Andrew J. Doig

12.9k total citations · 1 hit paper
108 papers, 8.6k citations indexed

About

Andrew J. Doig is a scholar working on Molecular Biology, Physiology and Materials Chemistry. According to data from OpenAlex, Andrew J. Doig has authored 108 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 25 papers in Physiology and 23 papers in Materials Chemistry. Recurrent topics in Andrew J. Doig's work include Protein Structure and Dynamics (46 papers), Alzheimer's disease research and treatments (24 papers) and Enzyme Structure and Function (23 papers). Andrew J. Doig is often cited by papers focused on Protein Structure and Dynamics (46 papers), Alzheimer's disease research and treatments (24 papers) and Enzyme Structure and Function (23 papers). Andrew J. Doig collaborates with scholars based in United Kingdom, United States and France. Andrew J. Doig's co-authors include Paul D. Dobson, Robert L. Baldwin, Sudeep Pushpakom, Katherine J. Escott, Christine J. McNamee, Philippe Sanséau, Alan Norris, Munir Pirmohamed, David Cavalla and Shirley Hopper and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Chemical Society Reviews.

In The Last Decade

Andrew J. Doig

105 papers receiving 8.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Drug repurposing: progress, challenges and recommendations

2018 2.9k citations Andrew J. Doig et al. profile →

Peers

Andrew J. Doig

MB

CTM

PHYSI

MC

SPECT

Elmar Krieger Netherlands

Chun Wu United States

John L. Klepeis United States

Jason Swails United States

Jing Huang China

Justin A. Lemkul United States

Nathan Baker United States

Noel Southall United States

Philippe Derreumaux France

Sunhwan Jo United States

Elmar Krieger Netherlands

Andrew J. Doig

7.1k ×1.3

MB

934 ×0.6

CTM

860 ×0.6

PHYSI

1.2k ×1.1

MC

410 ×0.7

SPECT

Citations per year, relative to Andrew J. Doig Andrew J. Doig (= 1×) peers Elmar Krieger

Countries citing papers authored by Andrew J. Doig

Since Specialization

Citations

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

Fields of papers citing papers by Andrew J. Doig

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew J. Doig. 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 Andrew J. Doig. The network helps show where Andrew J. Doig may publish in the future.

Co-authorship network of co-authors of Andrew J. Doig

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew J. Doig. A scholar is included among the top collaborators of Andrew J. Doig 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 Andrew J. Doig. Andrew J. Doig 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

1.

Kabir, M. Shahjahan, Helen M. Stuart, Filipa M. Lopes, et al.. (2023). Predicting congenital renal tract malformation genes using machine learning. Scientific Reports. 13(1). 13204–13204. 1 indexed citations

2.

Powell, Thomas, et al.. (2020). Raman Spectroscopy to Monitor Post-Translational Modifications and Degradation in Monoclonal Antibody Therapeutics. Analytical Chemistry. 92(15). 10381–10389. 43 indexed citations

3.

Bellina, Bruno, et al.. (2020). Quantification of protein glycation using vibrational spectroscopy. The Analyst. 145(10). 3686–3696. 18 indexed citations

4.

Outeiral, Carlos, et al.. (2020). Deconvolution of conformational exchange from Raman spectra of aqueous RNA nucleosides. Communications Chemistry. 3(1). 56–56. 7 indexed citations

5.

Kabir, M. Shahjahan, et al.. (2019). The Essentiality Status of Mouse Duplicate Gene Pairs Correlates with Developmental Co-Expression Patterns. Scientific Reports. 9(1). 3224–3224. 6 indexed citations

6.

Doig, Andrew J.. (2018). Positive Feedback Loops in Alzheimer’s Disease: The Alzheimer’s Feedback Hypothesis. Journal of Alzheimer s Disease. 66(1). 25–36. 38 indexed citations

7.

Berthoumieu, Olivia, Phuong H. Nguyen, Sabrina Ferré, et al.. (2015). Combined Experimental and Simulation Studies Suggest a Revised Mode of Action of the Anti‐Alzheimer Disease Drug NQ‐Trp. Chemistry - A European Journal. 21(36). 12657–12666. 20 indexed citations

8.

Muldoon, Mark, et al.. (2013). Maximising the Size of Non-Redundant Protein Datasets Using Graph Theory. PLoS ONE. 8(2). e55484–e55484. 11 indexed citations

9.

Tzotzos, Susan & Andrew J. Doig. (2009). Amyloidogenic sequences in native protein structures. Protein Science. 19(2). 327–348. 66 indexed citations

10.

Doig, Andrew J.. (2008). Stability and Design of α-Helical Peptides. Progress in molecular biology and translational science. 83. 1–52. 13 indexed citations

11.

Doig, Andrew J., et al.. (2008). Sequence and Structural Features of Enzymes and their Active Sites by EC Class. Journal of Molecular Biology. 386(5). 1423–1436. 13 indexed citations

12.

Dobson, Paul D. & Andrew J. Doig. (2004). Predicting Enzyme Class From Protein Structure Without Alignments. Journal of Molecular Biology. 345(1). 187–199. 122 indexed citations

13.

Wilson, Claire, et al.. (2004). Improved prediction for N‐termini of α‐helices using empirical information. Proteins Structure Function and Bioinformatics. 57(2). 322–330. 8 indexed citations

14.

Dobson, Paul D. & Andrew J. Doig. (2003). Distinguishing Enzyme Structures from Non-enzymes Without Alignments. Journal of Molecular Biology. 330(4). 771–783. 335 indexed citations

15.

Penel, Simon & Andrew J. Doig. (2001). Rotamer strain energy in protein helices - quantification of a major force opposing protein folding. Journal of Molecular Biology. 305(4). 961–968. 20 indexed citations

16.

Penel, Simon, et al.. (2000). Determination of α‐helix N1 energies after addition of N1, N2, and N3 preferences to helix/coil theory. Protein Science. 9(4). 750–754. 13 indexed citations

17.

Stapley, Benjamin J. & Andrew J. Doig. (1997). αヘリックス,β-シート及びα-ヘリックスN-キャップにおけるアミノ酸側鎖ロータマの自由エネルギー. Journal of Molecular Biology. 272(3). 456–464. 1 indexed citations

18.

Stapley, Benjamin J., Carol A. Rohl, & Andrew J. Doig. (1995). Addition of side chain interactions to modified Lifson‐Roig helix‐coil theory: Application to energetics of Phenylalanine‐Methionine interactions. Protein Science. 4(11). 2383–2391. 79 indexed citations

19.

Doig, Andrew J. & Robert L. Baldwin. (1995). N‐ and C‐capping preferences for all 20 amino acids in α‐helical peptides. Protein Science. 4(7). 1325–1336. 277 indexed citations

20.

Doig, Andrew J. & Dudley H. Williams. (1991). Is the hydrophobic effect stabilizing or destabilizing in proteins?. Journal of Molecular Biology. 217(2). 389–398. 136 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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