Matthew A.M. Devall

886 citations
24 papers · 437 · h-index 12

Impact in

Papers in

Matthew A.M. Devall

23 papers receiving 434 citations

Peers

Matthew A.M. Devall
Comparison fields: 5 of 72
  • Biological Psychiatry 20
  • Clinical Biochemistry 47
  • Aging 8
  • Neurology 34
  • Molecular Biology 275
Replace Virginia Brilhante with:
Virginia Brilhante Finland
Jessica Pfleger United States
Folami Lamoke Powell United States
Eva M. Rico‐Leo Spain
Andy Cheuk‐Him Ng Canada
Jyung Mean Son United States
Wangwei Cai China
Anbo Gao China
Yohan Bignon France
Jiangshan Deng China
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Citations per field
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Citations per year

Countries citing papers authored by Matthew A.M. Devall

Since Specialization
Citations

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

Fields of papers citing papers by Matthew A.M. Devall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew A.M. Devall. 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 Matthew A.M. Devall. The network helps show where Matthew A.M. Devall may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew A.M. Devall, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew A.M. Devall Line = papers co-authored together Matthew A.M. Devall links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017128
2 201440
3 201733
4 202028
5 201626
6 202021
7 202118
8 201517
9 202316
10 202115
11 202214
12 202112
13 202010
14 202110
15 20239
16 20218
17 20217
18 20227
19 20215
20 20224

About Matthew A.M. Devall

Matthew A.M. Devall is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Oncology, Genetics and Cancer Research, having authored 24 papers that have together received 437 indexed citations. Recurring topics across this work include Genetic factors in colorectal cancer (12 papers), Colorectal Cancer Screening and Detection (11 papers), Epigenetics and DNA Methylation (7 papers), RNA modifications and cancer (4 papers), Metabolism and Genetic Disorders (3 papers), Cancer-related molecular mechanisms research (3 papers), Mitochondrial Function and Pathology (3 papers) and Colorectal Cancer Treatments and Studies (2 papers). The work is most often cited by research in Biological Psychiatry (20 citations), Clinical Biochemistry (47 citations), Aging (8 citations), Neurology (34 citations) and Molecular Biology (275 citations). Matthew A.M. Devall has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Katie Lunnon, Jonathan Mill, Graham Casey, Leonard C. Schalkwyk, Steven M. Powell, Michael N. Weedon, Christopher H. Dampier, Magda Tsolaki, Daniel J. Weisenberger and Angela Hodges. Their work appears in journals such as Cancers, Clinical Epigenetics, Human Mutation, Oncotarget and Scientific Reports.

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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