World's Best Scientists 2026 revealed!

D-Index & Metrics

Molecular Biology

D-Index
56
Citations
57349
World Ranking
2170
National Ranking
52

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.

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 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.

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.

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 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.

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

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
Tracy A. Willson
Tracy A. Willson Walter and Eliza Hall Institute of Medical Research
Simon Tavaré
Simon Tavaré Columbia University

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