1.6× 147 0.6× 99 0.6× 59 0.6× 58 0.6× 72 1.5k
Johan Rung United Kingdom 16 950 1.3× 218 0.8× 154 0.9× 62 0.6× 31 0.3× 26 1.3k
Bernard de Bono United Kingdom 18 1.6k 2.1× 200 0.8× 136 0.8× 105 1.0× 221 2.2× 54 2.1k
Chen‐An Tsai Taiwan 20 681 0.9× 119 0.5× 123 0.7× 104 1.0× 62 0.6× 45 1.1k
Gabriella Rustici United Kingdom 16 1.5k 2.1× 143 0.6× 135 0.8× 102 1.0× 64 0.6× 26 1.9k
Alain Coletta Belgium 9 760 1.0× 90 0.3× 124 0.7× 266 2.5× 51 0.5× 12 1.2k
Chunwei Wang China 8 1.9k 2.6× 268 1.0× 163 0.9× 85 0.8× 33 0.3× 24 2.4k
Yixin Wang China 19 1.2k 1.6× 93 0.4× 217 1.2× 110 1.0× 67 0.7× 72 1.7k

Countries citing papers authored by Len Trigg

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Len Trigg

This figure shows the co-authorship network connecting the top 25 collaborators of Len Trigg. A scholar is included among the top collaborators of Len Trigg 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 Len Trigg. Len Trigg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Trigg, Len, et al.. (2024). Natural Language Explanation for Autonomous Navigation. 1–9.
2.
Krusche, Peter, Len Trigg, Paul C. Boutros, et al.. (2019). Best practices for benchmarking germline small-variant calls in human genomes. Nature Biotechnology. 37(5). 555–560. 182 indexed citations
3.
Zook, Justin M., Jennifer McDaniel, Nathan D. Olson, et al.. (2019). An open resource for accurately benchmarking small variant and reference calls. Nature Biotechnology. 37(5). 561–566. 152 indexed citations
4.
Cleary, John G., Brian S. Hilbush, Stuart J. Inglis, et al.. (2014). Joint Variant and De Novo Mutation Identification on Pedigrees from High-Throughput Sequencing Data. Journal of Computational Biology. 21(6). 405–419. 52 indexed citations
5.
Cleary, John G., et al.. (2013). Quantitative Analysis of Shotgun Metagenomic Data with the Real Time Genomics Platform. Journal of Biomolecular Techniques JBT. 24. 2 indexed citations
6.
7.
Frank, Eibe, Mark Hall, Len Trigg, Geoffrey Holmes, & Ian H. Witten. (2004). Data mining in bioinformatics using Weka. Bioinformatics. 20(15). 2479–2481. 712 indexed citations breakdown →
8.
Holmes, Geoffrey & Len Trigg. (2003). A diagnostic tool for tree based supervised classification learning algorithms. 2. 514–519. 5 indexed citations

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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