Max Hebditch

1.1k total citations · 1 hit paper
12 papers, 753 citations indexed

About

Max Hebditch is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Spectroscopy. According to data from OpenAlex, Max Hebditch has authored 12 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Spectroscopy. Recurrent topics in Max Hebditch's work include Protein purification and stability (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers) and Protein Structure and Dynamics (5 papers). Max Hebditch is often cited by papers focused on Protein purification and stability (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers) and Protein Structure and Dynamics (5 papers). Max Hebditch collaborates with scholars based in United Kingdom, Denmark and Singapore. Max Hebditch's co-authors include Jim Warwicker, Robin Curtis, Spyros Charonis, Günther H. Peters, Pernille Harris, Clair Baldock, Michael P. Williamson, Andrea M. Hounslow, Daniel Corbett and Jai A. Pathak and has published in prestigious journals such as Bioinformatics, The Journal of Physical Chemistry B and Chemical Communications.

In The Last Decade

Max Hebditch

12 papers receiving 737 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.

Protein–Sol: a web tool for predicting protein solubility from sequence

2017 527 citations Max Hebditch, Spyros Charonis et al. Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Max Hebditch United Kingdom	9	641	237	117	102	89	12	753
Spyros Charonis United States	8	527 0.8×	171 0.7×	135 1.2×	116 1.1×	78 0.9×	15	671
Patricia M. Legler United States	17	670 1.0×	136 0.6×	214 1.8×	114 1.1×	111 1.2×	47	1.1k
Alexis Lamiable France	8	660 1.0×	100 0.4×	126 1.1×	92 0.9×	34 0.4×	10	855
Shilpa R. Shenoy United States	14	743 1.2×	147 0.6×	132 1.1×	199 2.0×	130 1.5×	21	1.2k
Salman Sadullah Usmani India	18	1.4k 2.2×	202 0.9×	209 1.8×	145 1.4×	70 0.8×	24	1.7k
Cheng‐Yuan Huang United States	12	844 1.3×	291 1.2×	172 1.5×	38 0.4×	50 0.6×	18	1.1k
Shengshu Huang United States	17	1.1k 1.7×	238 1.0×	211 1.8×	58 0.6×	119 1.3×	20	1.3k
Willem A. de Jongh Denmark	12	425 0.7×	102 0.4×	182 1.6×	47 0.5×	80 0.9×	20	761
Chatchai Tayapiwatana Thailand	16	418 0.7×	143 0.6×	105 0.9×	122 1.2×	29 0.3×	87	705

Countries citing papers authored by Max Hebditch

Since Specialization

Citations

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

Fields of papers citing papers by Max Hebditch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Hebditch

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

All Works

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12 of 12 papers shown

1.

Hebditch, Max, et al.. (2021). PhosIDP: a web tool to visualize the location of phosphorylation sites in disordered regions. Scientific Reports. 11(1). 9930–9930. 5 indexed citations

2.

Hebditch, Max & Jim Warwicker. (2020). Protein-sol pKa: prediction of electrostatic frustration, with application to coronaviruses. Bioinformatics. 36(20). 5112–5114. 10 indexed citations

3.

Hebditch, Max, et al.. (2020). Modelling of pH-dependence to develop a strategy for stabilising mAbs at acidic steps in production. Computational and Structural Biotechnology Journal. 18. 897–905. 8 indexed citations

4.

Hebditch, Max & Jim Warwicker. (2019). Web-based display of protein surface and pH-dependent properties for assessing the developability of biotherapeutics. Scientific Reports. 9(1). 1969–1969. 69 indexed citations

5.

Hebditch, Max & Jim Warwicker. (2019). Charge and hydrophobicity are key features in sequence-trained machine learning models for predicting the biophysical properties of clinical-stage antibodies. PeerJ. 7. e8199–e8199. 30 indexed citations

6.

Hebditch, Max, et al.. (2018). Models for Antibody Behavior in Hydrophobic Interaction Chromatography and in Self-Association. Journal of Pharmaceutical Sciences. 108(4). 1434–1441. 14 indexed citations

7.

Hebditch, Max, et al.. (2018). Self-Interaction of Human Serum Albumin: A Formulation Perspective. ACS Omega. 3(11). 16105–16117. 27 indexed citations

8.

Hebditch, Max, Robin Curtis, & Jim Warwicker. (2017). Sequence composition predicts immunoglobulin superfamily members that could share the intrinsically disordered properties of antibody CH1 domains. Scientific Reports. 7(1). 12404–12404. 3 indexed citations

9.

Hebditch, Max, et al.. (2017). Protein–Sol: a web tool for predicting protein solubility from sequence. Bioinformatics. 33(19). 3098–3100. 527 indexed citations breakdown →

10.

Corbett, Daniel, Max Hebditch, Prasad Sarangapani, et al.. (2017). Coarse-Grained Modeling of Antibodies from Small-Angle Scattering Profiles. The Journal of Physical Chemistry B. 121(35). 8276–8290. 31 indexed citations

11.

Marsden, Catherine J., et al.. (2014). The Use of Antibodies in Small-Molecule Drug Discovery. SLAS DISCOVERY. 19(6). 829–838. 12 indexed citations

12.

Williamson, Michael P., et al.. (2013). Detection of salt bridges to lysines in solution in barnase. Chemical Communications. 49(84). 9824–9826. 17 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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