# Erik L. L. Sonnhammer
**Erik L. L. Sonnhammer** is a Swedish-based bioinformatician, Professor of Bioinformatics at [Stockholm University](https://www.edgepedia.org/stockholm-university)'s Department of Biochemistry and [Biophysics](https://www.edgepedia.org/biophysics) and at Science for Life Laboratory in Solna, and the creator of several widely used computational biology resources: the Pfam protein domain database, the InParanoid orthology (genes in different species descended from a common ancestral gene) tools, the Phobius transmembrane predictor, and the FunCoup functional network database.[1](https://sonnhammer.org/index.html) • [2](https://www.su.se/english/profiles/e/esonn) His ORCID identifier is 0000-0002-9015-5588.[1](https://sonnhammer.org/index.html)
| Key facts | |
|---|---|
| Position | Professor of Bioinformatics, Department of Biochemistry and Biophysics, Stockholm University, and Science for Life Laboratory[1](https://sonnhammer.org/index.html) • [3](https://publications-affiliated.scilifelab.se/researcher/8c4fb5f5a50a4dbb91bbea3cc6861ffa) |
| Field | Bioinformatics: protein function prediction, orthology analysis, gene regulatory and functional association networks[2](https://www.su.se/english/profiles/e/esonn) |
| Signature work | FunCoup 6, Nucleic Acids Research, 2025[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701656/) |
| Major databases created | Pfam (1995) — according to *Pfam 10 years on: 10 000 families and still growing* — InParanoid (2001), Phobius (2004), FunCoup, InParanoiDB |[5](https://doi.org/10.1093/bib/bbn010) • [6](https://inparanoidb.sbc.su.se/about/) • [7](https://sonnhammer.org/databases.html)
| Current role | Director of the Stockholm Bioinformatics Centre[8](https://www.sbc.su.se/about/) |
| Funding | Swedish Research Council grants 2022-06725, 2018-05973, and 2019-04095, and Stockholm University[9](http://su.diva-portal.org/smash/person.jsf?pid=authority-person%3A84235) |
## Research program
His group predicts protein function in terms of biochemical activity and role in a pathway, using hidden Markov models, Bayesian networks, clustering algorithms, evolutionary models, and discriminant statistical methods.[2](https://www.su.se/english/profiles/e/esonn) A second line develops integrative computational methods and databases for predicting pathway interactions, with a focus on identifying new disease genes; the resulting networks are published at FunCoup.[2](https://www.su.se/english/profiles/e/esonn) The group's stated interests include advanced methods for protein function prediction and machine learning in bioinformatics.[10](https://www.su.se/english/research/research-catalogue/research-groups/b/erik-sonnhammers-research-group)
## Representative work
**Phobius.** Phobius is a combined transmembrane topology and signal peptide predictor.[7](https://sonnhammer.org/databases.html) The lab's resource pages describe the earlier hidden Markov model TMHMM as superseded by Phobius, which it states is better at all types of prediction.[7](https://sonnhammer.org/databases.html) According to the Pfam database paper in Nucleic Acids Research (2007), the combined approach was introduced in a 2004 Journal of Molecular Biology method paper on which Sonnhammer is a co-author.[11](https://doi.org/10.1093/nar/gkm960)
## Pfam, InParanoid and orthology
**Pfam.** Sonnhammer co-founded Pfam in 1995 as a collection of common protein domains for annotating the complex proteins of multicellular animals.[5](https://doi.org/10.1093/bib/bbn010) Each Pfam entry holds a seed alignment and a full alignment; sequences for the full alignment are found by searching a profile hidden [Markov model](https://www.edgepedia.org/markov-model) built with the HMMer program against UniProt.[5](https://doi.org/10.1093/bib/bbn010) He co-authored the founding 1997 paper in Proteins on seed alignments and the 1998 Nucleic Acids Research description of the database.[12](https://sonnhammer.sbc.su.se/publications.html) Release 22.0 (2007) contained 9,318 protein families,[11](https://doi.org/10.1093/nar/gkm960) and, according to the 2014 Pfam update in *Nucleic Acids Research*, version 27.0 (2014) contained about 12,000 manually curated entries while holding UniProtKB sequence coverage at nearly 80% despite a 50% growth in the underlying sequence database.