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Matthew E. Ritchie

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Molecular Biology 56 2170 1953 52 49 225 57349

Matthew E. Ritchie publications per year

The chart shows the history of publications by Matthew E. Ritchie between 1997 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Matthew E. Ritchie published across 29 years, from 1997 to 2025, averaging 9.9 papers a year. Output peaked at 37 publications in 2021. 39 of the 286 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 1997 to 2025. Vertical axis: number of publications, 0 to 37. Peak 37 publications in 2021. 1997: 1 publication 1998: 0 publications 1999: 3 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 2 publications 2005: 1 publication 2006: 2 publications 2007: 3 publications 2008: 7 publications 2009: 9 publications 2010: 6 publications 2011: 4 publications 2012: 3 publications 2013: 6 publications 2014: 10 publications 2015: 10 publications 2016: 30 publications 2017: 13 publications 2018: 14 publications 2019: 12 publications 2020: 27 publications 2021: 37 publications 2022: 17 publications 2023: 30 publications 2024: 20 publications 2025: 19 publications
1997 2025

286 publications in total across all disciplines

View publications per year as a table
Matthew E. Ritchie: publications per year, 1997 to 2025
Year Publications
1997 1
1998 0
1999 3
2000 0
2001 0
2002 0
2003 0
2004 2
2005 1
2006 2
2007 3
2008 7
2009 9
2010 6
2011 4
2012 3
2013 6
2014 10
2015 10
2016 30
2017 13
2018 14
2019 12
2020 27
2021 37
2022 17
2023 30
2024 20
2025 19
Total 286
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Matthew E. Ritchie publication distribution in Molecular Biology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Molecular Biology in 2026. The highlighted bar marks where Matthew E. Ritchie sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 53 bars. Horizontal axis: publications, 47–56 to 564+. Vertical axis: number of scientists, 0 to 177. Most scientists, 177, have 117–126 publications. The last bar groups every scientist with 564 publications or more. The highlighted bar, 217–226 publications, is where this scientist sits. 47–56 publications: 7 scientists 57–66 publications: 17 scientists 67–76 publications: 65 scientists 77–86 publications: 90 scientists 87–96 publications: 125 scientists 97–106 publications: 131 scientists 107–116 publications: 162 scientists 117–126 publications: 177 scientists 127–136 publications: 158 scientists 137–146 publications: 158 scientists 147–156 publications: 146 scientists 157–166 publications: 159 scientists 167–176 publications: 131 scientists 177–186 publications: 110 scientists 187–196 publications: 112 scientists 197–206 publications: 100 scientists 207–216 publications: 89 scientists 217–226 publications: 98 scientists 227–236 publications: 74 scientists 237–246 publications: 72 scientists 247–256 publications: 63 scientists 257–266 publications: 53 scientists 267–276 publications: 54 scientists 277–286 publications: 49 scientists 287–296 publications: 52 scientists 297–306 publications: 43 scientists 307–316 publications: 46 scientists 317–326 publications: 41 scientists 327–336 publications: 42 scientists 337–346 publications: 31 scientists 347–356 publications: 28 scientists 357–366 publications: 29 scientists 367–376 publications: 26 scientists 377–386 publications: 24 scientists 387–396 publications: 24 scientists 397–406 publications: 14 scientists 407–416 publications: 13 scientists 417–426 publications: 20 scientists 427–436 publications: 12 scientists 437–446 publications: 20 scientists 447–456 publications: 11 scientists 457–466 publications: 10 scientists 467–476 publications: 14 scientists 477–486 publications: 14 scientists 487–496 publications: 10 scientists 497–506 publications: 13 scientists 507–516 publications: 13 scientists 517–526 publications: 2 scientists 527–536 publications: 4 scientists 537–546 publications: 6 scientists 547–556 publications: 8 scientists 557–563 publications: 6 scientists 564+ publications: 100 scientists
47–56 publications 564+

This scientist: 225 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 564 publications or more.

