Paul A. Dalby

4.7k total citations
126 papers, 3.4k citations indexed

About

Paul A. Dalby is a scholar working on Molecular Biology, Biochemistry and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Paul A. Dalby has authored 126 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 108 papers in Molecular Biology, 36 papers in Biochemistry and 26 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Paul A. Dalby's work include Microbial Metabolic Engineering and Bioproduction (41 papers), Protein purification and stability (36 papers) and Biochemical Acid Research Studies (34 papers). Paul A. Dalby is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (41 papers), Protein purification and stability (36 papers) and Biochemical Acid Research Studies (34 papers). Paul A. Dalby collaborates with scholars based in United Kingdom, United States and Denmark. Paul A. Dalby's co-authors include Haoran Yu, John M. Ward, Gary J. Lye, Edward G. Hibbert, John M. Woodley, Mark E. B. Smith, Cheng Zhang, Frank Baganz, Yihan Yan and Seán J. Costelloe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Paul A. Dalby

121 papers receiving 3.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Paul A. Dalby United Kingdom	35	2.7k	665	584	433	394	126	3.4k
Amir Aharoni Israel	25	2.6k 1.0×	316 0.5×	348 0.6×	162 0.4×	328 0.8×	75	4.0k
Koen H. G. Verschueren Belgium	14	2.3k 0.8×	296 0.4×	241 0.4×	103 0.2×	603 1.5×	23	3.3k
Jason Micklefield United Kingdom	39	3.8k 1.4×	198 0.3×	524 0.9×	165 0.4×	283 0.7×	120	5.2k
Paul Fitzpatrick United States	31	1.9k 0.7×	143 0.2×	205 0.4×	71 0.2×	233 0.6×	65	3.1k
Gill Stephens United Kingdom	33	1.9k 0.7×	115 0.2×	642 1.1×	68 0.2×	202 0.5×	94	3.1k
P.D.G. Dean United Kingdom	29	1.7k 0.6×	182 0.3×	240 0.4×	340 0.8×	240 0.6×	92	2.5k
Masafumi Noda Japan	22	2.0k 0.7×	135 0.2×	114 0.2×	137 0.3×	372 0.9×	63	2.8k
William C. Kenney United States	26	1.4k 0.5×	229 0.3×	118 0.2×	236 0.5×	168 0.4×	50	2.2k
Natarajan Venkatesan United States	32	1.7k 0.6×	120 0.2×	180 0.3×	345 0.8×	189 0.5×	87	3.4k
Nuno M. F. S. A. Cerqueira Portugal	30	1.6k 0.6×	198 0.3×	173 0.3×	48 0.1×	396 1.0×	93	2.9k

Countries citing papers authored by Paul A. Dalby

Since Specialization

Citations

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

Fields of papers citing papers by Paul A. Dalby

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul A. Dalby. 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 Paul A. Dalby. The network helps show where Paul A. Dalby may publish in the future.

Co-authorship network of co-authors of Paul A. Dalby

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

All Works

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20 of 20 papers shown

Abeln, Sanne, Paul A. Dalby, Heidi Goenaga‐Infante, et al.. (2025). Neurofilament Light Chain under the Lens of Structural Mass Spectrometry. ACS Chemical Neuroscience. 16(2). 141–151. 4 indexed citations

Zhang, Yaqian, Zhongwei Niu, Weina Li, et al.. (2025). Insights into type III collagen α1 chain remodeling: Mechanisms of enhanced cell adhesion in wound healing. International Journal of Biological Macromolecules. 318(Pt 3). 145085–145085. 1 indexed citations

Li, Yiwen, et al.. (2024). A transaminase-mediated aldol reaction and applications in cascades to styryl pyridines. Catalysis Science & Technology. 14(9). 2390–2399.

Doutch, James, et al.. (2024). Using atomistic solution scattering modelling to elucidate the role of the Fc glycans in human IgG4. PLoS ONE. 19(4). e0300964–e0300964. 1 indexed citations

Dalby, Paul A., et al.. (2024). Encapsulation of Transketolase into In Vitro-Assembled Protein Nanocompartments Improves Thermal Stability. ACS Applied Bio Materials. 7(6). 3660–3674. 6 indexed citations

Wang, Yuhan, Hywel D. Williams, Duygu Dikicioǧlu, & Paul A. Dalby. (2024). Predictive Model Building for Aggregation Kinetics Based on Molecular Dynamics Simulations of an Antibody Fragment. Molecular Pharmaceutics. 21(11). 5827–5841. 2 indexed citations

Jiang, Ziyu & Paul A. Dalby. (2023). Challenges in scaling up AAV-based gene therapy manufacturing. Trends in biotechnology. 41(10). 1268–1281. 47 indexed citations

Zhang, Cheng, et al.. (2023). Crystal structures and molecular dynamics simulations of a humanised antibody fragment at acidic to basic pH. Scientific Reports. 13(1). 16281–16281. 2 indexed citations

Dai, Shaobo, et al.. (2016). Structural Analysis of an Evolved Transketolase Reveals Divergent Binding Modes. Scientific Reports. 6(1). 35716–35716. 16 indexed citations

10.

Rios‐Solis, Leonardo, et al.. (2016). Impact of cofactor-binding loop mutations on thermotolerance and activity of E. coli transketolase. Enzyme and Microbial Technology. 89. 85–91. 18 indexed citations

11.

Dalby, Paul A., et al.. (2012). Use of design of experiment and microscale down strategies in formulation and cycle development for lyophilization. UCL Discovery (University College London). 1 indexed citations

12.

Heenan, Richard K., et al.. (2012). The Solution Structure of Rabbit IgG Accounts for Its Interactions with the Fc Receptor and Complement C1q and Its Conformational Stability. Journal of Molecular Biology. 425(3). 506–523. 31 indexed citations

13.

Dalby, Paul A., et al.. (2011). Optimal synthesis of chromatographic trains for downstream protein processing. Biotechnology Progress. 27(6). 1653–1660. 17 indexed citations

14.

Hibbert, Edward G., et al.. (2011). Directed evolution to re-adapt a co-evolved network within an enzyme. Journal of Biotechnology. 157(1). 237–245. 27 indexed citations

15.

Dalby, Paul A., Frank Baganz, Gary J. Lye, & John M. Ward. (2009). Protein and pathway engineering in biocatalysis. UCL Discovery (University College London). 2 indexed citations

16.

Dalby, Paul A., et al.. (2009). Biocatalytic approaches to ketodiols and aminodiols. 27(4). 28–31. 6 indexed citations

17.

Miller, Oliver J., et al.. (2007). Optimisation and evaluation of a generic microplate-based HPLC screen for transketolase activity. Biotechnology Letters. 29(11). 1759–1770. 18 indexed citations

18.

Miller, Oliver J. & Paul A. Dalby. (2004). Exposing relationships using directed evolution. Trends in biotechnology. 22(5). 203–205. 2 indexed citations

19.

Dalby, Paul A., et al.. (2000). Evolution of binding affinity in a WW domain probed by phage display. Protein Science. 9(12). 2366–2376. 3 indexed citations

20.

Dalby, Paul A., Ronald H. Hoess, & William F. DeGrado. (2000). Evolution of binding affinity in a WW domain probed by phage display. Protein Science. 9(12). 2366–2376. 31 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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