Tom Morrison

2.3k total citations · 1 hit paper
29 papers, 1.6k citations indexed

About

Tom Morrison is a scholar working on Molecular Biology, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Tom Morrison has authored 29 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 5 papers in Mechanical Engineering and 4 papers in Mechanics of Materials. Recurrent topics in Tom Morrison's work include Molecular Biology Techniques and Applications (7 papers), Gene expression and cancer classification (6 papers) and Non-Destructive Testing Techniques (4 papers). Tom Morrison is often cited by papers focused on Molecular Biology Techniques and Applications (7 papers), Gene expression and cancer classification (6 papers) and Non-Destructive Testing Techniques (4 papers). Tom Morrison collaborates with scholars based in United States, Canada and United Kingdom. Tom Morrison's co-authors include Carl T. Wittwer, Janis J. Weis, Janis J. Weis, John H. Weis, Ying Ma, Colin J. H. Brenan, R. Mark Wooten, Samuel D. Wright, Rolf Thieringer and Tanya S. Kanigan and has published in prestigious journals such as Nucleic Acids Research, The Journal of Immunology and Biochemistry.

In The Last Decade

Tom Morrison

29 papers receiving 1.6k citations

Hit Papers

Quantification of low-copy transcripts by continuous SYBR... 1998 2026 2007 2016 1998 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Morrison United States 13 721 261 259 221 174 29 1.6k
Lee Ann Sporn United States 19 366 0.5× 246 0.9× 162 0.6× 430 1.9× 100 0.6× 33 1.7k
Jerry R. Malayer United States 31 625 0.9× 126 0.5× 132 0.5× 454 2.1× 443 2.5× 70 2.2k
Jonathan H. Lass United States 28 463 0.6× 152 0.6× 353 1.4× 377 1.7× 158 0.9× 65 3.0k
Yadong Zheng China 32 671 0.9× 430 1.6× 154 0.6× 134 0.6× 60 0.3× 147 3.6k
Clive Wells United States 24 459 0.6× 264 1.0× 171 0.7× 219 1.0× 75 0.4× 65 2.1k
Janis J. Weis United States 6 512 0.7× 127 0.5× 199 0.8× 322 1.5× 107 0.6× 6 1.4k
Hongbin He China 29 854 1.2× 313 1.2× 615 2.4× 378 1.7× 324 1.9× 166 2.7k
Hiroki Sakai Japan 25 548 0.8× 241 0.9× 158 0.6× 146 0.7× 234 1.3× 243 2.2k
Shuhong Luo China 29 853 1.2× 247 0.9× 149 0.6× 410 1.9× 328 1.9× 91 2.2k
Takafumi Ito Japan 26 468 0.6× 112 0.4× 214 0.8× 921 4.2× 124 0.7× 82 1.8k

Countries citing papers authored by Tom Morrison

Since Specialization
Citations

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

Fields of papers citing papers by Tom Morrison

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Morrison

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

All Works

20 of 20 papers shown
1.
Devonshire, Alison S., Richard Dillon, Christian Thiede, et al.. (2024). Recommendations from the AML molecular MRD expert advisory board. Leukemia. 38(7). 1638–1641. 2 indexed citations
2.
Willey, James C., Tom Morrison, Erin L. Crawford, et al.. (2021). Advancing NGS quality control to enable measurement of actionable mutations in circulating tumor DNA. Cell Reports Methods. 1(7). 100106–100106. 11 indexed citations
3.
Cleveland, Megan H., Eric Delwart, Jim F. Huggett, et al.. (2020). Report of the 2019 NIST-FDA workshop on standards for next generation sequencing detection of viral adventitious agents in biologics and biomanufacturing. Biologicals. 64. 76–82. 10 indexed citations
5.
Morrison, Tom, et al.. (2015). Analysis of Borehole Jack Ice Strength Data Using Quantile Regression. Proceedings of the International Conference on Port and Ocean Engineering Under Arctic Conditions. 1 indexed citations
6.
Massingham, Lauren, Kirby L. Johnson, Diana W. Bianchi, et al.. (2011). Proof of Concept Study to Assess Fetal Gene Expression in Amniotic Fluid by NanoArray PCR. Journal of Molecular Diagnostics. 13(5). 565–570. 11 indexed citations
7.
Brenan, Colin J. H., et al.. (2008). A nanofluidic system for massively parallel PCR. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6886. 688609–688609. 1 indexed citations
8.
Morrison, Tom, James Hurley, Karl Yoder, et al.. (2006). Nanoliter high throughput quantitative PCR. Nucleic Acids Research. 34(18). e123–e123. 182 indexed citations
9.
Brenan, Colin J. H. & Tom Morrison. (2005). High throughput, nanoliter quantitative PCR. Drug Discovery Today Technologies. 2(3). 247–253. 15 indexed citations
10.
Morrison, Tom. (2003). A Cleaner Future.. American school & university. 75(10). 54–57. 1 indexed citations
11.
Worthingham, Robert, et al.. (2002). Bayesian Estimates of Measurement Error for In-Line Inspection and Field Tools. 1865–1873. 1 indexed citations
12.
Worthingham, Robert, et al.. (2000). Comparison of Estimates From a Growth Model 5 Years After the Previous Inspection. 4 indexed citations
13.
Morrison, Tom, et al.. (2000). Validation of an In-Line Inspection Metal Loss Tool. 3 indexed citations
14.
Weis, Janis J., Barbara A. McCracken, Ying Ma, et al.. (1999). Identification of Quantitative Trait Loci Governing Arthritis Severity and Humoral Responses in the Murine Model of Lyme Disease. The Journal of Immunology. 162(2). 948–956. 99 indexed citations
15.
Morrison, Tom, Ying Ma, John H. Weis, & Janis J. Weis. (1999). Rapid and Sensitive Quantification of Borrelia burgdorferi -Infected Mouse Tissues by Continuous Fluorescent Monitoring of PCR. Journal of Clinical Microbiology. 37(4). 987–992. 171 indexed citations
16.
Morrison, Tom. (1998). Quantification of low-copy transcripts by cantinuous SYBR Green monitoring during amplification. BioTechniques. 24. 952–962. 2 indexed citations
17.
Wooten, R. Mark, Tom Morrison, John H. Weis, et al.. (1998). The Role of CD14 in Signaling Mediated by Outer Membrane Lipoproteins of Borrelia burgdorferi. The Journal of Immunology. 160(11). 5485–5492. 126 indexed citations
18.
Morrison, Tom, Janis J. Weis, & Carl T. Wittwer. (1998). Quantification of low-copy transcripts by continuous SYBR Green I monitoring during amplification.. PubMed. 24(6). 954–8, 960, 962. 765 indexed citations breakdown →
19.
Mangat, Naurang Singh, et al.. (1998). Estimation of Measurement Errors. 315–325. 23 indexed citations
20.
McEvoy, Megan M., Hongjun Zhou, Amy F. Roth, et al.. (1995). Nuclear magnetic resonance assignments and global fold of a CheY-binding domain in CheA, the chemotaxis-specific kinase of Escherichia coli. Biochemistry. 34(42). 13871–13880. 25 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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