View publications distribution as a table
Number of Molecular Biology scientists by publication count, Research.com 2026 ranking edition. Based on 3,076 ranked scientists.
Publications Scientists This scientist
47–56 7
57–66 17
67–76 65
77–86 90
87–96 125
97–106 131
107–116 162
117–126 177
127–136 158
137–146 158
147–156 146
157–166 159
167–176 131
177–186 110
187–196 112
197–206 100
207–216 89
217–226 98 225
227–236 74
237–246 72
247–256 63
257–266 53
267–276 54
277–286 49
287–296 52
297–306 43
307–316 46
317–326 41
327–336 42
337–346 31
347–356 28
357–366 29
367–376 26
377–386 24
387–396 24
397–406 14
407–416 13
417–426 20
427–436 12
437–446 20
447–456 11
457–466 10
467–476 14
477–486 14
487–496 10
497–506 13
507–516 13
517–526 2
527–536 4
537–546 6
547–556 8
557–563 6
564+ 100
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Matthew E. Ritchie D-index placement in Molecular Biology in 2026

The chart shows the D-index (discipline H-index) distribution of Molecular Biology scientists ranked by Research.com in 2026. The highlighted bar marks where Matthew E. Ritchie sits on this spectrum.

No. of scientists
25 50 75 100 125
Bar chart with 54 bars. Horizontal axis: D-Index, 40–41 to 145+. Vertical axis: number of scientists, 0 to 131. Most scientists, 131, have 64–65 D-Index. The last bar groups every scientist with 145 D-Index or more. The highlighted bar, 56–57 D-Index, is where this scientist sits. 40–41 D-Index: 36 scientists 42–43 D-Index: 101 scientists 44–45 D-Index: 115 scientists 46–47 D-Index: 121 scientists 48–49 D-Index: 118 scientists 50–51 D-Index: 130 scientists 52–53 D-Index: 106 scientists 54–55 D-Index: 116 scientists 56–57 D-Index: 113 scientists 58–59 D-Index: 129 scientists 60–61 D-Index: 120 scientists 62–63 D-Index: 105 scientists 64–65 D-Index: 131 scientists 66–67 D-Index: 95 scientists 68–69 D-Index: 97 scientists 70–71 D-Index: 106 scientists 72–73 D-Index: 83 scientists 74–75 D-Index: 89 scientists 76–77 D-Index: 77 scientists 78–79 D-Index: 70 scientists 80–81 D-Index: 73 scientists 82–83 D-Index: 60 scientists 84–85 D-Index: 48 scientists 86–87 D-Index: 45 scientists 88–89 D-Index: 50 scientists 90–91 D-Index: 31 scientists 92–93 D-Index: 51 scientists 94–95 D-Index: 43 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 39 scientists 100–101 D-Index: 41 scientists 102–103 D-Index: 29 scientists 104–105 D-Index: 33 scientists 106–107 D-Index: 35 scientists 108–109 D-Index: 20 scientists 110–111 D-Index: 38 scientists 112–113 D-Index: 19 scientists 114–115 D-Index: 28 scientists 116–117 D-Index: 13 scientists 118–119 D-Index: 23 scientists 120–121 D-Index: 16 scientists 122–123 D-Index: 15 scientists 124–125 D-Index: 11 scientists 126–127 D-Index: 21 scientists 128–129 D-Index: 7 scientists 130–131 D-Index: 13 scientists 132–133 D-Index: 14 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 9 scientists 138–139 D-Index: 8 scientists 140–141 D-Index: 16 scientists 142–143 D-Index: 7 scientists 144 D-Index: 7 scientists 145+ D-Index: 100 scientists
40–41 D-Index 145+

This scientist: 56 D-Index — 29th percentile

29% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 145 D-Index or more.

View D-Index distribution as a table
Number of Molecular Biology scientists by D-index, Research.com 2026 ranking edition. Based on 3,076 ranked scientists.
D-Index Scientists This scientist
40–41 36
42–43 101
44–45 115
46–47 121
48–49 118
50–51 130
52–53 106
54–55 116
56–57 113 56
58–59 129
60–61 120
62–63 105
64–65 131
66–67 95
68–69 97
70–71 106
72–73 83
74–75 89
76–77 77
78–79 70
80–81 73
82–83 60
84–85 48
86–87 45
88–89 50
90–91 31
92–93 51
94–95 43
96–97 38
98–99 39
100–101 41
102–103 29
104–105 33
106–107 35
108–109 20
110–111 38
112–113 19
114–115 28
116–117 13
118–119 23
120–121 16
122–123 15
124–125 11
126–127 21
128–129 7
130–131 13
132–133 14
134–135 17
136–137 9
138–139 8
140–141 16
142–143 7
144 7
145+ 100
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Overview

Matthew E. Ritchie is affiliated with the Walter and Eliza Hall Institute of Medical Research in Australia. Their work is situated primarily within the field of Biochemistry, Genetics, and Molecular Biology, with a focus on subfields including Molecular Biology, Immunology, Cancer Research, Genetics, and Oncology.

