Matthew J. Callow

21 papers receiving 2.7k citations

Matthew J. Callow's Hit Papers

Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays 2009 · 956 citations
9560+8+16Years since publication2505007501000

Peers

Matthew J. Callow
Comparison fields: 5 of 150
  • Genetics 740
  • Cancer Research 348
  • Molecular Biology 1.7k
  • Endocrinology, Diabetes and Metabolism 143
  • Biophysics 40
Replace Eugene Chudin with:
Eugene Chudin United States
David Montaner Spain
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Yi Zhu China
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Citations per year

Countries citing papers authored by Matthew J. Callow

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Callow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. Callow. 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 J. Callow. The network helps show where Matthew J. Callow may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew J. Callow, 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 J. Callow Line = papers co-authored together Matthew J. Callow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS
Hit paper breakdown →
20021080
2
Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays
Hit paper breakdown →
2009956
3 2012156
4 1994146
5 2003113
6 199585
7 199577
8 198644
9 198744
10 199042
11 200039
12 202015
13 199111
14 200711
15 19949
16
Charge effects on chylomicron clearance in rats.
19936
17 19936
18 20225
19 20044
20 20022

About Matthew J. Callow

Matthew J. Callow is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics, Molecular Biology, Biochemistry and Hematology, having authored 21 papers that have together received 2.9k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), RNA and protein synthesis mechanisms (3 papers), Advanced biosensing and bioanalysis techniques (3 papers), Lipid metabolism and biosynthesis (2 papers), Gene expression and cancer classification (2 papers) and Diabetes Management and Research (2 papers). The work is most often cited by research in Genetics (740 citations), Cancer Research (348 citations), Molecular Biology (1.7k citations), Endocrinology, Diabetes and Metabolism (143 citations) and Biophysics (40 citations). Matthew J. Callow has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Sandrine Dudoit, Jean Yee Hwa Yang, Terence Paul Speed, Edward A. Rubin, Trevor G. Redgrave, Peter E Bundred, John T. Manning, E M Rubin, Richard M. Lawn and Ravi Tangirala. Their work appears in journals such as Nucleic Acids Research, Proceedings of the National Academy of Sciences, American Journal of Physiology-Gastrointestinal and Liver Physiology, Diseases of the Colon & Rectum and Metabolism.

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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