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Neil Swainston

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 39 7546 7280 468 445 97 8852

Neil Swainston publications per year

The chart shows the history of publications by Neil Swainston between 1998 and 2023, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Neil Swainston published across 26 years, from 1998 to 2023, averaging 4.5 papers a year. Output peaked at 18 publications in 2020. 5 of the 117 publications appeared in the last two years.

No. of publications
5 10 15
Bar chart. Horizontal axis: year, 1998 to 2023. Vertical axis: number of publications, 0 to 18. Peak 18 publications in 2020. 1998: 1 publication 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 4 publications 2005: 0 publications 2006: 1 publication 2007: 4 publications 2008: 2 publications 2009: 4 publications 2010: 10 publications 2011: 8 publications 2012: 3 publications 2013: 4 publications 2014: 6 publications 2015: 9 publications 2016: 7 publications 2017: 11 publications 2018: 9 publications 2019: 4 publications 2020: 18 publications 2021: 7 publications 2022: 4 publications 2023: 1 publication
1998 2023

117 publications in total across all disciplines

View publications per year as a table
Neil Swainston: publications per year, 1998 to 2023
Year Publications
1998 1
1999 0
2000 0
2001 0
2002 0
2003 0
2004 4
2005 0
2006 1
2007 4
2008 2
2009 4
2010 10
2011 8
2012 3
2013 4
2014 6
2015 9
2016 7
2017 11
2018 9
2019 4
2020 18
2021 7
2022 4
2023 1
Total 117
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Neil Swainston publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Neil Swainston sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 88–97 publications, is where this scientist sits. 38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38–47 publications 804+

This scientist: 97 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259 97
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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Neil Swainston D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Neil Swainston sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 39 D-Index, is where this scientist sits. 30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 39 D-Index — 24th percentile

24% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385 39
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Overview

Neil Swainston is affiliated with Epoch BioDesign in the United Kingdom. Their research primarily falls within the broad field of Biochemistry, Genetics and Molecular Biology, with a significant focus on Molecular Biology. Other subfields of study include Computational Theory and Mathematics, Spectroscopy, Materials Chemistry, and Biomedical Engineering.

The scientist's work spans several main topics, with notable concentrations in Microbial Metabolic Engineering and Bioproduction, Gene Regulatory Network Analysis, and Computational Drug Discovery Methods. Additional research interests cover Metabolomics and Mass Spectrometry Studies, Bioinformatics and Genomic Networks, as well as Machine Learning applications within Materials Science and Mass Spectrometry Techniques and Applications.

Neil Swainston has contributed to the publication of numerous papers in various reputable scientific journals. Recent notable publications include:

  • SBML Level 3: an extensible format for the exchange and reuse of biological models (2020) in Molecular Systems Biology
  • The RESOLUTE consortium: unlocking SLC transporters for drug discovery (2020) in Nature Reviews Drug Discovery
  • Engineering Escherichia coli towards de novo production of gatekeeper (2S)-flavanones: naringenin, pinocembrin, eriodictyol and homoeriodictyol (2020) in Synthetic Biology
  • DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach (2020) in Journal of Cheminformatics
  • Rapid prototyping of microbial production strains for the biomanufacture of potential materials monomers (2020) in Metabolic Engineering

Many of Swainston's papers have appeared frequently in a select group of publication venues. These include bioRxiv (Cold Spring Harbor Laboratory), Synthetic Biology, Molecular Systems Biology, Nature Reviews Drug Discovery, and the Journal of Cheminformatics.

The scientist has collaborated extensively with several frequent co-authors, including Douglas B. Kell, Soumitra Samanta, Pablo Carbonell, Valentin Zulkower, and Marina Wright Muelas, reflecting active engagement in collaborative research networks.

Best Publications

  • A community-driven global reconstruction of human metabolism

    Ines Thiele;Neil Swainston;Ronan M T Fleming;Andreas Hoppe

  • ChEBI in 2016: Improved services and an expanding collection of metabolites.

    Janna Hastings;Gareth Owen;Adriano Dekker;Marcus Ennis

  • A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

    Markus Herrgard;Neil Swainston;Paul Dobson;Warwick B. Dunn

  • Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

    Andrew Currin;Neil Swainston;Philip J. Day;Douglas B. Kell

  • Recon 2.2: from reconstruction to model of human metabolism

    Neil Swainston;Kieran Smallbone;Hooman Hefzi;Paul D. Dobson

  • Growth control of the eukaryote cell: a systems biology study in yeast

    Juan I Castrillo;Leo A Zeef;David C Hoyle;Nianshu Zhang

  • Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics

    Marie Brown;Warwick B. Dunn;P. Dobson;Y. Patel

  • SBML Level 3: an extensible format for the exchange and reuse of biological models

    Sarah M. Keating;Sarah M. Keating;Dagmar Waltemath;Matthias König;Fengkai Zhang

  • An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals

    Pablo Carbonell;Adrian J. Jervis;Christopher J. Robinson;Cunyu Yan

  • Membrane transporter engineering in industrial biotechnology and whole cell biocatalysis