Their research covers several main topics such as Single-cell and spatial transcriptomics, Gene expression and cancer classification, Genomics and Phylogenetic Studies, RNA modifications and cancer, Molecular Biology Techniques and Applications, Cancer Genomics and Diagnostics, and Cancer-related molecular mechanisms research.

They have published extensively in various scientific venues, with frequent contributions to bioRxiv (Cold Spring Harbor Laboratory), Genome biology, NAR Genomics and Bioinformatics, Nature Methods, and Blood.

Among recent papers co-authored by or involving Matthew E. Ritchie are:

  • "Opportunities and challenges in long-read sequencing data analysis" (2020, Genome biology)
  • "Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing" (2021, Genome biology)
  • "Systematic assessment of long-read RNA-seq methods for transcript identification and quantification" (2024, Nature Methods)
  • "Systematic comparison of sequencing-based spatial transcriptomic methods" (2024, Nature Methods)
  • "Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures" (2023, Nature Methods)

Frequent collaborators in research include Quentin Gouil, Shian Su, Luyi Tian, Charity W. Law, and Peter F. Hickey, reflecting ongoing partnerships in related fields and topics.

Best Publications

  • limma powers differential expression analyses for RNA-sequencing and microarray studies

    Matthew E. Ritchie;Belinda Phipson;Di Wu;Yifang Hu

  • A comparison of background correction methods for two-colour microarrays

    Matthew E. Ritchie;Jeremy Silver;Alicia Oshlack;Melissa Holmes

  • Apoptotic Caspases Suppress mtDNA-Induced STING-Mediated Type I IFN Production

    Michael J. White;Michael J. White;Kate McArthur;Kate McArthur;Donald Metcalf;Donald Metcalf;Rachael M. Lane

  • beadarray: R classes and methods for Illumina bead-based data.

    Mark J. Dunning;Mike L. Smith;Matthew E. Ritchie;Simon Tavaré

  • Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses

    Ruijie Liu;Aliaksei Z. Holik;Shian Su;Natasha Jansz

  • Targeting BCL-2 with the BH3 Mimetic ABT-199 in Estrogen Receptor-Positive Breast Cancer

    François Vaillant;Delphine Merino;Delphine Merino;Lily Lee;Lily Lee;Kelsey Breslin

  • A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data

    Nuno L. Barbosa-Morais;Mark J. Dunning;Shamith A. Samarajiwa;Jeremy F. J. Darot

  • The neuropeptide VIP confers anticipatory mucosal immunity by regulating ILC3 activity.

    Cyril Seillet;Cyril Seillet;Kylie Luong;Kylie Luong;Julie Tellier;Julie Tellier;Nicolas Jacquelot;Nicolas Jacquelot

  • Combining multiple tools outperforms individual methods in gene set enrichment analyses.

    Unknown

  • Glimma: interactive graphics for gene expression analysis

    Shian Su;Charity W. Law;Charity W. Law;Casey Ah-Cann;Casey Ah-Cann;Marie Liesse Asselin-Labat;Marie Liesse Asselin-Labat

  • Opposing roles of polycomb repressive complexes in hematopoietic stem and progenitor cells

    Ian J Majewski;Matthew E Ritchie;Belinda Phipson;Jason Corbin

  • Global changes in the mammary epigenome are induced by hormonal cues and coordinated by Ezh2.

