Nathan D. Price

27.8k total citations · 4 hit papers
204 papers, 11.3k citations indexed

About

Nathan D. Price is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Nathan D. Price has authored 204 papers receiving a total of 11.3k indexed citations (citations by other indexed papers that have themselves been cited), including 143 papers in Molecular Biology, 25 papers in Biomedical Engineering and 20 papers in Genetics. Recurrent topics in Nathan D. Price's work include Microbial Metabolic Engineering and Bioproduction (58 papers), Bioinformatics and Genomic Networks (46 papers) and Gene Regulatory Network Analysis (29 papers). Nathan D. Price is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (58 papers), Bioinformatics and Genomic Networks (46 papers) and Gene Regulatory Network Analysis (29 papers). Nathan D. Price collaborates with scholars based in United States, China and Russia. Nathan D. Price's co-authors include Bernhard Ø. Palsson, Leroy Hood, Jennifer L. Reed, Jason A. Papin, James A. Eddy, Sriram Chandrasekaran, Cory C. Funk, Andrew T. Magis, Jennifer C. Lovejoy and Sean M. Gibbons and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nucleic Acids Research.

In The Last Decade

Nathan D. Price

198 papers receiving 11.1k 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.

Genome-scale models of microbial cells: evaluating the consequences of constraints

2004 772 citations Nathan D. Price et al. profile →
Health and disease markers correlate with gut microbiome composition across thousands of people

2020 550 citations Nathan D. Price, Jennifer C. Lovejoy et al. Nature Communications profile →
Multiscale Analysis of Independent Alzheimer’s Cohorts Finds Disruption of Molecular, Genetic, and Clinical Networks by Human Herpesvirus

2018 471 citations Cory C. Funk, Matthew A. Richards et al. profile →
P4 Medicine: How Systems Medicine Will Transform the Healthcare Sector and Society

2013 360 citations Gustavo Glusman, Nathan D. Price et al. profile →

Peers

Nathan D. Price

PHYSI

GENET

EPIDE

Peter Nilsson Sweden

Wei Zheng United States

Sergio Bernardini Italy

Jake Y. Chen United States

Robert Powers United States

Christopher P. Austin United States

Rainer Bischoff Netherlands

Aiping Lü China

Bernhard Küster Germany

Jan Baumbach Germany

Peter Nilsson Sweden

Nathan D. Price

5.7k ×0.7

1.3k ×0.8

1.1k ×0.9

PHYSI

1.0k ×1.0

GENET

641 ×0.9

EPIDE

Citations per year, relative to Nathan D. Price Nathan D. Price (= 1×) peers Peter Nilsson

Countries citing papers authored by Nathan D. Price

Since Specialization

Citations

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

Fields of papers citing papers by Nathan D. Price

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nathan D. Price

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

All Works

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20 of 20 papers shown

Pearl, Jocelynn R., Amol C. Shetty, Jeffrey P. Cantle, et al.. (2025). Altered huntingtin−chromatin interactions predict transcriptional and epigenetic changes in Huntington's disease. Disease Models & Mechanisms. 18(5). 1 indexed citations

Pflieger, Lance, et al.. (2025). Bile acids segregate metabolic syndrome in a cohort of 100 deeply phenotyped horses. Communications Biology. 8(1). 1711–1711.

Paquette, Alison G., et al.. (2024). Accelerating adverse pregnancy outcomes research amidst rising medication use: parallel retrospective cohort analyses for signal prioritization. BMC Medicine. 22(1). 495–495.

Yurkovich, James T., Simon J. Evans, Noa Rappaport, et al.. (2023). The transition from genomics to phenomics in personalized population health. Nature Reviews Genetics. 25(4). 286–302. 27 indexed citations

Wainberg, Michael, Zeyuan Song, Stacy L. Andersen, et al.. (2022). Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring. GeroScience. 44(2). 719–729. 7 indexed citations

Lind, Margaret L., Alexander J. Robertson, Julio Silva, et al.. (2022). Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case–control analysis. PLoS Medicine. 19(12). e1004136–e1004136. 11 indexed citations

Durant, Thomas J S, Sarah Dudgeon, Nathan D. Price, et al.. (2021). Applications of Digital Microscopy and Densely Connected Convolutional Neural Networks for Automated Quantification of Babesia-Infected Erythrocytes. Clinical Chemistry. 68(1). 218–229. 13 indexed citations

Arif, Muhammad, Cheng Zhang, Xiangyü Li, et al.. (2021). iNetModels 2.0: an interactive visualization and database of multi-omics data. Nucleic Acids Research. 49(W1). W271–W276. 29 indexed citations

Baloni, Priyanka, Kwangsik Nho, Matthias Arnold, et al.. (2021). Investigating the importance of acylcarnitines in Alzheimer's disease.. PuSH - Publication Server of Helmholtz Zentrum München. 1 indexed citations

10.

Zimmer, Anat, Yael Korem, Noa Rappaport, et al.. (2021). The geometry of clinical labs and wellness states from deeply phenotyped humans. Nature Communications. 12(1). 3578–3578. 10 indexed citations

11.

Funk, Cory C., et al.. (2020). iREAD: a tool for intron retention detection from RNA-seq data. BMC Genomics. 21(1). 38 indexed citations

12.

Wainberg, Michael, Andrew T. Magis, John C. Earls, et al.. (2020). Multiomic blood correlates of genetic risk identify presymptomatic disease alterations. Proceedings of the National Academy of Sciences. 117(35). 21813–21820. 21 indexed citations

13.

Gilley, James R., et al.. (2020). The Quest for an Independent Scotland: The Impact of Culture, Economics, and International Relations Theory on Votes of Self-Determination. Carroll Collected (John Carroll University). 25(1). 1 indexed citations

14.

Paquette, Alison G., Oksana Shynlova, Xiaogang Wu, et al.. (2019). MicroRNA‐transcriptome networks in whole blood and monocytes of women undergoing preterm labour. Journal of Cellular and Molecular Medicine. 23(10). 6835–6845. 20 indexed citations

15.

Yurkovich, James T., Qiang Tian, Nathan D. Price, & Leroy Hood. (2019). A systems approach to clinical oncology uses deep phenotyping to deliver personalized care. Nature Reviews Clinical Oncology. 17(3). 183–194. 37 indexed citations

16.

Baloni, Priyanka, Vineet Sangar, James T. Yurkovich, et al.. (2019). Genome-scale metabolic model of the rat liver predicts effects of diet restriction. Scientific Reports. 9(1). 9807–9807. 9 indexed citations

17.

Madduri, Ravi, Kyle Chard, Mike D’Arcy, et al.. (2019). Reproducible big data science: A case study in continuous FAIRness. PLoS ONE. 14(4). e0213013–e0213013. 23 indexed citations

18.

Farrah, Terry, et al.. (2017). ProbAnnoWeb and ProbAnnoPy: probabilistic annotation and gap-filling of metabolic reconstructions. Bioinformatics. 34(9). 1594–1596. 4 indexed citations

19.

Price, Nathan D., et al.. (2014). Promoting Wellness & Demystifying Disease: The 100K Project. 1(3). 20–23. 19 indexed citations

20.

Craig, Theodore A., Yuji Zhang, Andrew T. Magis, et al.. (2014). Detection of 1α,25-Dihydroxyvitamin D-Regulated miRNAs in Zebrafish by Whole Transcriptome Sequencing. Zebrafish. 11(3). 207–218. 10 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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