Kelli D. Goodman

416 total citations
9 papers, 218 citations indexed

About

Kelli D. Goodman is a scholar working on Molecular Biology, Physiology and Nephrology. According to data from OpenAlex, Kelli D. Goodman has authored 9 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Physiology and 2 papers in Nephrology. Recurrent topics in Kelli D. Goodman's work include Metabolomics and Mass Spectrometry Studies (7 papers), Diet and metabolism studies (3 papers) and Chronic Kidney Disease and Diabetes (2 papers). Kelli D. Goodman is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (7 papers), Diet and metabolism studies (3 papers) and Chronic Kidney Disease and Diabetes (2 papers). Kelli D. Goodman collaborates with scholars based in United States, South Africa and Egypt. Kelli D. Goodman's co-authors include Lisa A. Ford, Douglas R. Toal, Anne M. Evans, Adam D. Kennedy, Luke A. D. Miller, Jacob Wulff, Kirk L. Pappan, Sarah H. Elsea, John J. Lennon and Régis Périchon and has published in prestigious journals such as Cancer Research, Clinical Chemistry and Nutrients.

In The Last Decade

Kelli D. Goodman

8 papers receiving 217 citations

Peers

Kelli D. Goodman

MB

PHYSI

NEPHR

CB

EPIDE

Lisa A. Ford United States

Melaku Mekonnen Agidew Ethiopia

Régis Périchon United States

Moritsugu Kimura Japan

Julia Wenger United States

Giovanni Noberasco Italy

Magdalena P. Cardelo Spain

Akinori Yuri Japan

Katsumi Takemura Japan

Jovia L. Nierenberg United States

Lisa A. Ford United States

Kelli D. Goodman

133 ×1.2

MB

55 ×1.1

PHYSI

48 ×1.3

NEPHR

37 ×1.1

CB

33 ×1.1

EPIDE

Citations per year, relative to Kelli D. Goodman Kelli D. Goodman (= 1×) peers Lisa A. Ford

Countries citing papers authored by Kelli D. Goodman

Since Specialization

Citations

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

Fields of papers citing papers by Kelli D. Goodman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kelli D. Goodman

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

All Works

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9 of 9 papers shown

1.

DeBalsi, Karen L., et al.. (2025). Dried blood spots capture a wide range of metabolic pathways and biological changes associated with exercise. Metabolomics. 22(1). 14–14.

2.

Goodman, Kelli D., Megan R. Showalter, Anne M. Evans, Matthew Mitchell, & Rangaprasad Sarangarajan. (2023). Abstract 6607: Dried blood spot (DBS) sample analysis for drug and metabolomic profiling in oncology clinical trials: Cost-effective decentralized sampling modality for precision oncology. Cancer Research. 83(7_Supplement). 6607–6607. 1 indexed citations

3.

Weber, Annika, Hend Ibrahim, Lansana Sangaré, et al.. (2022). Non-Targeted Dried Blood Spot-Based Metabolomics Analysis Showed Rice Bran Supplementation Effects Multiple Metabolic Pathways during Infant Weaning and Growth in Mali. Nutrients. 14(3). 609–609. 4 indexed citations

4.

Goodman, Kelli D., Matthew Mitchell, Anne M. Evans, et al.. (2021). Assessment of the effects of repeated freeze thawing and extended bench top processing of plasma samples using untargeted metabolomics. Metabolomics. 17(3). 31–31. 13 indexed citations

5.

Tobin, Nicole H., Aisling Murphy, Fan Li, et al.. (2021). Comparison of dried blood spot and plasma sampling for untargeted metabolomics. Metabolomics. 17(7). 62–62. 17 indexed citations

6.

Ford, Lisa A., Adam D. Kennedy, Kelli D. Goodman, et al.. (2020). Precision of a Clinical Metabolomics Profiling Platform for Use in the Identification of Inborn Errors of Metabolism. The Journal of Applied Laboratory Medicine. 5(2). 342–356. 116 indexed citations

7.

Freed, Tiffany A., Josef Coresh, Lesley A. Inker, et al.. (2019). Validation of a Metabolite Panel for a More Accurate Estimation of Glomerular Filtration Rate Using Quantitative LC-MS/MS. Clinical Chemistry. 65(3). 406–418. 17 indexed citations

8.

Coresh, Josef, Lesley A. Inker, Yingying Sang, et al.. (2018). Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study. Nephrology Dialysis Transplantation. 34(5). 825–833. 38 indexed citations

9.

Zhang, Qibo, et al.. (2016). LC–MS/MS method for quantitation of seven biomarkers in human plasma for the assessment of insulin resistance and impaired glucose tolerance. Journal of Chromatography B. 1038. 101–108. 12 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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