Charlotte Nelson

1.8k total citations · 1 hit paper
14 papers, 998 citations indexed

About

Charlotte Nelson is a scholar working on Molecular Biology, Artificial Intelligence and Neurology. According to data from OpenAlex, Charlotte Nelson has authored 14 papers receiving a total of 998 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Artificial Intelligence and 2 papers in Neurology. Recurrent topics in Charlotte Nelson's work include Biomedical Text Mining and Ontologies (7 papers), Machine Learning in Healthcare (3 papers) and Bioinformatics and Genomic Networks (3 papers). Charlotte Nelson is often cited by papers focused on Biomedical Text Mining and Ontologies (7 papers), Machine Learning in Healthcare (3 papers) and Bioinformatics and Genomic Networks (3 papers). Charlotte Nelson collaborates with scholars based in United States, Australia and Canada. Charlotte Nelson's co-authors include Sergio E. Baranzini, Egle Cekanaviciute, Ilana Katz Sand, Bruce Cree, Tessel F. Runia, Rob Knight, Justine W. Debelius, Sarkis K. Mazmanian, Patrizia Casaccia and Elizabeth Crabtree‐Hartman and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

In The Last Decade

Charlotte Nelson

13 papers receiving 983 citations

Hit Papers

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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.

Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models

2017 730 citations Egle Cekanaviciute, Bryan B. Yoo et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Charlotte Nelson United States	9	748	147	147	135	116	14	998
Simone Baldi Italy	15	466 0.6×	184 1.3×	88 0.6×	55 0.4×	67 0.6×	52	825
Leigh Maher United States	9	726 1.0×	260 1.8×	200 1.4×	126 0.9×	58 0.5×	12	1.3k
Qi‐Kui Chen China	19	677 0.9×	182 1.2×	80 0.5×	28 0.2×	91 0.8×	39	1.3k
Paromita Mukherjee United States	4	813 1.1×	230 1.6×	123 0.8×	116 0.9×	51 0.4×	6	1.1k
Duncan Horlock Australia	11	710 0.9×	496 3.4×	72 0.5×	55 0.4×	77 0.7×	14	1.1k
Jiangtao Jin China	10	504 0.7×	215 1.5×	45 0.3×	152 1.1×	39 0.3×	15	1.0k
Gladys Ferrere France	9	462 0.6×	157 1.1×	92 0.6×	42 0.3×	46 0.4×	12	980
Xiaoqing Li China	15	463 0.6×	133 0.9×	106 0.7×	22 0.2×	35 0.3×	57	909
Zhengzheng Yan China	15	489 0.7×	87 0.6×	78 0.5×	34 0.3×	26 0.2×	24	878
Yael Haberman Israel	17	395 0.5×	208 1.4×	76 0.5×	30 0.2×	92 0.8×	44	826

Countries citing papers authored by Charlotte Nelson

Since Specialization

Citations

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

Fields of papers citing papers by Charlotte Nelson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charlotte Nelson

This figure shows the co-authorship network connecting the top 25 collaborators of Charlotte Nelson. A scholar is included among the top collaborators of Charlotte Nelson 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 Charlotte Nelson. Charlotte Nelson 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

Nelson, Charlotte & Katie E. Marshall. (2025). Preprints in comparative physiology – a guide for the preprint curious. Journal of Experimental Biology. 228(13). 1 indexed citations

Soman, Karthik, Peter W. Rose, John H. Morris, et al.. (2024). Biomedical knowledge graph-optimized prompt generation for large language models. Bioinformatics. 40(9). 30 indexed citations

Soman, Karthik, Charlotte Nelson, Gabriel Cerono, et al.. (2023). Early detection of Parkinson’s disease through enriching the electronic health record using a biomedical knowledge graph. Frontiers in Medicine. 10. 1081087–1081087. 14 indexed citations

Baranzini, Sergio E., Katy Börner, John P. Morris, et al.. (2022). A biomedical open knowledge network harnesses the power of AI to understand deep human biology. AI Magazine. 43(1). 46–58. 6 indexed citations

Baranzini, Sergio E., Katy Börner, John P. Morris, et al.. (2022). A Biomedical Open Knowledge Network Harnesses the Power of AI to Understand Deep Human Biology. AI Magazine. 43(1). 46–58. 6 indexed citations

Soman, Karthik, Charlotte Nelson, Gabriel Cerono, & Sergio E. Baranzini. (2022). Time-aware Embeddings of Clinical Data using a Knowledge Graph. PubMed. 28. 97–108. 3 indexed citations

Nelson, Charlotte, Riley Bove, Atul J. Butte, & Sergio E. Baranzini. (2021). Embedding electronic health records onto a knowledge network recognizes prodromal features of multiple sclerosis and predicts diagnosis. Journal of the American Medical Informatics Association. 29(3). 424–434. 30 indexed citations

Nelson, Charlotte, Amber M. Paul, Ryan T. Scott, et al.. (2021). Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases. Life. 11(1). 42–42. 7 indexed citations

Nelson, Charlotte, et al.. (2020). Mutations in domain IV of elongation factor EF-G confer −1 frameshifting. RNA. 27(1). 40–53. 11 indexed citations

10.

Nelson, Charlotte, Atul J. Butte, & Sergio E. Baranzini. (2019). Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings. Nature Communications. 10(1). 3045–3045. 41 indexed citations

11.

Cekanaviciute, Egle, Bryan B. Yoo, Tessel F. Runia, et al.. (2017). Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models. Proceedings of the National Academy of Sciences. 114(40). 10713–10718. 730 indexed citations breakdown →

12.

Cekanaviciute, Egle, Justine W. Debelius, Sudha Singh, et al.. (2016). Gut dysbiosis is a feature of MS and it is characterized by bacteria able to regulate lymphocyte differentiation in vitro. CaltechAUTHORS (California Institute of Technology). 8 indexed citations

13.

Tee, Andrew E., Dora Ling, Charlotte Nelson, et al.. (2014). The histone demethylase JMJD1A induces cell migration and invasion by up-regulating the expression of the long noncoding RNA MALAT1. Oncotarget. 5(7). 1793–1804. 97 indexed citations

14.

Ling, Dora, Glenn M. Marshall, Pei Y. Liu, et al.. (2012). Enhancing the anticancer effect of the histone deacetylase inhibitor by activating transglutaminase. European Journal of Cancer. 48(17). 3278–3287. 14 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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