[13](https://academic.oup.com/nar/article-pdf/42/D1/D222/3643441/gkt1223.pdf)
**InParanoid.** The original InParanoid method, described by Remm, Storm, and Sonnhammer in 2001, constructs orthology groups from pairwise similarity scores, calculated with DIAMOND, between two complete proteomes.[19](https://pubmed.ncbi.nlm.nih.gov/11743721/) Each group starts from two seed orthologs found by two-way best hits; additional recently duplicated genes within each species, the inparalogs, are then added with confidence values.[6](https://inparanoidb.sbc.su.se/about/) A 2022 reimplementation, InParanoid-DIAMOND, made the analysis faster.[6](https://inparanoidb.sbc.su.se/about/) The companion method Hieranoid, published in the Journal of Molecular Biology in 2013, extends orthology inference to many species by progressively applying the pairwise InParanoid method at nodes of a bifurcating guide tree, giving linear computational complexity; on the orthobench benchmark it produced lower total levels of false and missing orthology assignments than other methods.[14](https://sonnhammer.sbc.su.se/download/papers/2013_JMB_425_2072-2081.pdf)
## FunCoup and network biology
FunCoup builds genome-wide functional association networks that link genes and proteins likely to participate in the same pathway, aimed at identifying new disease genes.[2](https://www.su.se/english/profiles/e/esonn) Version 6, published in Nucleic Acids Research in 2025, expands gene regulatory link coverage, adds bin-free Bayesian training, and a new website at funcoup.org.[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701656/) It integrates the TOPAS algorithm for disease and drug target module identification and pathway enrichment analysis using the ANUBIX and EASE algorithms.[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701656/) Bin-free training was applied to 23 primary species, with networks generated for all remaining 618 species in InParanoiDB 9.[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701656/) The human network alone now includes over half a million directed gene regulatory links, and 13 species carry regulatory links.[15](https://data.scilifelab.se/highlights/funcoup6/) FunCoup 6 was developed by Erik Sonnhammer's group at SciLifeLab and contains major updates.[16](https://www.scilifelab.se/news/funcoup-6-a-major-update/) The live database covers species from [Arabidopsis thaliana](https://www.edgepedia.org/arabidopsis-thaliana) to Bos taurus and [Caenorhabditis elegans](https://www.edgepedia.org/caenorhabditis-elegans), with configurable direction confidence thresholds.[17](https://funcoup.org/)
## Recent developments
InParanoiDB 9, published in the Journal of Molecular Biology in 2023, covers about 600 species, built on proteomes from roughly 400 eukaryotes, 100+ bacteria, and 30+ archaea; according to the Sonnhammer group's Stockholm University research portal entry, it includes over one billion predicted ortholog groups for both protein domains and full-length proteins.[9](http://su.diva-portal.org/smash/person.jsf?pid=authority-person%3A84235) Pfam itself has moved on under new stewardship: since 2020 the standalone Pfam website has been decommissioned in favor of integration with InterPro, the database has been harmonized with the ECOD structural classification, and [AlphaFold](https://www.edgepedia.org/alphafold) structure predictions are now used to refine domain boundaries and identify new domains.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701544/) A deep-learning extension, Pfam-N, achieved an 8.8% increase in UniProtKB coverage compared with standard Pfam.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701544/)