    Douglas B. Kell;Neil Swainston;Pınar Pir;Stephen G. Oliver

  • Towards a genome-scale kinetic model of cellular metabolism

    Kieran Smallbone;Evangelos Simeonidis;Neil Swainston;Pedro Mendes;Pedro Mendes

  • Improving metabolic flux predictions using absolute gene expression data

    Dave Lee;Kieran Smallbone;Warwick B Dunn;Ettore Murabito

  • Large-scale generation of computational models from biochemical pathway maps

    Finja Büchel;Nicolas Rodriguez;Neil Swainston;Clemens Wrzodek

  • A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

    Ines Thiele;Daniel R Hyduke;Benjamin Steeb;Guy Fankam

  • Path2Models: large-scale generation of computational models from biochemical pathway maps

    Finja Buchel;Finja Buchel;Nicolas Rodriguez;Nicolas Rodriguez;Neil Swainston;Clemens Wrzodek

  • Identifiers for the 21st century : How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data

    Julie A. McMurry;Nick Juty;Niklas Blomberg;Tony Burdett

  • Further developments towards a genome-scale metabolic model of yeast

    Paul D. Dobson;Kieran Smallbone;Daniel Jameson;Evangelos Simeonidis

  • Integration of metabolic databases for the reconstruction of genome-scale metabolic networks

    Karin Radrich;Karin Radrich;Yoshimasa Tsuruoka;Yoshimasa Tsuruoka;Paul D. Dobson;Albert Gevorgyan;Albert Gevorgyan

  • Selenzyme: enzyme selection tool for pathway design

    Pablo Carbonell;Jerry Wong;Neil Swainston;Eriko Takano;Eriko Takano

  • A 'rule of 0.5' for the metabolite-likeness of approved pharmaceutical drugs.

    Steve O′Hagan;Neil Swainston;Julia Handl;Douglas B. Kell

  • Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli

    Adrian J. Jervis;Pablo Carbonell;Maria Vinaixa;Mark S. Dunstan

  • The SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks.

    Neil Swainston;Kieran Smallbone;Pedro Mendes;Douglas B. Kell

  • SBOL Visual: A Graphical Language for Genetic Designs

    Jacqueline Y. Quinn;Robert Sidney Cox;Aaron Adler;Jacob Beal

  • Bioinformatics for the synthetic biology of natural products: integrating across the Design–Build–Test cycle

    Pablo Carbonell;Andrew Currin;Adrian J. Jervis;Nicholas J. W. Rattray

  • SpeedyGenes: An improved gene synthesis method for the efficient production of error-corrected, synthetic protein libraries for directed evolution

    Andrew Currin;Neil Swainston;Philip J. Day;Douglas B. Kell

Frequent Co-Authors

Douglas B. Kell
Douglas B. Kell University of Liverpool
Pedro Mendes
Pedro Mendes University of Connecticut
Nigel S. Scrutton
Nigel S. Scrutton University of Manchester
Jean-Loup Faulon
Jean-Loup Faulon University of Paris-Saclay
Eriko Takano
Eriko Takano University of Manchester
Rainer Breitling
Rainer Breitling University of Manchester
Warwick B. Dunn
Warwick B. Dunn University of Liverpool
Nicolas Le Novère
Nicolas Le Novère Babraham Institute
Nicholas J. Turner
Nicholas J. Turner University of Manchester
Hans V. Westerhoff
Hans V. Westerhoff Vrije Universiteit Amsterdam

External Links

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Related Online Degrees & Career Pathways

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Integrating technical expertise with skills in business or leadership can create diverse and rewarding career pathways in the engineering and technology sectors.

Best Scientists Citing Neil Swainston

Douglas B. Kell

Douglas B. Kell

University of Liverpool

Publications: 112

Jens Nielsen

Jens Nielsen

Chalmers University of Technology

Publications: 105

Manfred T. Reetz

Manfred T. Reetz

Max Planck Society

Publications: 75

Bernhard O. Palsson

Bernhard O. Palsson

University of California, San Diego

Publications: 65

Hans V. Westerhoff

Hans V. Westerhoff

Vrije Universiteit Amsterdam

Publications: 57

Stephen G. Oliver

Stephen G. Oliver

University of Cambridge

Publications: 55

Ines Thiele

Ines Thiele

University of Galway

Publications: 54

Warwick B. Dunn

Warwick B. Dunn

University of Liverpool

Publications: 47

Ronan M. T. Fleming

Ronan M. T. Fleming

Leiden University

Publications: 42

Henning Hermjakob

Henning Hermjakob

European Bioinformatics Institute

Publications: 32

Royston Goodacre

Royston Goodacre

University of Liverpool

Publications: 29

Nicolas Le Novère

Nicolas Le Novère

Babraham Institute

Publications: 28

Matej Orešič

Matej Orešič

Örebro University

Publications: 26

Nathan E. Lewis

Nathan E. Lewis

University of California, San Diego

Publications: 26

Markus Ralser

Markus Ralser

Charité - University Medicine Berlin

Publications: 25

Pedro Mendes

Pedro Mendes

University of Connecticut

Publications: 24

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