Benjamin D. Kaehler

33.0k total citations · 2 hit papers
14 papers, 4.9k citations indexed

About

Benjamin D. Kaehler is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Benjamin D. Kaehler has authored 14 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Genetics and 3 papers in Ecology. Recurrent topics in Benjamin D. Kaehler's work include Genomics and Phylogenetic Studies (9 papers), Genetic diversity and population structure (4 papers) and Microbial Community Ecology and Physiology (3 papers). Benjamin D. Kaehler is often cited by papers focused on Genomics and Phylogenetic Studies (9 papers), Genetic diversity and population structure (4 papers) and Microbial Community Ecology and Physiology (3 papers). Benjamin D. Kaehler collaborates with scholars based in Australia, United States and Switzerland. Benjamin D. Kaehler's co-authors include Nicholas A. Bokulich, Matthew R. Dillon, Gavin Huttley, J. Gregory Caporaso, Rob Knight, Evan Bolyen, Jai Ram Rideout, Michał Ziemski, Michael S. Robeson and Devon O’Rourke and has published in prestigious journals such as Nature Communications, PLoS ONE and Frontiers in Microbiology.

In The Last Decade

Benjamin D. Kaehler

14 papers receiving 4.8k citations

Hit Papers

align trajectories

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.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin

2018 3.9k citations Nicholas A. Bokulich, Benjamin D. Kaehler et al. Microbiome profile →
RESCRIPt: Reproducible sequence taxonomy reference database management

2021 540 citations Michael S. Robeson, Devon O’Rourke et al. PLoS Computational Biology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Benjamin D. Kaehler Australia	9	2.3k	1.3k	685	488	426	14	4.9k
Evan Bolyen United States	9	2.3k 1.0×	1.2k 0.9×	715 1.0×	486 1.0×	432 1.0×	12	4.8k
Matthew R. Dillon United States	6	2.5k 1.1×	1.4k 1.0×	738 1.1×	525 1.1×	459 1.1×	8	5.2k
Jai Ram Rideout United States	15	3.1k 1.3×	1.6k 1.2×	801 1.2×	610 1.3×	578 1.4×	19	6.1k
Gail Ackermann United States	30	2.8k 1.2×	1.1k 0.8×	673 1.0×	369 0.8×	652 1.5×	45	5.5k
Anna Klindworth Germany	7	3.0k 1.3×	2.2k 1.7×	675 1.0×	690 1.4×	378 0.9×	9	6.6k
Georgia Giannoukos United States	21	3.8k 1.6×	1.3k 1.0×	708 1.0×	479 1.0×	349 0.8×	28	6.2k
Dawn Ciulla United States	10	2.7k 1.2×	1.0k 0.8×	493 0.7×	452 0.9×	331 0.8×	13	4.4k
Markus Bauer Austria	6	3.2k 1.4×	2.2k 1.7×	924 1.3×	454 0.9×	477 1.1×	9	6.9k
Jean M. Macklaim Canada	23	3.1k 1.3×	952 0.7×	452 0.7×	658 1.3×	498 1.2×	33	5.5k

Countries citing papers authored by Benjamin D. Kaehler

Since Specialization

Citations

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

Fields of papers citing papers by Benjamin D. Kaehler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin D. Kaehler. 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 Benjamin D. Kaehler. The network helps show where Benjamin D. Kaehler may publish in the future.

Co-authorship network of co-authors of Benjamin D. Kaehler

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

All Works

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14 of 14 papers shown

Robinson, Anna, et al.. (2023). New insights from modelling studies and molecular dynamics simulations of the DI_S5‐S6 extracellular linker of the skeletal muscle sodium channel NaV1.4. Biopolymers. 114(7). e23540–e23540. 1 indexed citations

Robeson, Michael S., Devon O’Rourke, Benjamin D. Kaehler, et al.. (2021). RESCRIPt: Reproducible sequence taxonomy reference database management. PLoS Computational Biology. 17(11). e1009581–e1009581. 540 indexed citations breakdown →

Ziemski, Michał, et al.. (2021). Beating Naive Bayes at Taxonomic Classification of 16S rRNA Gene Sequences. Frontiers in Microbiology. 12. 644487–644487. 18 indexed citations

Bokulich, Nicholas A., Michał Ziemski, Michael S. Robeson, & Benjamin D. Kaehler. (2020). Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods. Computational and Structural Biotechnology Journal. 18. 4048–4062. 48 indexed citations

Kaehler, Benjamin D., Nicholas A. Bokulich, Daniel McDonald, et al.. (2019). Species abundance information improves sequence taxonomy classification accuracy. Nature Communications. 10(1). 4643–4643. 126 indexed citations

McDonald, Daniel, Benjamin D. Kaehler, Antonio G. González, et al.. (2019). redbiom: a Rapid Sample Discovery and Feature Characterization System. mSystems. 4(4). 30 indexed citations

Bokulich, Nicholas A., Benjamin D. Kaehler, Jai Ram Rideout, et al.. (2018). Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 6(1). 90–90. 3938 indexed citations breakdown →

Bokulich, Nicholas A., Matthew R. Dillon, Evan Bolyen, et al.. (2018). q2-sample-classifier: machine-learning tools for microbiome classification and regression. The Journal of Open Source Software. 3(30). 934–934. 128 indexed citations

Sutherland, Tara D., Alagacone Sriskantha, Trevor D. Rapson, Benjamin D. Kaehler, & Gavin Huttley. (2018). Did aculeate silk evolve as an antifouling material?. PLoS ONE. 13(9). e0203948–e0203948. 2 indexed citations

10.

Kaehler, Benjamin D.. (2017). Full reconstruction of non-stationary strand-symmetric models on rooted phylogenies. Journal of Theoretical Biology. 420. 144–151. 2 indexed citations

11.

Kaehler, Benjamin D., Von Bing Yap, & Gavin Huttley. (2017). Standard Codon Substitution Models Overestimate Purifying Selection for Non-Stationary Data. Genome Biology and Evolution. 9(1). evw308–evw308. 7 indexed citations

12.

Kaehler, Benjamin D., et al.. (2016). Multivariate subordination using generalised Gamma convolutions with applications to Variance Gamma processes and option pricing. Stochastic Processes and their Applications. 127(7). 2208–2242. 15 indexed citations

13.

Trueman, Holly E., et al.. (2015). Folding behavior of four silks of giant honey bee reflects the evolutionary conservation of aculeate silk proteins. Insect Biochemistry and Molecular Biology. 59. 72–79. 8 indexed citations

14.

Kaehler, Benjamin D., Von Bing Yap, Rongli Zhang, & Gavin Huttley. (2014). Genetic Distance for a General Non-Stationary Markov Substitution Process. Systematic Biology. 64(2). 281–293. 15 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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