Alex Bateman

151.2k total citations · 22 hit papers
158 papers, 57.2k citations indexed

About

Alex Bateman is a scholar working on Molecular Biology, Genetics and Materials Chemistry. According to data from OpenAlex, Alex Bateman has authored 158 papers receiving a total of 57.2k indexed citations (citations by other indexed papers that have themselves been cited), including 133 papers in Molecular Biology, 23 papers in Genetics and 22 papers in Materials Chemistry. Recurrent topics in Alex Bateman's work include Genomics and Phylogenetic Studies (58 papers), RNA and protein synthesis mechanisms (42 papers) and Machine Learning in Bioinformatics (36 papers). Alex Bateman is often cited by papers focused on Genomics and Phylogenetic Studies (58 papers), RNA and protein synthesis mechanisms (42 papers) and Machine Learning in Bioinformatics (36 papers). Alex Bateman collaborates with scholars based in United Kingdom, United States and Sweden. Alex Bateman's co-authors include ROBERT FINN, Sean R. Eddy, Jaina Mistry, Erik L. L. Sonnhammer, John Tate, Neil D. Rawlings, Marco Punta, A. John Barrett, Ruth Y. Eberhardt and Gustavo A Salazar and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Alex Bateman

158 papers receiving 56.6k citations

Hit Papers

The Pfam Protein Families Database 2000 2026 2008 2017 2002 2013 2015 2020 2018 2.5k 5.0k 7.5k 10.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Alex Bateman United Kingdom 69 40.4k 13.7k 7.4k 6.8k 2.8k 158 57.2k
ROBERT FINN United Kingdom 57 33.4k 0.8× 12.7k 0.9× 7.4k 1.0× 5.3k 0.8× 2.2k 0.8× 151 48.5k
Sean R. Eddy United States 80 54.3k 1.3× 18.3k 1.3× 13.1k 1.8× 9.1k 1.3× 3.2k 1.1× 127 75.9k
Rodrigo López United Kingdom 32 32.5k 0.8× 13.2k 1.0× 7.9k 1.1× 7.3k 1.1× 5.0k 1.8× 68 57.4k
Erik L. L. Sonnhammer Sweden 51 30.6k 0.8× 10.3k 0.8× 5.6k 0.8× 5.3k 0.8× 2.8k 1.0× 153 44.6k
Hamish McWilliam United Kingdom 15 25.5k 0.6× 10.7k 0.8× 6.7k 0.9× 6.1k 0.9× 4.4k 1.5× 18 46.3k
Eugene W. Myers United States 49 50.9k 1.3× 19.4k 1.4× 14.0k 1.9× 11.8k 1.7× 4.9k 1.8× 126 88.6k
Søren Brunak Denmark 83 35.2k 0.9× 7.8k 0.6× 3.6k 0.5× 5.5k 0.8× 6.1k 2.2× 350 55.8k
Warren Gish United States 17 46.9k 1.2× 18.4k 1.3× 13.8k 1.9× 10.5k 1.5× 4.9k 1.7× 20 80.8k
L. Aravind United States 123 39.4k 1.0× 6.5k 0.5× 6.1k 0.8× 9.0k 1.3× 4.4k 1.6× 381 52.4k
Andreas Wilm Singapore 21 21.0k 0.5× 8.3k 0.6× 5.4k 0.7× 5.0k 0.7× 2.5k 0.9× 29 37.5k

Countries citing papers authored by Alex Bateman

Since Specialization
Citations

This map shows the geographic impact of Alex Bateman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alex Bateman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Bateman more than expected).

Fields of papers citing papers by Alex Bateman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alex Bateman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alex Bateman. The network helps show where Alex Bateman may publish in the future.

