Matthew J. Gebert

29 total papers · 1.9k total citations
13 papers, 920 citations indexed

About

Matthew J. Gebert is a scholar working on Molecular Biology, Ecology and Epidemiology. According to data from OpenAlex, Matthew J. Gebert has authored 13 papers receiving a total of 920 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Ecology and 3 papers in Epidemiology. Recurrent topics in Matthew J. Gebert's work include Gut microbiota and health (4 papers), Microbial Community Ecology and Physiology (3 papers) and Mycobacterium research and diagnosis (3 papers). Matthew J. Gebert is often cited by papers focused on Gut microbiota and health (4 papers), Microbial Community Ecology and Physiology (3 papers) and Mycobacterium research and diagnosis (3 papers). Matthew J. Gebert collaborates with scholars based in United States, Denmark and Spain. Matthew J. Gebert's co-authors include Noah Fierer, Rob Knight, Derek J. Linderman, Brent E. Palmer, Thomas Campbell, Marcella Li, Andrew P. Fontenot, Sonia C. Flores, Catherine Lozupone and Manuel Delgado‐Baquerizo and has published in prestigious journals such as Environmental Science & Technology, The Journal of Immunology and Applied and Environmental Microbiology.

In The Last Decade

Matthew J. Gebert

12 papers receiving 908 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matthew J. Gebert 414 241 203 170 118 13 920
James W. Bullard 365 0.9× 74 0.3× 200 1.0× 70 0.4× 177 1.5× 16 1.1k
Sandy MacDonald 273 0.7× 31 0.1× 354 1.7× 118 0.7× 157 1.3× 19 959
Stevenn Volant 318 0.8× 214 0.9× 175 0.9× 124 0.7× 49 0.4× 29 1.1k
Dipankar Bachar 547 1.3× 241 1.0× 318 1.6× 99 0.6× 42 0.4× 13 1.0k
Christine P. Zolnik 381 0.9× 267 1.1× 167 0.8× 237 1.4× 76 0.6× 20 1.0k
Siyang Huang 56 0.1× 445 1.8× 72 0.4× 51 0.3× 52 0.4× 27 795
Michele Burday 529 1.3× 169 0.7× 42 0.2× 158 0.9× 54 0.5× 12 1.1k
Tom A. Mendum 381 0.9× 434 1.8× 27 0.1× 343 2.0× 72 0.6× 37 1.0k
Robert B. Moeller 150 0.4× 177 0.7× 86 0.4× 129 0.8× 65 0.6× 48 924
W. Russell Byrne 274 0.7× 300 1.2× 37 0.2× 351 2.1× 225 1.9× 23 968

Countries citing papers authored by Matthew J. Gebert

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Gebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. Gebert. 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 Matthew J. Gebert. The network helps show where Matthew J. Gebert may publish in the future.

Co-authorship network of co-authors of Matthew J. Gebert

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

All Works

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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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