| Type | n |
|---|---|
| Article | 21716 |
| Review | 3275 |
| Book chapter | 1083 |
| Conference paper | 662 |
| Letter | 356 |
| Note | 306 |
| Short survey | 303 |
| Editorial | 251 |
| Book | 91 |
| Erratum | 68 |
| Data paper | 11 |
| Retracted | 5 |
Mycology UK
A bibliometric analysis of the past 25 years of scientific research into Fungi, conducted on behalf of the British Mycological Society
Professor Dan Bebber
Department of Biosciences, University of Exeter, UK
2025-06-30
Introduction
Using this presentation
- This presentation was made using reveal.js
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Mycology
- Mycology, the scientific investigation of Kingdom Fungi, has a long and rich history in the UK.
- The term mycologist may first have been used by the English botanist Robert Kaye Greville, in a paper on published almost exactly 200 years ago.
Mycology is a diverse discipline
Mycological research spans a wide range of subdisciplines. These include:
taxonomy, systematics, phylogenetics and biodiversity
roles of fungi in ecosystems (e.g. decomposition and nutrient cycling), symbiotic interactions with other organisms (such as endosymbionts, mycorrhizas and lichens)
medical mycology (including immunology and mycotoxicology) and antifungal resistance
plant pathology and fungal biocontrol agents
biotechnology and fermentation (including production and use of metabolites)
bioremediation
genomics and proteomics
cellular processes, metabolic pathways and stress responses
synthetic biology and genetic engineering.
Aims of this study
This bibliometric analysis aims to provide an overview of patterns and trends in mycological research in the UK over the past quarter century (1999—2023), investigating the popularity of different research topics, centres of excellence, influential authors, collaboration networks, funding sources, and publication venues.
Bibliometric data
Mycological publications in the Scopus database
Bibliometric data (i.e., information on publications) were obtained from Elsevier’s SCOPUS database for the years 1999—2023 inclusive. The fields Article Title, Abstract and Keywords were searched for terms: “fungi” OR “fungal” OR “fungus” OR “mycology” OR “mycological”.
Results were restricted to those with at least one author with an institutional affiliation (or address) in the United Kingdom.
This search resulted in a document count of 27,445.
In addition, all papers from mycological journals, i.e. those with words like ‘fungal’ or ‘mycology’ (but not ‘mycobacterium’ etc.) in the journal title, were included. This yielded an additional 682 papers.
The total document count was 28,127.
Bibliometric data including authors and affiliations, citation number and funding details were downloaded for analysis.
Types of publications
- Most publications are articles, along with some reviews and book chapters.
Publications per year
- Publications per year have increased over time, but declined somewhat in 2022-3. A legacy of COVID19?
Mycological Topics
Grouping publications into topics
Latent Dirichlet Allocation (LDA) was used to group publications into topics.
Words in publication titles, abstracts and keywords were processed to remove common “stop words” and “stemmed” to find common roots (e.g. immune, immunity and immunological all become “immun”).
The number of Topics was set to eight, following some experimentation to minimize subject overlap while retaining major themes.
The top 20 terms (stemmed words) most likely to be found in each topic were used to find a single-word descriptor or title for each topic.
Major topics in mycology
- Here are the topics identified by LDA (in alphabetical order) along with a brief summary of topics covered.
- Fungal genera are associated with certain topics.
Biochemistry: enzymes, products and structures
Clinical: infection, human and antifungal
Diagnostics: isolate, test and Aspergillus
Ecology: soil, microbiome and community
Genomics: sequencing, species and evolution
Immunology: cell, animal and Candida
Phytopathology: plant, disease and Fusarium
Regulation: protein, gene and Saccharomyces
Important terms per topic
- Here are the the top 20 terms associated with each topic.
- These are terms rather than words, i.e. some are stems of several different words.
- NB: You may need to scroll down to see them all.
| Topic | Terms |
|---|---|
| Biochemistry | activ, acid, enzym, product, structur, drug, metabol, deriv, compound, chemic, inhibit, synthesi, metabolit, process, chemistri, oxid, substrat, mass, ferment, molecular |
| Clinical | infect, human, antifung, diseas, patient, treatment, drug, agent, clinic, age, virus, risk, case, invas, adult, aspergillosi, review, femal, therapi, male |
| Diagnostics | aspergillus, isol, test, cultur, method, strain, detect, sampl, analysi, growth, sensit, control, bacteri, time, concentr, reaction, chain, fumigatus, assay, extract |
| Ecology | soil, microbi, communiti, plant, organ, root, environment, carbon, speci, water, ecosystem, divers, bacteria, forest, mycorrhiz, chang, temperatur, environ, composit, nitrogen |
| Genomics | sequenc, speci, genet, genom, analysi, data, dna, molecular, gene, model, identifi, evolut, region, type, biolog, phylogeni, group, isol, distribut, famili |
| Immunology | cell, anim, respons, candida, albican, immun, human, model, stress, growth, signal, interact, receptor, system, pathogen, wall, virul, mechan, factor, activ |
| Phytopathology | plant, diseas, pathogen, resist, control, develop, host, spore, food, fusarium, wheat, crop, popul, fungicid, biolog, leaf, parasit, caus, infect, reduc |
| Regulation | protein, gene, cerevisia, express, saccharomyc, yeast, dna, regul, rna, transcript, function, bind, genet, cell, complex, mutat, sequenc, mutant, factor, chromosom |
Relationships among topics: PCA
- Principal Components Analysis (PCA) of terms allows us to visualize relationships among publications in ‘term space’.
- The next slides show the first three PCA axes, with loadings of some of the more important terms plotted.
- Each publication is a point, coloured by topic.
- Three main ‘lobes’ are identified: Ecology, Clinical and Regulation.
- Axis 1 appears to span pure research on the left, applied research on the right.
- Axis 2 spans spatial scales from proteins at the bottom to ecosystems at the top.
- Axis 3 potentially indicates data analytics on the left, clinical application on the right.
PCA Axes 1 & 2