Co-authorship network of co-authors of Alex Bateman

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Bateman. A scholar is included among the top collaborators of Alex Bateman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alex Bateman. Alex Bateman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Pei, Jimin, Antonina Andreeva, Sara Chuguransky, et al.. (2024). Bridging the Gap between Sequence and Structure Classifications of Proteins with AlphaFold Models. Journal of Molecular Biology. 436(22). 168764–168764. 5 indexed citations
2.
Andreeva, Antonina, et al.. (2024). Isopeptor: a tool for detecting intramolecular isopeptide bonds in protein structures. Bioinformatics Advances. 5(1). vbaf049–vbaf049. 1 indexed citations
3.
Ontiveros‐Palacios, Nancy, Emma J. Cooke, Eric P. Nawrocki, et al.. (2024). Rfam 15: RNA families database in 2025. Nucleic Acids Research. 53(D1). D258–D267. 30 indexed citations
4.
Blum, Matthias, et al.. (2024). Keeping it in the family: using protein family templates to rescue low confidence AlphaFold2 models. Bioinformatics Advances. 4(1). vbae188–vbae188. 1 indexed citations
5.
Durairaj, Janani, Andrew Waterhouse, Toomas Mets, et al.. (2023). Uncovering new families and folds in the natural protein universe. Nature. 622(7983). 646–653. 78 indexed citations
6.
Lafita, Aleix, Vivian Monzon, Catherine R. Back, et al.. (2023). Domain shuffling of a highly mutable ligand‐binding fold drives adhesin generation across the bacterial kingdom. Proteins Structure Function and Bioinformatics. 91(8). 1007–1020. 2 indexed citations
7.
Monzon, Vivian, Typhaine Paysan‐Lafosse, Valerie Wood, & Alex Bateman. (2022). Reciprocal best structure hits: using AlphaFold models to discover distant homologues. Bioinformatics Advances. 2(1). vbac072–vbac072. 23 indexed citations
8.
Bileschi, Maxwell L., David Belanger, Drew Bryant, et al.. (2022). Using deep learning to annotate the protein universe. Nature Biotechnology. 40(6). 932–937. 164 indexed citations breakdown →
9.
Monzon, Vivian & Alex Bateman. (2022). Large-Scale Discovery of Microbial Fibrillar Adhesins and Identification of Novel Members of Adhesive Domain Families. Journal of Bacteriology. 204(6). e0010722–e0010722. 10 indexed citations
10.
Bateman, Alex, et al.. (2022). DPCfam: Unsupervised protein family classification by Density Peak Clustering of large sequence datasets. PLoS Computational Biology. 18(10). e1010610–e1010610. 7 indexed citations
11.
Whelan, Fiona, Aleix Lafita, Samuel C. Griffiths, et al.. (2021). Periscope Proteins are variable-length regulators of bacterial cell surface interactions. Proceedings of the National Academy of Sciences. 118(23). 14 indexed citations
12.
Wang, Han, et al.. (2020). Caenorhabditis elegans AF4/FMR2 Family Homolog affl-2 Regulates Heat-Shock-Induced Gene Expression. Genetics. 215(4). 1039–1054. 2 indexed citations
13.
Kalvari, Ioanna, Eric P. Nawrocki, Nancy Ontiveros‐Palacios, et al.. (2020). Rfam 14: expanded coverage of metagenomic, viral and microRNA families. Nucleic Acids Research. 49(D1). D192–D200. 584 indexed citations breakdown →
14.
Tonelli, Marco, Woonghee Lee, Ziqing Lin, et al.. (2019). Solution structure of human myeloid-derived growth factor suggests a conserved function in the endoplasmic reticulum. Nature Communications. 10(1). 5612–5612. 14 indexed citations
15.
El-Gebali, Sara, Jaina Mistry, Alex Bateman, et al.. (2018). The Pfam protein families database in 2019. Nucleic Acids Research. 47(D1). D427–D432. 3202 indexed citations breakdown →
16.
FINN, ROBERT, Penelope Coggill, Ruth Y. Eberhardt, et al.. (2015). The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research. 44(D1). D279–D285. 4051 indexed citations breakdown →
17.
Mistry, Jaina, Penny Coggill, Ruth Y. Eberhardt, et al.. (2013). The challenge of increasing Pfam coverage of the human proteome. Database. 2013. bat023–bat023. 23 indexed citations
18.
FINN, ROBERT, Alex Bateman, Jody Clements, et al.. (2013). Pfam: the protein families database. Nucleic Acids Research. 42(D1). D222–D230. 4740 indexed citations breakdown →
19.
Rawlings, Neil D., A. John Barrett, & Alex Bateman. (2011). MEROPS: the database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Research. 40(D1). D343–D350. 1273 indexed citations breakdown →
20.
Bateman, Alex, et al.. (1999). The SIS domain: a phosphosugar-binding domain. Trends in Biochemical Sciences. 24(3). 94–95. 76 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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