Mark V. Sullivan

484 total citations
27 papers, 392 citations indexed

About

Mark V. Sullivan is a scholar working on Analytical Chemistry, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, Mark V. Sullivan has authored 27 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Analytical Chemistry, 13 papers in Biomedical Engineering and 10 papers in Molecular Biology. Recurrent topics in Mark V. Sullivan's work include Analytical chemistry methods development (17 papers), Biosensors and Analytical Detection (9 papers) and Advanced biosensing and bioanalysis techniques (9 papers). Mark V. Sullivan is often cited by papers focused on Analytical chemistry methods development (17 papers), Biosensors and Analytical Detection (9 papers) and Advanced biosensing and bioanalysis techniques (9 papers). Mark V. Sullivan collaborates with scholars based in United Kingdom, Japan and Sweden. Mark V. Sullivan's co-authors include Nicholas W. Turner, Subrayal M. Reddy, Sarah R. Dennison, Joseph M. Hayes, Georgios Archontis, Philippa C. Hawes, Hazim F. EL-Sharif, Jonathan K. Watts, Oliver Clay and Tim Mercer and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Physical Chemistry B and Scientific Reports.

In The Last Decade

Mark V. Sullivan

24 papers receiving 388 citations

Peers

Mark V. Sullivan
Hazim F. EL-Sharif United Kingdom
Mark V. Sullivan
Citations per year, relative to Mark V. Sullivan Mark V. Sullivan (= 1×) peers Hazim F. EL-Sharif

Countries citing papers authored by Mark V. Sullivan

Since Specialization
Citations

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

Fields of papers citing papers by Mark V. Sullivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark V. Sullivan. 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 Mark V. Sullivan. The network helps show where Mark V. Sullivan may publish in the future.

Co-authorship network of co-authors of Mark V. Sullivan

This figure shows the co-authorship network connecting the top 25 collaborators of Mark V. Sullivan. A scholar is included among the top collaborators of Mark V. Sullivan 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 Mark V. Sullivan. Mark V. Sullivan 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.
Sullivan, Mark V., Matthias Klein, Jaligam Murali Mohan, & Amy Q. Shen. (2025). Highly sensitive, real-time cortisol sensing with molecularly imprinted polymer nanoparticles on graphene electrodes in a microfluidic biosensor. Talanta. 299. 129141–129141.
2.
Holden, Mark A., et al.. (2025). Optimised solution-phase synthesis of nanoMIPs for protein detection in electrochemical diagnostics. Biomedical Materials. 20(2). 25043–25043. 4 indexed citations
3.
Shen, Amy Q., et al.. (2025). Solid-phase engineering of molecularly imprinted nanoparticles (NanoMIPs): how template and solid-phase drive polymer composition and binding performance. Journal of Materials Chemistry B. 13(46). 15047–15056. 1 indexed citations
4.
Sullivan, Mark V., Nicholas W. Turner, Francesco Patitucci, et al.. (2025). Development of molecularly imprinted polymers for the detection of human chorionic gonadotropin. Scientific Reports. 15(1). 10436–10436. 2 indexed citations
5.
Singla, Pankaj, Thomas Broughton, Mark V. Sullivan, et al.. (2024). Double Imprinted Nanoparticles for Sequential Membrane‐to‐Nuclear Drug Delivery. Advanced Science. 11(36). e2309976–e2309976. 13 indexed citations
6.
Johnson, Edwin C., Ram R. R. Prasad, Mark V. Sullivan, et al.. (2024). Phage Display Against 2D Metal–Organic Nanosheets as a New Route to Highly Selective Biomolecular Recognition Surfaces. Small. 21(29). e2406339–e2406339. 2 indexed citations
7.
Davies, Julia R., et al.. (2024). Molecularly imprinted nanogels as synthetic recognition materials for the ultrasensitive detection of periodontal disease biomarkers. Analytical and Bioanalytical Chemistry. 416(30). 7305–7316. 13 indexed citations
9.
Sullivan, Mark V., et al.. (2023). Highly Selective Aptamer‐Molecularly Imprinted Polymer Hybrids for Recognition of SARS‐CoV‐2 Spike Protein Variants. SHILAP Revista de lepidopterología. 7(6). 2200215–2200215. 14 indexed citations
10.
Sullivan, Mark V., et al.. (2023). Core-shell magnetic molecularly imprinted polymers: nanoparticles targeting selective androgen receptor modulators (sarms) and steroidal models. SHILAP Revista de lepidopterología. 4(2). 25002–25002. 4 indexed citations
11.
Sullivan, Mark V., et al.. (2023). A rapid synthesis of molecularly imprinted polymer nanoparticles for the extraction of performance enhancing drugs (PIEDs). Nanoscale Advances. 5(19). 5352–5360. 9 indexed citations
12.
Sullivan, Mark V., et al.. (2023). Molecularly imprinted polymer hydrogel sheets with metalloporphyrin-incorporated molecular recognition sites for protein capture. Talanta. 266(Pt 2). 125083–125083. 11 indexed citations
13.
Sullivan, Mark V., et al.. (2023). Utilisation of molecularly imprinting technology for the detection of glucocorticoids for a point of care surface plasmon resonance (SPR) device. Analytica Chimica Acta. 1285. 342004–342004. 16 indexed citations
14.
Sullivan, Mark V., et al.. (2022). A molecularly imprinted polymer nanoparticle-based surface plasmon resonance sensor platform for antibiotic detection in river water and milk. Analytical and Bioanalytical Chemistry. 414(12). 3687–3696. 33 indexed citations
15.
Sullivan, Mark V., Sarah R. Dennison, Joseph M. Hayes, & Subrayal M. Reddy. (2021). Evaluation of acrylamide-based molecularly imprinted polymer thin-sheets for specific protein capture—a myoglobin model. Biomedical Physics & Engineering Express. 7(4). 45025–45025. 17 indexed citations
16.
Sullivan, Mark V., et al.. (2021). Generation of High-Affinity Aptamer-MIP Hybrid Nanoparticles. Methods in molecular biology. 2359. 109–121. 1 indexed citations
17.
EL-Sharif, Hazim F., Nicholas W. Turner, Subrayal M. Reddy, & Mark V. Sullivan. (2021). Application of thymine-based nucleobase-modified acrylamide as a functional co-monomer in electropolymerised thin-film molecularly imprinted polymer (MIP) for selective protein (haemoglobin) binding. Talanta. 240. 123158–123158. 22 indexed citations
19.
Sullivan, Mark V., Sarah R. Dennison, Georgios Archontis, Subrayal M. Reddy, & Joseph M. Hayes. (2019). Toward Rational Design of Selective Molecularly Imprinted Polymers (MIPs) for Proteins: Computational and Experimental Studies of Acrylamide Based Polymers for Myoglobin. The Journal of Physical Chemistry B. 123(26). 5432–5443. 66 indexed citations
20.
Graham, Simon P., Hazim F. EL-Sharif, Rebecca McLean, et al.. (2019). Evaluation of Molecularly Imprinted Polymers as Synthetic Virus Neutralizing Antibody Mimics. Frontiers in Bioengineering and Biotechnology. 7. 115–115. 30 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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