Charles Schmitt

2.4k total citations · 1 hit paper
53 papers, 1.4k citations indexed

About

Charles Schmitt is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis and Artificial Intelligence. According to data from OpenAlex, Charles Schmitt has authored 53 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 13 papers in Health, Toxicology and Mutagenesis and 10 papers in Artificial Intelligence. Recurrent topics in Charles Schmitt's work include Biomedical Text Mining and Ontologies (12 papers), Health, Environment, Cognitive Aging (10 papers) and Computational Drug Discovery Methods (7 papers). Charles Schmitt is often cited by papers focused on Biomedical Text Mining and Ontologies (12 papers), Health, Environment, Cognitive Aging (10 papers) and Computational Drug Discovery Methods (7 papers). Charles Schmitt collaborates with scholars based in United States, Canada and Brazil. Charles Schmitt's co-authors include David Borland, Marc Niethammer, J. S. Marron, Xiaojun Guan, John T. Woosley, Nancy E. Thomas, Chris Bizon, Alexander Tropsha, Vinícius M. Alves and Eugene Muratov and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Charles Schmitt

48 papers receiving 1.3k 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.

A method for normalizing histology slides for quantitative analysis

2009 726 citations Marc Niethammer, J. S. Marron et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Charles Schmitt United States	14	648	363	342	265	179	53	1.4k
Alexis B. Carter United States	20	627 1.0×	130 0.4×	333 1.0×	402 1.5×	186 1.0×	50	1.9k
Nina Linder Finland	24	743 1.1×	300 0.8×	633 1.9×	490 1.8×	184 1.0×	57	2.1k
Juan Liu China	26	433 0.7×	138 0.4×	255 0.7×	1.2k 4.5×	44 0.2×	168	2.2k
Pegah Khosravi United States	14	439 0.7×	102 0.3×	398 1.2×	316 1.2×	79 0.4×	25	1.3k
Marco Masseroli Italy	23	310 0.5×	66 0.2×	78 0.2×	1.0k 3.9×	53 0.3×	135	2.0k
Eric F. Lock United States	16	133 0.2×	52 0.1×	81 0.2×	710 2.7×	25 0.1×	70	1.4k
A. K. Bhattacharyya United States	29	739 1.1×	151 0.4×	392 1.1×	874 3.3×	190 1.1×	62	3.3k
Mikael Lundin Finland	32	869 1.3×	320 0.9×	869 2.5×	1.3k 4.9×	220 1.2×	76	4.4k
Mingon Kang United States	17	246 0.4×	74 0.2×	176 0.5×	457 1.7×	26 0.1×	68	984

Countries citing papers authored by Charles Schmitt

Since Specialization

Citations

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

Fields of papers citing papers by Charles Schmitt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charles Schmitt

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chan, Lauren, Elena Casiraghi, Justin Reese, et al.. (2024). Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests. International Journal of Medical Informatics. 187. 105461–105461. 4 indexed citations

House, John S., Farida S. Akhtari, Charles Schmitt, et al.. (2024). Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study. PubMed. 4(1). osae003–osae003. 1 indexed citations

Lin, Dawei, Matthew McAuliffe, Kim D. Pruitt, et al.. (2024). Biomedical Data Repository Concepts and Management Principles. Scientific Data. 11(1). 622–622. 7 indexed citations

Borrel, Alexandre, et al.. (2023). ChemMaps.com v2.0: exploring the environmental chemical universe. Nucleic Acids Research. 51(W1). W78–W82. 2 indexed citations

Holmgren, Stephanie, Shannon Bell, Jessica Wignall, et al.. (2023). Workshop Report: Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Harmonized Language. International Journal of Environmental Research and Public Health. 20(3). 2317–2317. 3 indexed citations

Schmitt, Charles, Jeanette A. Stingone, Arcot Rajasekar, et al.. (2023). A roadmap to advance exposomics through federation of data. PubMed. 3(1). 5 indexed citations

Akhtari, Farida S., David C. Fargo, Charles Schmitt, et al.. (2022). The skin is no barrier to mixtures: Air pollutant mixtures and reported psoriasis or eczema in the Personalized Environment and Genes Study (PEGS). Journal of Exposure Science & Environmental Epidemiology. 33(3). 474–481. 18 indexed citations

Ayala‐Ramirez, Montserrat, John A. McGrath, Farida S. Akhtari, et al.. (2022). Association of distance to swine concentrated animal feeding operations with immune-mediated diseases: An exploratory gene-environment study. Environment International. 171. 107687–107687. 8 indexed citations

Holmgren, Stephanie, Rebecca Boyles, Ryan Cronk, et al.. (2021). Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language. International Journal of Environmental Research and Public Health. 18(17). 8985–8985. 7 indexed citations

10.

Fecho, Karamarie, Chris Bizon, Frederick W. Miller, et al.. (2021). A Biomedical Knowledge Graph System to Propose Mechanistic Hypotheses for Real-World Environmental Health Observations: Cohort Study and Informatics Application. JMIR Medical Informatics. 9(7). e26714–e26714. 15 indexed citations

11.

Walker, Vickie R., Charles Schmitt, Mary S. Wolfe, et al.. (2021). Evaluation of a semi-automated data extraction tool for public health literature-based reviews: Dextr. Environment International. 159. 107025–107025. 18 indexed citations

12.

Appold, Stephen J., Saravanan Arunachalam, Steven J. Cox, et al.. (2020). Translator Exposure APIs: Open Access to Data on Airborne Pollutant Exposures, Roadway Exposures, and Socio-Environmental Exposures and Use Case Application. International Journal of Environmental Research and Public Health. 17(14). 5243–5243. 4 indexed citations

13.

Schmitt, Charles, et al.. (2018). Overview of the TAC 2018 Systematic Review Information Extraction Track.. Theory and applications of categories. 4 indexed citations

14.

Fecho, Karamarie, et al.. (2016). SSWiS: An Information System for Graduate Education in Social Work. Preprints.org. 1 indexed citations

15.

Mane, Ketan K., Chris Bizon, Charles Schmitt, et al.. (2011). VisualDecisionLinc: A visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry. Journal of Biomedical Informatics. 45(1). 101–106. 43 indexed citations

16.

Mane, Ketan K., Chris Bizon, Phillips Owen, et al.. (2011). Patient Electronic Health Data–Driven Approach to Clinical Decision Support. Clinical and Translational Science. 4(5). 369–371. 5 indexed citations

17.

Niethammer, Marc, J. S. Marron, David Borland, et al.. (2009). A method for normalizing histology slides for quantitative analysis. 1107–1110. 726 indexed citations breakdown →

18.

Inokuma, Margaret, Corazon dela Rosa, Charles Schmitt, et al.. (2007). Functional T Cell Responses to Tumor Antigens in Breast Cancer Patients Have a Distinct Phenotype and Cytokine Signature. The Journal of Immunology. 179(4). 2627–2633. 38 indexed citations

19.

Špidlen, Josef, Robert Gentleman, Perry Haaland, et al.. (2006). Data Standards for Flow Cytometry. OMICS A Journal of Integrative Biology. 10(2). 209–214. 21 indexed citations

20.

Merle‐Béral, Hélène, Charles Schmitt, Djavad Mossalayi, et al.. (1993). Interleukin-7 and malignant T cells.. PubMed. 35(3). 231–2. 3 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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