    Bhupinder Pal;Toula Bouras;Toula Bouras;Wei Shi;Wei Shi;François Vaillant;François Vaillant

  • Integrative analysis of RUNX1 downstream pathways and target genes

    Joëlle Michaud;Joëlle Michaud;Joëlle Michaud;Ken M Simpson;Robert Escher;Robert Escher;Karine Buchet-Poyau

  • Deciphering the Innate Lymphoid Cell Transcriptional Program

    Cyril Seillet;Cyril Seillet;Lisa A. Mielke;Lisa A. Mielke;Daniela B. Amann-Zalcenstein;Daniela B. Amann-Zalcenstein;Shian Su;Shian Su

  • Using the R Package crlmm for Genotyping and Copy Number Estimation.

    Robert B. Scharpf;Rafael A. Irizarry;Matthew E. Ritchie;Benilton Carvalho

  • Statistical issues in the analysis of Illumina data

    Mark J Dunning;Nuno L Barbosa-Morais;Andy G Lynch;Simon Tavaré

  • High-resolution transcription atlas of the mitotic cell cycle in budding yeast

    Marina V Granovskaia;Lars J Jensen;Lars J Jensen;Matthew E Ritchie;Matthew E Ritchie;Joern Toedling

  • Identification of quiescent and spatially restricted mammary stem cells that are hormone responsive

    Nai Yang Fu;Anne C. Rios;Anne C. Rios;Bhupinder Pal;Bhupinder Pal;Charity W. Law;Charity W. Law

  • Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing.

    Luyi Tian;Luyi Tian;Jafar S. Jabbari;Rachel Thijssen;Rachel Thijssen;Quentin Gouil;Quentin Gouil

  • RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR [version 2; referees: 3 approved]

    Charity W. Law;Monther Alhamdoosh;Shian Su;Gordon K. Smyth

Frequent Co-Authors

Marnie E. Blewitt
Marnie E. Blewitt Walter and Eliza Hall Institute of Medical Research
Gordon K. Smyth
Gordon K. Smyth Walter and Eliza Hall Institute of Medical Research
Douglas J. Hilton
Douglas J. Hilton Walter and Eliza Hall Institute of Medical Research
Benjamin T. Kile
Benjamin T. Kile University of Adelaide
Geoffrey J. Lindeman
Geoffrey J. Lindeman Peter MacCallum Cancer Centre
Jane E. Visvader
Jane E. Visvader Walter and Eliza Hall Institute of Medical Research
François Vaillant
François Vaillant Walter and Eliza Hall Institute of Medical Research
Gabrielle T. Belz
Gabrielle T. Belz University of Queensland
Stephen L. Nutt
Stephen L. Nutt Walter and Eliza Hall Institute of Medical Research
Simon Tavaré
Simon Tavaré Columbia University

External Links

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Related Online Degrees & Career Pathways

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Best Scientists Citing Matthew E. Ritchie

Gordon K. Smyth

Gordon K. Smyth

Walter and Eliza Hall Institute of Medical Research

Publications: 154

Jane E. Visvader

Jane E. Visvader

Walter and Eliza Hall Institute of Medical Research

Publications: 72

Geoffrey J. Lindeman

Geoffrey J. Lindeman

Peter MacCallum Cancer Centre

Publications: 68

John C. Marioni

John C. Marioni

European Bioinformatics Institute

Publications: 66

Julio Saez-Rodriguez

Julio Saez-Rodriguez

Heidelberg University

Publications: 63

Wei Shi

Wei Shi

Monash University

Publications: 59

Alicia Oshlack

Alicia Oshlack

Peter MacCallum Cancer Centre

Publications: 49

Gabrielle T. Belz

Gabrielle T. Belz

University of Queensland

Publications: 49

Melanie Boerries

Melanie Boerries

University of Freiburg

Publications: 45

Stephen L. Nutt

Stephen L. Nutt

Walter and Eliza Hall Institute of Medical Research

Publications: 45

Marnie E. Blewitt

Marnie E. Blewitt

Walter and Eliza Hall Institute of Medical Research

Publications: 45

Andrew E. Jaffe

Andrew E. Jaffe

Johns Hopkins University

Publications: 44

Christoph Bock

Christoph Bock

Austrian Academy of Sciences

Publications: 44

Mark D. Robinson

Mark D. Robinson

University of Zurich

Publications: 40

Sarah A. Teichmann

Sarah A. Teichmann

University of Cambridge

Publications: 40

Eric E. Schadt

Eric E. Schadt

Icahn School of Medicine at Mount Sinai

Publications: 37

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