William A. Mattingly

68 total papers · 1.5k total citations
51 papers, 588 citations indexed

About

William A. Mattingly is a scholar working on Epidemiology, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, William A. Mattingly has authored 51 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Epidemiology, 8 papers in Artificial Intelligence and 6 papers in Molecular Biology. Recurrent topics in William A. Mattingly's work include Pneumonia and Respiratory Infections (10 papers), Respiratory viral infections research (8 papers) and Migration, Health and Trauma (5 papers). William A. Mattingly is often cited by papers focused on Pneumonia and Respiratory Infections (10 papers), Respiratory viral infections research (8 papers) and Migration, Health and Trauma (5 papers). William A. Mattingly collaborates with scholars based in United States, Belgium and Argentina. William A. Mattingly's co-authors include F.E. McDonough, Timothy L. Wiemken, Julio A. Ramírez, R.E. Hargrove, Ruth Carrico, J. A. Alford, Paula Peyrani, Stephen Furmanek, Linda P. Posati and John A. Alford and has published in prestigious journals such as SHILAP Revista de lepidopterología, Clinical Infectious Diseases and American Journal of Public Health.

In The Last Decade

William A. Mattingly

47 papers receiving 552 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
William A. Mattingly	180	143	82	57	44	51	588
Yan Wang	111 0.6×	188 1.3×	78 1.0×	20 0.4×	42 1.0×	37	533
A-Reum Kim	98 0.5×	96 0.7×	226 2.8×	53 0.9×	47 1.1×	49	685
Saira Bashir	61 0.3×	111 0.8×	100 1.2×	66 1.2×	28 0.6×	46	622
Jiyoon Jeong	138 0.8×	90 0.6×	129 1.6×	29 0.5×	37 0.8×	46	636
Mehmet Özden	220 1.2×	40 0.3×	95 1.2×	50 0.9×	21 0.5×	42	658
Weilan Wang	54 0.3×	117 0.8×	264 3.2×	41 0.7×	66 1.5×	63	677
Nirmal Kumar Mohakud	210 1.2×	81 0.6×	88 1.1×	45 0.8×	32 0.7×	60	573
Javed Muhammad	76 0.4×	91 0.6×	118 1.4×	36 0.6×	50 1.1×	55	690
Jingjing Xu	103 0.6×	135 0.9×	153 1.9×	26 0.5×	58 1.3×	29	656
G Sridharan	169 0.9×	81 0.6×	116 1.4×	28 0.5×	27 0.6×	39	592

Countries citing papers authored by William A. Mattingly

Since Specialization

Citations

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

Fields of papers citing papers by William A. Mattingly

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William A. Mattingly. 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 William A. Mattingly. The network helps show where William A. Mattingly may publish in the future.

Co-authorship network of co-authors of William A. Mattingly

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

All Works

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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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