Machine Learning in Bioinformatics
Machine Learning in Bioinformatics is a research topic within Molecular Biology. Science Explorer counts 26k research works in it since 1950. 16.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the prediction of protein subcellular localization using various computational methods such as amino acid composition, machine learning algorithms like support vector machines, and the analysis of signal peptides and transmembrane topology. The research aims to improve the accuracy and reliability of predicting the subcellular location of proteins, which has significant implications for understanding protein function and cellular processes.
- Subcellular Localization
- Protein
- Prediction
- Amino Acid Composition
- Machine Learning
- Support Vector Machines
- Signal Peptides
- Transmembrane Topology
- Enzyme Subfamily Classes
- Bioinformatics
- Research works
- 26k fractional, since 1950
- In the world top 10%
- 4.2k per year above
- Top-10% rate
- 16.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +28% the tick is no change
Which countries lead Machine Learning in Bioinformatics research?
By volume, China and the United States publish the most (1.7k and 807 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.7k works
- 2 United States 807 works
- 3 India 611 works
- 4 Indonesia 145 works
- 5 Germany 136 works
- 6 United Kingdom 131 works
- 7 South Korea 99 works
- 8 Japan 99 works
- 9 Canada 92 works
- 10 Türkiye 88 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Machine Learning in Bioinformatics research?
By volume in 2022–2025, Central South University publishes the most Machine Learning in Bioinformatics research, followed by University of Electronic Science and Technology of China and Shanghai Jiao Tong University.
By volume, 2022–2025
- 1 Central South University China 29 works
- 2 University of Electronic Science and Technology of China China 26 works
- 3 Shanghai Jiao Tong University China 23 works
- 4 Shandong University China 21 works
- 5 Saveetha University India 20 works
- 6 Vellore Institute of Technology University India 19 works
- 7 University of North Carolina at Chapel Hill United States 18 works
- 8 Chinese Academy of Sciences China 17 works
- 9 Anhui University China 17 works
- 10 Xidian University China 17 works
Who are the leading researchers in Machine Learning in Bioinformatics?
The most-cited researchers publishing on Machine Learning in Bioinformatics include Minoru Kanehisa and Matthias Mann.
- 1 Minoru Kanehisa 5.7k citations
- 2 Matthias Mann 5.1k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Machine Learning in Bioinformatics research done?
The largest centres of Machine Learning in Bioinformatics research in 2022–2025 are Beijing (China), Shanghai (China), Changsha (China) and Chennai (India).
Where is the best place to study Machine Learning in Bioinformatics?
Among universities, judged by research, University of Electronic Science and Technology of China, Quzhou University and Shanghai Maritime University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | University of Electronic Science and Technology of China China | 62.4 | 36.4% | 4.5× | 26 | +71.2% |
| 2 | Quzhou University China | 58.9 | 29.3% | 32.2× | 11 | — |
| 3 | Shanghai Maritime University China | 54.3 | 30.6% | 9.1× | 12 | +9.8% |
| 4 | Shandong University China | 52.9 | 32.8% | 3.5× | 21 | +53.4% |
| 5 | Amrita Vishwa Vidyapeetham India | 52.4 | 18.3% | 5.7× | 16 | +397.7% |
| 6 | Central South University China | 51.2 | 27.7% | 3.4× | 29 | +4.3% |
| 7 | Jeonbuk National University South Korea | 49.3 | 25.7% | 8.1× | 10 | — |
| 8 | King Abdulaziz University Saudi Arabia | 47.5 | 31.4% | 3.1× | 9 | +144.5% |
| 9 | Beijing Institute of Technology China | 47.0 | 33.8% | 2.2× | 13 | +125.2% |
| 10 | University of Missouri United States | 46.8 | 30.6% | 5.8× | 11 | +21.2% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Machine Learning in Bioinformatics research growing?
Output in 2018–2022 was 28% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Machine Learning in Bioinformatics.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.