Thomas McIntosh

649 total citations
19 papers, 496 citations indexed

About

Thomas McIntosh is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Immunology. According to data from OpenAlex, Thomas McIntosh has authored 19 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Thomas McIntosh's work include Monoclonal and Polyclonal Antibodies Research (11 papers), Protein purification and stability (5 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). Thomas McIntosh is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (11 papers), Protein purification and stability (5 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). Thomas McIntosh collaborates with scholars based in United States, Belgium and Australia. Thomas McIntosh's co-authors include Hugh M. Davis, David E. Martin, Jonathan Q. Tran, Steven J. Kovacs, Dwight E. Matthews, Weirong Wang, Honghui Zhou, Songmao Zheng, Shiaw‐Lin Wu and Ago Ahene and has published in prestigious journals such as Analytical Chemistry, Cancer Research and Diabetes.

In The Last Decade

Thomas McIntosh

19 papers receiving 468 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas McIntosh United States 12 191 141 126 75 74 19 496
Carsten Schiller Switzerland 5 180 0.9× 223 1.6× 202 1.6× 36 0.5× 107 1.4× 9 799
Carol Astbury United Kingdom 13 82 0.4× 77 0.5× 25 0.2× 52 0.7× 70 0.9× 38 527
Gregory L. Weber United States 12 188 1.0× 60 0.4× 55 0.4× 29 0.4× 68 0.9× 20 480
Scot Eustis United States 10 178 0.9× 76 0.5× 40 0.3× 39 0.5× 63 0.9× 12 701
A. Cordier Switzerland 14 212 1.1× 75 0.5× 14 0.1× 56 0.7× 55 0.7× 30 713
Taiji Sawamoto Japan 17 100 0.5× 27 0.2× 36 0.3× 51 0.7× 159 2.1× 30 644
Hongbin Liu China 10 250 1.3× 60 0.4× 31 0.2× 45 0.6× 37 0.5× 22 483
Elisabeth Niel France 10 287 1.5× 65 0.5× 43 0.3× 27 0.4× 55 0.7× 15 519
Aleš Tichý Czechia 15 464 2.4× 37 0.3× 166 1.3× 16 0.2× 181 2.4× 74 746

Countries citing papers authored by Thomas McIntosh

Since Specialization
Citations

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

Fields of papers citing papers by Thomas McIntosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas McIntosh

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

All Works

19 of 19 papers shown
1.
Sun, Yongliang, Thomas W. McCloskey, Thomas McIntosh, et al.. (2020). Best practices for optimization and validation of flow cytometry‐based receptor occupancy assays. Cytometry Part B Clinical Cytometry. 100(1). 63–71. 5 indexed citations
2.
Jiang, Xiling, et al.. (2018). Development and Translational Application of a Minimal Physiologically Based Pharmacokinetic Model for a Monoclonal Antibody against Interleukin 23 (IL-23) in IL-23-Induced Psoriasis-Like Mice. Journal of Pharmacology and Experimental Therapeutics. 365(1). 140–155. 18 indexed citations
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Zheng, Songmao, Thomas McIntosh, & Weirong Wang. (2015). Utility of free and total target measurements as target engagement and efficacy biomarkers in biotherapeutic development—Opportunities and challenges. The Journal of Clinical Pharmacology. 55(S3). S75–84. 28 indexed citations
5.
Fetterly, Gerald J., Chris H. Takimoto, Shobha Seetharam, et al.. (2013). Utilizing pharmacokinetics/pharmacodynamics modeling to simultaneously examine free CCL2, total CCL2 and carlumab (CNTO 888) concentration time data. The Journal of Clinical Pharmacology. 53(10). 1020–1027. 26 indexed citations
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Han, Chao, Thomas McIntosh, Thomas A. Puchalski, et al.. (2013). A Novel Approach to Evaluate the Pharmacokinetic Biocomparability of a Monoclonal Antibody Derived from Two Different Cell Lines Using Simultaneous Crossover Design. The AAPS Journal. 16(1). 125–128. 3 indexed citations
9.
Kelley, Marian, Ago Ahene, Boris Gorovits, et al.. (2013). Theoretical Considerations and Practical Approaches to Address the Effect of Anti-drug Antibody (ADA) on Quantification of Biotherapeutics in Circulation. The AAPS Journal. 15(3). 646–658. 47 indexed citations
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Seetharam, Shobha, Thomas A. Puchalski, Thomas McIntosh, et al.. (2011). Abstract A37: Development of biologics targeting soluble ligands: Novel biomarker and PK-PD analyzes examining free and total ligand profile following treatment with carlumab (anti-CCL2 mAb).. Molecular Cancer Therapeutics. 10(11_Supplement). A37–A37. 1 indexed citations
12.
Lu, Qiaozhen, Xiaoyang Zheng, Thomas McIntosh, et al.. (2009). Development of Different Analysis Platforms with LC−MS for Pharmacokinetic Studies of Protein Drugs. Analytical Chemistry. 81(21). 8715–8723. 57 indexed citations
13.
McIntosh, Thomas, et al.. (2002). A Liquid Chromatography–Mass Spectrometry Method to Measure Stable Isotopic Tracer Enrichments of Glycerol and Glucose in Human Serum. Analytical Biochemistry. 300(2). 163–169. 64 indexed citations
14.
Jucker, Beat M., Thomas Schaeffer, Thomas McIntosh, et al.. (2002). Normalization of Skeletal Muscle Glycogen Synthesis and Glycolysis in Rosiglitazone-Treated Zucker Fatty Rats. Diabetes. 51(7). 2066–2073. 23 indexed citations
15.
Tran, Jonathan Q., Steven J. Kovacs, Thomas McIntosh, Hugh M. Davis, & David E. Martin. (1999). Morning Spot and 24‐Hour Urinary 6β‐Hydroxycortisol to Cortisol Ratios: Intraindividual Variability and Correlation under Basal Conditions and Conditions of CYP 3A4 Induction. The Journal of Clinical Pharmacology. 39(5). 487–494. 58 indexed citations
16.
Tran, Jonathan Q., Steven J. Kovacs, Thomas McIntosh, Hugh M. Davis, & David E. Martin. (1999). Morning spot and 24-hour urinary 6 beta-hydroxycortisol to cortisol ratios: intraindividual variability and correlation under basal conditions and conditions of CYP 3A4 induction.. PubMed. 39(5). 487–94. 65 indexed citations
17.
McIntosh, Thomas, et al.. (1989). The agronomic landspreading of coal bottom ash: Using a regulated solid waste as a resource. Resources Conservation and Recycling. 2(2). 119–129. 25 indexed citations
18.
Eisenstein, Toby K., et al.. (1983). Quantitation of in vitro opsonic activity of human antibody induced by a vaccine consisting of the type III-specific polysaccharide of group B streptococcus. Infection and Immunity. 39(3). 1155–1160. 11 indexed citations
19.

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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