Anders Krogh
Impact in
- Molecular Biology top 0.05%
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- Endocrinology top 0.5%
Papers in
-
- Machine Learning in Bioinformatics 45
- Genomics and Phylogenetic Studies 37
- RNA and protein synthesis mechanisms 36
- Protein Structure and Dynamics 17
- Genomics and Chromatin Dynamics 10
- RNA Research and Splicing 9
-
- Neural Networks and Applications 18
- Algorithms and Data Compression 13
- Co-authors
- Erik L. L. Sonnhammer (5 shared papers)Gunnar von Heijne (5 shared papers)B. Larsson (1 shared paper)Lukas Käll (3 shared papers)John Hertz (16 shared papers)Graeme Mitchison (3 shared papers)Richard Durbin (12 shared papers)Sean R. Eddy (12 shared papers)
- Journals
- Bioinformatics (8 papers)BMC Bioinformatics (8 papers)Journal of Molecular Biology (7 papers)Nucleic Acids Research (6 papers)PLoS Computational Biology (6 papers)
- Partner nations
- DenmarkUnited StatesUnited Kingdom
In The Last Decade
Anders Krogh
153 papers receiving 35.9k citations
Anders Krogh's Hit Papers
Peers
Comparison fields: 5 of 229
- Molecular Biology 19.5k
- Endocrinology 820
- Cancer Research 2.1k
- Microbiology 836
- Ecology 3.5k
Countries citing papers authored by Anders Krogh
This map shows the geographic impact of Anders Krogh'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 Anders Krogh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anders Krogh more than expected).
Fields of papers citing papers by Anders Krogh
This network shows the impact of papers produced by Anders Krogh. 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 Anders Krogh. The network helps show where Anders Krogh may publish in the future.
Co-authors
The 25 scholars most cited alongside Anders Krogh, 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 158 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen Hit paper breakdown → | 2001 | 10238 |
| 2 | Biological Sequence Analysis Hit paper breakdown → | 1998 | 2477 |
| 3 | A hidden Markov model for predicting transmembrane helices in protein sequences. Hit paper breakdown → | 1998 | 2135 |
| 4 | A Combined Transmembrane Topology and Signal Peptide Prediction Method Hit paper breakdown → | 2004 | 1872 |
| 5 | Hidden Markov Models in Computational Biology Hit paper breakdown → | 1994 | 1487 |
| 6 | Neural Network Ensembles, Cross Validation, and Active Learning Hit paper breakdown → | 1994 | 1438 |
| 7 | Fast and sensitive taxonomic classification for metagenomics with Kaiju Hit paper breakdown → | 2016 | 1408 |
| 8 | Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server Hit paper breakdown → | 2007 | 1316 |
| 9 | Introduction to the Theory of Neural Computation Hit paper breakdown → | 1994 | 1054 |
| 10 | Programmed Cell Death 4 (PDCD4) Is an Important Functional Target of the MicroRNA miR-21 in Breast Cancer Cells Hit paper breakdown → | 2007 | 982 |
| 11 | Prediction of lipoprotein signal peptides in Gram‐negative bacteria Hit paper breakdown → | 2003 | 930 |
| 12 | Introduction to the Theory of Neural Computation Hit paper breakdown → | 1991 | 854 |
| 13 | A Simple Weight Decay Can Improve Generalization Hit paper breakdown → | 1991 | 753 |
| 14 | What are artificial neural networks? Hit paper breakdown → | 2008 | 603 |
| 15 | JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update Hit paper breakdown → | 2007 | 571 |
| 16 | Prediction of signal peptides and signal anchors by a hidden Markov model. | 1998 | 439 |
| 17 | 1996 | 355 | |
| 18 | Introduction to the Theory of Neural Computation Hit paper breakdown → | 2018 | 324 |
| 19 | 2011 | 305 | |
| 20 | 2005 | 277 |
About Anders Krogh
Anders Krogh is a scholar working on Molecular Biology, Artificial Intelligence, Cancer Research, Genetics and Ecology, having authored 158 papers that have together received 37.0k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (45 papers), Genomics and Phylogenetic Studies (37 papers), RNA and protein synthesis mechanisms (36 papers), Neural Networks and Applications (18 papers), Protein Structure and Dynamics (17 papers), Algorithms and Data Compression (13 papers), Genomics and Chromatin Dynamics (10 papers) and RNA Research and Splicing (9 papers). The work is most often cited by research in Molecular Biology (19.5k citations), Endocrinology (820 citations), Cancer Research (2.1k citations), Microbiology (836 citations) and Ecology (3.5k citations). Anders Krogh has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include Erik L. L. Sonnhammer, Gunnar von Heijne, B. Larsson, Lukas Käll, John Hertz, Graeme Mitchison, Richard Durbin, Sean R. Eddy, Peter Menzel and Kim Lee Ng. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, Journal of Molecular Biology, Nucleic Acids Research and PLoS Computational Biology.
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.