Byron J. Smith

1.8k total citations · 1 hit paper
14 papers, 1.2k citations indexed

About

Byron J. Smith is a scholar working on Molecular Biology, Infectious Diseases and Ecology. According to data from OpenAlex, Byron J. Smith has authored 14 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 3 papers in Infectious Diseases and 2 papers in Ecology. Recurrent topics in Byron J. Smith's work include Gut microbiota and health (9 papers), Genomics and Phylogenetic Studies (5 papers) and Clostridium difficile and Clostridium perfringens research (3 papers). Byron J. Smith is often cited by papers focused on Gut microbiota and health (9 papers), Genomics and Phylogenetic Studies (5 papers) and Clostridium difficile and Clostridium perfringens research (3 papers). Byron J. Smith collaborates with scholars based in United States, Denmark and Israel. Byron J. Smith's co-authors include Thomas M. Schmidt, Benjamin R. K. Roller, Richard A. Miller, Aaron C. Ericsson, Randy Strong, David C. Harrison, D. P. Cruikshank, Michael W. Varner, William F. Rayburn and Katherine S. Pollard and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Gastroenterology.

In The Last Decade

Byron J. Smith

12 papers receiving 1.2k 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.

rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development

2014 782 citations Byron J. Smith, Benjamin R. K. Roller et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Byron J. Smith United States	6	663	361	134	120	100	14	1.2k
Andrew P. A. Oxley Australia	19	709 1.1×	303 0.8×	145 1.1×	91 0.8×	119 1.2×	34	1.7k
Salam M. Habib Canada	5	728 1.1×	246 0.7×	155 1.2×	183 1.5×	127 1.3×	5	1.4k
Junko Tomita Japan	13	565 0.9×	326 0.9×	107 0.8×	158 1.3×	190 1.9×	21	1.7k
Bangzhou Zhang China	23	745 1.1×	307 0.9×	92 0.7×	204 1.7×	58 0.6×	47	1.4k
Achal Dhariwal Norway	9	838 1.3×	252 0.7×	156 1.2×	199 1.7×	140 1.4×	15	1.6k
Doug Wendel United States	4	657 1.0×	291 0.8×	97 0.7×	109 0.9×	42 0.4×	5	1.0k
Tiffany Hsu United States	11	735 1.1×	254 0.7×	170 1.3×	83 0.7×	123 1.2×	14	1.3k
Sandra Reitmeier Germany	11	646 1.0×	190 0.5×	101 0.8×	178 1.5×	47 0.5×	20	1.1k
Emilie Muller Luxembourg	21	963 1.5×	493 1.4×	107 0.8×	68 0.6×	254 2.5×	35	1.6k
Adam Robbins‐Pianka United States	9	718 1.1×	362 1.0×	96 0.7×	109 0.9×	187 1.9×	11	1.2k

Countries citing papers authored by Byron J. Smith

Since Specialization

Citations

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

Fields of papers citing papers by Byron J. Smith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Byron J. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Byron J. Smith. A scholar is included among the top collaborators of Byron J. Smith 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 Byron J. Smith. Byron J. Smith 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

Smith, Byron J., Chunyu Zhao, Veronika Dubinkina, et al.. (2025). Accurate estimation of intraspecific microbial gene content variation in metagenomic data with MIDAS v3 and StrainPGC. Genome Research. 35(5). 1247–1260. 1 indexed citations

Zhang, Bing, Kevin M. Magnaye, Jacqueline Moltzau Anderson, et al.. (2024). Sustained mucosal colonization and fecal metabolic dysfunction by Bacteroides associates with fecal microbial transplant failure in ulcerative colitis patients. Scientific Reports. 14(1). 18558–18558. 5 indexed citations

Smith, Byron J., Yvette M. Piceno, Martin Zydek, et al.. (2022). Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis. Scientific Reports. 12(1). 5517–5517. 28 indexed citations

Smith, Byron J., Xiangpeng Li, Zhou Jason Shi, Adam R. Abate, & Katherine S. Pollard. (2022). Scalable Microbial Strain Inference in Metagenomic Data Using StrainFacts. SHILAP Revista de lepidopterología. 2. 867386–867386. 8 indexed citations

Zhao, Chunyu, et al.. (2022). Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables. Current Protocols. 2(12). e604–e604. 1 indexed citations

Smith, Byron J., Richard A. Miller, & Thomas M. Schmidt. (2021). Muribaculaceae Genomes Assembled from Metagenomes Suggest Genetic Drivers of Differential Response to Acarbose Treatment in Mice. mSphere. 6(6). e0085121–e0085121. 94 indexed citations

El‐Nachef, Najwa, Byron J. Smith, Yvette M. Piceno, et al.. (2020). 36 ANTIBIOTIC PRETREATMENT PRIOR TO FECAL MICROBIOTA TRANSPLANTATION INCREASES RATES OF REMISSION IN PATIENTS WITH MILD TO MODERATE ULCERATIVE COLITIS: RESULTS FROM A PILOT RANDOMIZED CLINICAL TRIAL. Gastroenterology. 158(6). S–14. 2 indexed citations

Smith, Byron J., Richard A. Miller, Aaron C. Ericsson, et al.. (2019). Changes in the gut microbiome and fermentation products concurrent with enhanced longevity in acarbose-treated mice. BMC Microbiology. 19(1). 130–130. 243 indexed citations

Smith, Byron J.. (2019). Integrated Analysis of the Gut Microbiota and Their Fermentation Products in Mice Treated with the Longevity Enhancing Drug Acarbose. Deep Blue (University of Michigan).

10.

Smith, Byron J., et al.. (2014). rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Research. 43(D1). D593–D598. 782 indexed citations breakdown →

11.

Olufsen, Mette S., Byron J. Smith, J. Mehlsen, & Johnny T. Ottesen. (2011). The impact of gravity during head-up tilt. PubMed. 2011. 2399–2402. 3 indexed citations

12.

Matthews, K., et al.. (2006). SU-CC-ValA-03: A Directional Algorithm for An Electronically-Collimated Gamma-Ray Detector for Intraoperative Localization of Radiation Sources. Medical Physics. 33(6Part1). 1983–1983. 1 indexed citations

13.

Smith, Byron J., et al.. (2006). TH‐D‐330A‐02: An Electronically‐Collimated Gamma‐Ray Detector for Intraoperative Localization of Radiation Sources. Medical Physics. 33(6Part22). 2277–2277. 1 indexed citations

14.

Rayburn, William F., Byron J. Smith, I Feller, Michael W. Varner, & D. P. Cruikshank. (1984). Major burns during pregnancy: effects on fetal well-being.. PubMed. 63(3). 392–5. 23 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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