Alex Washburne

6.2k total citations · 2 hit papers
17 papers, 1.8k citations indexed

About

Alex Washburne is a scholar working on Molecular Biology, Ecology and Modeling and Simulation. According to data from OpenAlex, Alex Washburne has authored 17 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Ecology and 3 papers in Modeling and Simulation. Recurrent topics in Alex Washburne's work include Microbial Community Ecology and Physiology (8 papers), Gut microbiota and health (7 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Alex Washburne is often cited by papers focused on Microbial Community Ecology and Physiology (8 papers), Gut microbiota and health (7 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Alex Washburne collaborates with scholars based in United States, Switzerland and Luxembourg. Alex Washburne's co-authors include Justin D. Silverman, Sayan Mukherjee, Lawrence A. David, Karsten Zengler, James T. Morton, Clarisse Marotz, Anna Edlund, Lívia S. Zaramela, Rob Knight and Jennifer D. Rocca and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Ecology.

In The Last Decade

Alex Washburne

17 papers receiving 1.8k 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.

SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases

2020 593 citations Fuqing Wu, Jianbo Zhang et al. mSystems profile →
Establishing microbial composition measurement standards with reference frames

2019 392 citations James T. Morton, Clarisse Marotz et al. Nature Communications profile →

Peers

Alex Washburne

ECOLO

PHEOH

Janelle R. Thompson United States

Dexiang Chen United States

Naomi Sengamalay United States

Jinping Chen China

Daniel Palm Sweden

Greg Humphrey United States

Justin D. Silverman United States

Gordon Ritchie Canada

Wei Ji China

David R. Franz United States

Janelle R. Thompson United States

Alex Washburne

996 ×1.2

1.0k ×1.6

1.2k ×2.7

ECOLO

546 ×1.6

171 ×1.6

PHEOH

Citations per year, relative to Alex Washburne Alex Washburne (= 1×) peers Janelle R. Thompson

Countries citing papers authored by Alex Washburne

Since Specialization

Citations

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

Fields of papers citing papers by Alex Washburne

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Washburne

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

All Works

Sort: Min cites: Since: Top N: Style:

17 of 17 papers shown

Busi, Susheel Bhanu, Stilianos Fodelianakis, Hannes Peter, et al.. (2022). The microbiome of cryospheric ecosystems. Nature Communications. 13(1). 3087–3087. 34 indexed citations

Abbott, Sam, Rosanna C. Barnard, Christopher I Jarvis, et al.. (2021). On a comprehensive model of the novel coronavirus (COVID-19) under Mittag-Leffler derivative. 3 indexed citations

Fodelianakis, Stilianos, Alex Washburne, Paraskevi Pramateftaki, et al.. (2021). Microdiversity characterizes prevalent phylogenetic clades in the glacier-fed stream microbiome. The ISME Journal. 16(3). 666–675. 42 indexed citations

Hoegh, Andrew, Alison J. Peel, Manuel Ruiz‐Aravena, et al.. (2021). Estimating viral prevalence with data fusion for adaptive two‐phase pooled sampling. Ecology and Evolution. 11(20). 14012–14023. 4 indexed citations

Darcy, John L., et al.. (2020). A phylogenetic model for the recruitment of species into microbial communities and application to studies of the human microbiome. The ISME Journal. 14(6). 1359–1368. 20 indexed citations

Kohler, Tyler J., Hannes Peter, Stilianos Fodelianakis, et al.. (2020). Patterns and Drivers of Extracellular Enzyme Activity in New Zealand Glacier-Fed Streams. Frontiers in Microbiology. 11. 591465–591465. 18 indexed citations

Albright, Michaeline, Renee Johansen, Jaron Thompson, et al.. (2020). Soil Bacterial and Fungal Richness Forecast Patterns of Early Pine Litter Decomposition. Frontiers in Microbiology. 11. 542220–542220. 18 indexed citations

Wu, Fuqing, Jianbo Zhang, Amy Xiao, et al.. (2020). SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases. mSystems. 5(4). 593 indexed citations breakdown →

Silverman, Justin D., Nathaniel Hupert, & Alex Washburne. (2020). Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States. Science Translational Medicine. 12(554). 63 indexed citations

10.

Rocca, Jennifer D., Marie Simonin, Emily S. Bernhardt, Alex Washburne, & Justin P. Wright. (2019). Rare microbial taxa emerge when communities collide: freshwater and marine microbiome responses to experimental mixing. Ecology. 101(3). e02956–e02956. 78 indexed citations

11.

Rocca, Jennifer D., Marie Simonin, Joanna R. Blaszczak, et al.. (2019). The Microbiome Stress Project: Toward a Global Meta-Analysis of Environmental Stressors and Their Effects on Microbial Communities. Frontiers in Microbiology. 9. 3272–3272. 140 indexed citations

12.

Morton, James T., Clarisse Marotz, Alex Washburne, et al.. (2019). Establishing microbial composition measurement standards with reference frames. Nature Communications. 10(1). 392 indexed citations breakdown →

13.

Faust, Karoline, Béatrice Laroche, Sophie de Buyl, et al.. (2018). Signatures of ecological processes in microbial community time series. Microbiome. 6(1). 120–120. 65 indexed citations

14.

Oliverio, Angela, Jean F. Power, Alex Washburne, et al.. (2018). The ecology and diversity of microbial eukaryotes in geothermal springs. The ISME Journal. 12(8). 1918–1928. 47 indexed citations

15.

Silverman, Justin D., Alex Washburne, Sayan Mukherjee, & Lawrence A. David. (2017). A phylogenetic transform enhances analysis of compositional microbiota data. eLife. 6. 211 indexed citations

16.

Washburne, Alex, Justin D. Silverman, Jonathan W. Leff, et al.. (2017). Phylogenetic factorization of compositional data yields lineage-level associations in microbiome datasets. PeerJ. 5. e2969–e2969. 74 indexed citations

17.

Tarnita, Corina E., Alex Washburne, Ricardo Martínez‐García, Allyson E. Sgro, & Simon A. Levin. (2015). Fitness tradeoffs between spores and nonaggregating cells can explain the coexistence of diverse genotypes in cellular slime molds. Proceedings of the National Academy of Sciences. 112(9). 2776–2781. 46 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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