Søren Brunak
Impact in
- Molecular Biology top 0.02%
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- vaccines and immunoinformatics approaches
- Bioinformatics and Genomic Networks
- Glycosylation and Glycoproteins Research
- Photosynthetic Processes and Mechanisms
- Protein Structure and Dynamics
- Biotechnology top 0.05%
Papers in
-
- Machine Learning in Bioinformatics 53
- RNA and protein synthesis mechanisms 48
- Genomics and Phylogenetic Studies 33
- Bioinformatics and Genomic Networks 31
- Protein Structure and Dynamics 25
- vaccines and immunoinformatics approaches 22
- Glycosylation and Glycoproteins Research 19
- Genetics 40
- Co-authors
- Henrik Nielsen (15 shared papers)Gunnar von Heijne (15 shared papers)Jannick Dyrløv Bendtsen (4 shared papers)Nikolaj Blom (14 shared papers)Jacob Engelbrecht (12 shared papers)Olof Emanuelsson (2 shared papers)Ramneek Gupta (20 shared papers)Steen Gammeltoft (3 shared papers)
- Journals
- Bioinformatics (13 papers)Journal of Molecular Biology (12 papers)Nucleic Acids Research (12 papers)PLoS ONE (10 papers)Proteins Structure Function and Bioinformatics (8 papers)
- Partner nations
- DenmarkUnited StatesSweden
In The Last Decade
Søren Brunak
339 papers receiving 55.2k citations
Søren Brunak's Hit Papers
Peers
Comparison fields: 5 of 222
- Molecular Biology 33.0k
- Biotechnology 2.5k
- Immunology 5.5k
- Microbiology 1.5k
- Parasitology 1.6k
Countries citing papers authored by Søren Brunak
This map shows the geographic impact of Søren Brunak'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 Søren Brunak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Søren Brunak more than expected).
Fields of papers citing papers by Søren Brunak
This network shows the impact of papers produced by Søren Brunak. 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 Søren Brunak. The network helps show where Søren Brunak may publish in the future.
Co-authors
The 25 scholars most cited alongside Søren Brunak, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 346 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Improved Prediction of Signal Peptides: SignalP 3.0 Hit paper breakdown → | 2004 | 5584 |
| 2 | Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites Hit paper breakdown → | 1997 | 4856 |
| 3 | Predicting Subcellular Localization of Proteins Based on their N-terminal Amino Acid Sequence Hit paper breakdown → | 2000 | 3600 |
| 4 | SignalP 5.0 improves signal peptide predictions using deep neural networks Hit paper breakdown → | 2019 | 3057 |
| 5 | Locating proteins in the cell using TargetP, SignalP and related tools Hit paper breakdown → | 2007 | 2678 |
| 6 | Sequence and structure-based prediction of eukaryotic protein phosphorylation sites Hit paper breakdown → | 1999 | 2635 |
| 7 | Prediction of post‐translational glycosylation and phosphorylation of proteins from the amino acid sequence Hit paper breakdown → | 2004 | 1633 |
| 8 | Assessing the accuracy of prediction algorithms for classification: an overview Hit paper breakdown → | 2000 | 1617 |
| 9 | SignalP 6.0 predicts all five types of signal peptides using protein language models Hit paper breakdown → | 2022 | 1496 |
| 10 | Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis Hit paper breakdown → | 2010 | 1229 |
| 11 | Precision mapping of the human O‐GalNAc glycoproteome through SimpleCell technology Hit paper breakdown → | 2013 | 1111 |
| 12 | Mining electronic health records: towards better research applications and clinical care Hit paper breakdown → | 2012 | 1058 |
| 13 | Feature-based prediction of non-classical and leaderless protein secretion Hit paper breakdown → | 2004 | 986 |
| 14 | Prediction of lipoprotein signal peptides in Gram‐negative bacteria Hit paper breakdown → | 2003 | 920 |
| 15 | Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations Hit paper breakdown → | 2003 | 837 |
| 16 | Prediction of glycosylation across the human proteome and the correlation to protein function Hit paper breakdown → | 2001 | 787 |
| 17 | Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites Hit paper breakdown → | 2004 | 742 |
| 18 | A human phenome-interactome network of protein complexes implicated in genetic disorders Hit paper breakdown → | 2007 | 660 |
| 19 | Analysis and prediction of leucine-rich nuclear export signals Hit paper breakdown → | 2004 | 646 |
| 20 | Prediction of human mRNA donor and acceptor sites from the DNA sequence Hit paper breakdown → | 1991 | 630 |
About Søren Brunak
Søren Brunak is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Immunology and Oncology, having authored 346 papers that have together received 56.2k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (53 papers), RNA and protein synthesis mechanisms (48 papers), Genomics and Phylogenetic Studies (33 papers), Bioinformatics and Genomic Networks (31 papers), Protein Structure and Dynamics (25 papers), vaccines and immunoinformatics approaches (22 papers), Glycosylation and Glycoproteins Research (19 papers) and Computational Drug Discovery Methods (19 papers). The work is most often cited by research in Molecular Biology (33.0k citations), Biotechnology (2.5k citations), Immunology (5.5k citations), Microbiology (1.5k citations) and Parasitology (1.6k citations). Søren Brunak has collaborated with scholars based in Denmark, United States and Sweden. Frequent co-authors include Henrik Nielsen, Gunnar von Heijne, Jannick Dyrløv Bendtsen, Nikolaj Blom, Jacob Engelbrecht, Olof Emanuelsson, Ramneek Gupta, Steen Gammeltoft, Lars Juhl Jensen and Pierre Baldi. Their work appears in journals such as Bioinformatics, Journal of Molecular Biology, Nucleic Acids Research, PLoS ONE and Proteins Structure Function and Bioinformatics.
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.