Shahid Uddin

856 total citations
28 papers, 695 citations indexed

About

Shahid Uddin is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Shahid Uddin has authored 28 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 14 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Biomedical Engineering. Recurrent topics in Shahid Uddin's work include Protein purification and stability (19 papers), Monoclonal and Polyclonal Antibodies Research (14 papers) and Viral Infectious Diseases and Gene Expression in Insects (6 papers). Shahid Uddin is often cited by papers focused on Protein purification and stability (19 papers), Monoclonal and Polyclonal Antibodies Research (14 papers) and Viral Infectious Diseases and Gene Expression in Insects (6 papers). Shahid Uddin collaborates with scholars based in United Kingdom, United States and Qatar. Shahid Uddin's co-authors include Christopher F. van der Walle, Malgorzata B. Tracka, Robin Curtis, Alexander P. Golovanov, Jim Warwicker, David W. Roberts, Rebecca J. Dearman, Maximilian W. A. Skoda, Alain Pluen and José R. Casas‐Finet and has published in prestigious journals such as PLoS ONE, The Journal of Physical Chemistry B and ACS Applied Materials & Interfaces.

In The Last Decade

Shahid Uddin

27 papers receiving 688 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shahid Uddin United Kingdom 15 553 286 193 75 47 28 695
Michaela Blech Germany 18 879 1.6× 423 1.5× 192 1.0× 64 0.9× 101 2.1× 41 1.1k
Erwin Freund United States 10 696 1.3× 319 1.1× 236 1.2× 52 0.7× 105 2.2× 12 840
Erinç Şahin United States 12 682 1.2× 373 1.3× 99 0.5× 128 1.7× 33 0.7× 19 795
Sonoko Kanai United States 10 512 0.9× 300 1.0× 125 0.6× 43 0.6× 26 0.6× 10 635
Atul Saluja United States 17 936 1.7× 545 1.9× 284 1.5× 142 1.9× 40 0.9× 22 1.1k
Thomas M. Spitznagel United States 8 487 0.9× 220 0.8× 160 0.8× 33 0.4× 66 1.4× 9 566
Muppalla Sukumar United States 13 467 0.8× 171 0.6× 113 0.6× 73 1.0× 43 0.9× 14 609
Michael Wiggenhorn Germany 14 764 1.4× 249 0.9× 442 2.3× 59 0.8× 98 2.1× 16 1.1k
Tim J. Kamerzell United States 15 706 1.3× 348 1.2× 108 0.6× 117 1.6× 43 0.9× 18 878

Countries citing papers authored by Shahid Uddin

Since Specialization
Citations

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

Fields of papers citing papers by Shahid Uddin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shahid Uddin

This figure shows the co-authorship network connecting the top 25 collaborators of Shahid Uddin. A scholar is included among the top collaborators of Shahid Uddin 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 Shahid Uddin. Shahid Uddin 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.
2.
Uddin, Shahid, et al.. (2025). A BRET-based Mpro biosensor containing a nanobody and tandem cleavage sites shows an increased cleavage rate. Sensors and Actuators Reports. 9. 100315–100315. 1 indexed citations
3.
Uddin, Shahid, et al.. (2024). Engineering β-catenin-derived peptides for α-catenin binding. Emergent Materials. 8(2). 1183–1197. 1 indexed citations
4.
Ahmed, Wesam S., et al.. (2024). A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity. International Journal of Biological Macromolecules. 269(Pt 1). 131864–131864. 6 indexed citations
5.
Dearman, Rebecca J., et al.. (2019). Impact of a Heat Shock Protein Impurity on the Immunogenicity of Biotherapeutic Monoclonal Antibodies. Pharmaceutical Research. 36(4). 35–38. 15 indexed citations
6.
Li, Zongyi, Ruiheng Li, Charles Smith, et al.. (2017). Neutron Reflection Study of Surface Adsorption of Fc, Fab, and the Whole mAb. ACS Applied Materials & Interfaces. 9(27). 23202–23211. 24 indexed citations
7.
Rattray, Zahra, et al.. (2017). Evaluation of aggregate and silicone-oil counts in pre-filled siliconized syringes: An orthogonal study characterising the entire subvisible size range. International Journal of Pharmaceutics. 519(1-2). 58–66. 13 indexed citations
8.
Dajani, Rana, Alexander P. Golovanov, Alain Pluen, et al.. (2017). The effect of charge mutations on the stability and aggregation of a human single chain Fv fragment. European Journal of Pharmaceutics and Biopharmaceutics. 115. 18–30. 41 indexed citations
9.
Batalha, Íris L., et al.. (2017). Dipicolinic acid as a novel spore-inspired excipient for antibody formulation. International Journal of Pharmaceutics. 526(1-2). 332–338. 4 indexed citations
10.
Dearman, Rebecca J., et al.. (2017). Investigating Liquid–Liquid Phase Separation of a Monoclonal Antibody Using Solution-State NMR Spectroscopy: Effect of Arg·Glu and Arg·HCl. Molecular Pharmaceutics. 14(8). 2852–2860. 22 indexed citations
11.
Golovanov, Alexander P., et al.. (2016). The effects of arginine glutamate, a promising excipient for protein formulation, on cell viability: Comparisons with NaCl. Toxicology in Vitro. 33. 88–98. 15 indexed citations
12.
Alexander, Cameron, et al.. (2016). The effect of protein concentration on the viscosity of a recombinant albumin solution formulation. RSC Advances. 6(18). 15143–15154. 40 indexed citations
13.
14.
Tracka, Malgorzata B., et al.. (2015). Characterisation of Stress-Induced Aggregate Size Distributions and Morphological Changes of a Bi-Specific Antibody Using Orthogonal Techniques. Journal of Pharmaceutical Sciences. 104(8). 2473–2481. 16 indexed citations
15.
Tracka, Malgorzata B., et al.. (2014). The effect of arginine glutamate on the stability of monoclonal antibodies in solution. International Journal of Pharmaceutics. 473(1-2). 126–133. 69 indexed citations
16.
Longo, Edoardo, Emiliana De Santis, Rohanah Hussain, et al.. (2014). The effect of palmitoylation on the conformation and physical stability of a model peptide hormone. International Journal of Pharmaceutics. 472(1-2). 156–164. 14 indexed citations
17.
Li, Tong, Malgorzata B. Tracka, Shahid Uddin, et al.. (2014). Redistribution of Flexibility in Stabilizing Antibody Fragment Mutants Follows Le Châtelier’s Principle. PLoS ONE. 9(3). e92870–e92870. 34 indexed citations
18.
Skoda, Maximilian W. A., et al.. (2013). Adsorption behavior of a human monoclonal antibody at hydrophilic and hydrophobic surfaces. mAbs. 5(1). 126–139. 54 indexed citations
19.
Uddin, Shahid, et al.. (2012). An apparatus to measure electrical charge of bubble swarms. Journal of Colloid and Interface Science. 389(1). 298–305. 9 indexed citations
20.
Smith, Graeme, Shahid Uddin, Sandrine Mulot, et al.. (2009). Factors influencing antibody stability at solid–liquid interfaces in a high shear environment. Biotechnology Progress. 25(5). 1499–1507. 46 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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