Anders Krogh
Impact in
- Infectious Diseases top 0.2%
- Tuberculosis Research and Epidemiology
- Molecular Biology top 0.1%
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
Papers in
-
- Genomics and Phylogenetic Studies 54
- Machine Learning in Bioinformatics 25
- Protein Structure and Dynamics 14
- Genomics and Chromatin Dynamics 10
- Fractal and DNA sequence analysis 10
- RNA Research and Splicing 9
-
- Neural Networks and Applications 23
- Co-authors
- Erik L. L. Sonnhammer (4 shared papers)Graeme Mitchison (7 shared papers)Richard M. Durbin (12 shared papers)Sean R. Eddy (12 shared papers)Lukas Käll (3 shared papers)John Hertz (16 shared papers)Gunnar von HEIJNE (4 shared papers)Peter Menzel (7 shared papers)
- Journals
- BMC Bioinformatics (8 papers)Bioinformatics (8 papers)Nucleic Acids Research (7 papers)Nature (6 papers)Nature Communications (6 papers)
- Partner nations
- DenmarkUnited StatesUnited Kingdom
In The Last Decade
Anders Krogh
168 papers receiving 39.7k citations
Anders Krogh's Hit Papers
Peers
Comparison fields: 5 of 225
- Infectious Diseases 5k
- Molecular Biology 14.9k
- Genetics 5.1k
- Cancer Research 1.8k
- Artificial Intelligence 4.3k
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 174 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence Hit paper breakdown → | 1998 | 6674 |
| 2 | Biological sequence analysis probabilistic models of proteins and nucleic acids Hit paper breakdown → | 1998 | 2630 |
| 3 | Biological Sequence Analysis Hit paper breakdown → | 1998 | 2477 |
| 4 | A hidden Markov model for predicting transmembrane helices in protein sequences. Hit paper breakdown → | 1998 | 2130 |
| 5 | A Combined Transmembrane Topology and Signal Peptide Prediction Method Hit paper breakdown → | 2004 | 1942 |
| 6 | Fast and sensitive taxonomic classification for metagenomics with Kaiju Hit paper breakdown → | 2016 | 1525 |
| 7 | Hidden Markov Models in Computational Biology Hit paper breakdown → | 1994 | 1472 |
| 8 | Neural Network Ensembles, Cross Validation, and Active Learning Hit paper breakdown → | 1994 | 1423 |
| 9 | Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server Hit paper breakdown → | 2007 | 1368 |
| 10 | Complete genome sequence of a multiple drug resistant Salmonella enterica serovar Typhi CT18 Hit paper breakdown → | 2001 | 1060 |
| 11 | Introduction to the Theory of Neural Computation Hit paper breakdown → | 1994 | 1048 |
| 12 | 2007 | 981 | |
| 13 | Prediction of lipoprotein signal peptides in Gram‐negative bacteria Hit paper breakdown → | 2003 | 935 |
| 14 | Introduction to the Theory of Neural Computation Hit paper breakdown → | 1991 | 868 |
| 15 | A Simple Weight Decay Can Improve Generalization Hit paper breakdown → | 1992 | 788 |
| 16 | Whole-genome sequencing of cultivated and wild peppers provides insights into Capsicum domestication and specialization Hit paper breakdown → | 2014 | 663 |
| 17 | Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse Hit paper breakdown → | 2013 | 650 |
| 18 | What are artificial neural networks? Hit paper breakdown → | 2008 | 635 |
| 19 | Ancient human genome sequence of an extinct Palaeo-Eskimo Hit paper breakdown → | 2010 | 611 |
| 20 | 2007 | 567 |
About Anders Krogh
Anders Krogh is a scholar working on Molecular Biology, Artificial Intelligence, Cancer Research, Genetics and Paleontology, having authored 174 papers that have together received 41.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (54 papers), Machine Learning in Bioinformatics (25 papers), Neural Networks and Applications (23 papers), Protein Structure and Dynamics (14 papers), MicroRNA in disease regulation (14 papers), Genomics and Chromatin Dynamics (10 papers), Fractal and DNA sequence analysis (10 papers) and RNA Research and Splicing (9 papers). The work is most often cited by research in Infectious Diseases (5k citations), Molecular Biology (14.9k citations), Genetics (5.1k citations), Cancer Research (1.8k citations) and Artificial Intelligence (4.3k citations). Anders Krogh has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include Erik L. L. Sonnhammer, Graeme Mitchison, Richard M. Durbin, Sean R. Eddy, Lukas Käll, John Hertz, Gunnar von HEIJNE, Peter Menzel, Kim Lee Ng and Shahzad I. Mian. Their work appears in journals such as BMC Bioinformatics, Bioinformatics, Nucleic Acids Research, Nature and Nature Communications.
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.