According to the Sonnhammer Group's publications page, the group's recent output centers on gene regulatory network inference and its evaluation: GeneSPIDER2 for large-scale simulation and benchmarking with perturbed single-cell data (2024), BiGSM for Bayesian inference via sparse modeling and topology-based metrics for optimal sparsity (both 2025, in [Bioinformatics](https://www.edgepedia.org/bioinformatics)), and GeneSNAKE, a Python package for benchmarking and simulation of gene regulatory networks, published in Bioinformatics Advances in 2026 with Sonnhammer as corresponding author.[12](https://sonnhammer.sbc.su.se/publications.html) Sonnhammer also co-authored 2024 Quest for Orthologs consortium papers on benchmark service developments and orthology in the era of biodiversity genomics.[12](https://sonnhammer.sbc.su.se/publications.html) A 2026 paper in [Scientific Reports](https://www.edgepedia.org/scientific-reports) applies the group's network tools to the RBP regulome in liver cancer, identifying functional modules and drug candidates.[12](https://sonnhammer.sbc.su.se/publications.html)
## Institutional roles and funding
Sonnhammer became director of the Stockholm Bioinformatics Centre (SBC). SBC was started in January 2000 as a collaboration between Stockholm University, the Royal Institute of Technology, and Karolinska Institutet, with main funding from the Swedish Foundation for Strategic Research during its first five years; since 2005 it has received center funding from Stockholm University and the Royal Institute of Technology.[8](https://www.sbc.su.se/about/) His research is funded by Swedish Research Council grants 2022-06725, 2018-05973, and 2019-04095, and by Stockholm University.[9](http://su.diva-portal.org/smash/person.jsf?pid=authority-person%3A84235)
## References
1. [The Sonnhammer Bioinformatics Lab](https://sonnhammer.org/index.html)
2. [Erik Sonnhammer - Stockholm University](https://www.su.se/english/profiles/e/esonn)
3. [Sonnhammer ELL - Science for Life Laboratory](https://publications-affiliated.scilifelab.se/researcher/8c4fb5f5a50a4dbb91bbea3cc6861ffa)
4. [FunCoup 6: advancing functional association networks across species with directed links and improved user experience](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701656/)
5. [Pfam 10 years on: 10 000 families and still growing](https://doi.org/10.1093/bib/bbn010)
6. [InParanoiDB 9 - About](https://inparanoidb.sbc.su.se/about/)
7. [Databases and Servers - Sonnhammer lab](https://sonnhammer.org/databases.html)
8. [Stockholm Bioinformatics Centre - About](https://www.sbc.su.se/about/)
9. [Sonnhammer, Erik L. L. - Stockholm University research portal](http://su.diva-portal.org/smash/person.jsf?pid=authority-person%3A84235)
10. [Erik Sonnhammer's research group - Stockholm University](https://www.su.se/english/research/research-catalogue/research-groups/b/erik-sonnhammers-research-group)
11. [The Pfam protein families database (Nucleic Acids Research, 2007)](https://doi.org/10.1093/nar/gkm960)
12. [Sonnhammer Group Publications](https://sonnhammer.sbc.su.se/publications.html)
13. [Pfam 27.0 database update](https://academic.oup.com/nar/article-pdf/42/D1/D222/3643441/gkt1223.pdf)
14. [Hieranoid: Hierarchical Orthology Inference (Journal of Molecular Biology, 2013)](https://sonnhammer.sbc.su.se/download/papers/2013_JMB_425_2072-2081.pdf)
15. [FunCoup 6: Large-scale functional association networks with regulatory links and integrated tools](https://data.scilifelab.se/highlights/funcoup6/)
16. [FunCoup 6: A major update - SciLifeLab](https://www.scilifelab.se/news/funcoup-6-a-major-update/)
17. [FunCoup - functional gene/protein association networks database](https://funcoup.org/)
18. [The Pfam protein families database: embracing AI/ML](https://pmc.ncbi.nlm.nih.gov/articles/PMC11701544/)
19. [pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/11743721/)
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*Topic: Encyclopedia › Life and health › Life and health scientists › Life scientists › Researchers in computational biology, bioinformatics, and systems biology › Bioinformatics algorithms and sequence analysis*
*Initially written Sep 21, 2026 · Reviewed: Sep 25, 2026; Sep 30, 2026 · Edited: Sep 25, 2026; Sep 30, 2026; Oct 15, 2026; Oct 25, 2026 · Last review: Sep 30, 2026*
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License: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license