Johan Pensar
Impact in
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria
- Endocrinology top 10%
- Escherichia coli research studies
Papers in
-
- Bayesian Modeling and Causal Inference 16
- Bayesian Methods and Mixture Models 4
-
- Genomics and Phylogenetic Studies 5
- Co-authors
- Jukka Corander (27 shared papers)Santeri Puranen (5 shared papers)Maiju Pesonen (6 shared papers)Timo Koski (3 shared papers)Ida Scheel (2 shared papers)Anders Hjort (3 shared papers)Dag Einar Sommervoll (2 shared papers)Rob J. L. Willems (3 shared papers)
- Journals
- International Journal of Approximate Reasoning (2 papers)Nature Communications (2 papers)Microbial Genomics (2 papers)Statistics and Computing (2 papers)Bayesian Analysis (2 papers)
- Partner nations
- FinlandNorwayUnited Kingdom
In The Last Decade
Johan Pensar
36 papers receiving 553 citations
Peers
Comparison fields: 5 of 110
- Molecular Medicine 64
- Endocrinology 52
- Clinical Biochemistry 45
- Infectious Diseases 102
- Statistics and Probability 36
Countries citing papers authored by Johan Pensar
This map shows the geographic impact of Johan Pensar'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 Johan Pensar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johan Pensar more than expected).
Fields of papers citing papers by Johan Pensar
This network shows the impact of papers produced by Johan Pensar. 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 Johan Pensar. The network helps show where Johan Pensar may publish in the future.
Co-authors
The 25 scholars most cited alongside Johan Pensar, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 93 | |
| 2 | 2021 | 83 | |
| 3 | 2012 | 56 | |
| 4 | 2019 | 30 | |
| 5 | 2022 | 27 | |
| 6 | 2014 | 25 | |
| 7 | 2022 | 20 | |
| 8 | 2015 | 19 | |
| 9 | 2020 | 18 | |
| 10 | 2018 | 17 | |
| 11 | 2013 | 14 | |
| 12 | 2016 | 13 | |
| 13 | 2014 | 13 | |
| 14 | 2021 | 12 | |
| 15 | 2023 | 12 | |
| 16 | 2020 | 11 | |
| 17 | 2024 | 10 | |
| 18 | 2017 | 9 | |
| 19 | 2015 | 8 | |
| 20 | 1993 | 7 |
About Johan Pensar
Johan Pensar is a scholar working on Artificial Intelligence, Molecular Biology, Statistics and Probability, Control and Systems Engineering and Signal Processing, having authored 40 papers that have together received 563 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (16 papers), Genomics and Phylogenetic Studies (5 papers), Data Management and Algorithms (4 papers), Statistical Methods and Inference (4 papers), Bayesian Methods and Mixture Models (4 papers), Statistical Methods and Bayesian Inference (4 papers), Evolution and Genetic Dynamics (3 papers) and Advanced Causal Inference Techniques (3 papers). The work is most often cited by research in Molecular Medicine (64 citations), Endocrinology (52 citations), Clinical Biochemistry (45 citations), Infectious Diseases (102 citations) and Statistics and Probability (36 citations). Johan Pensar has collaborated with scholars based in Finland, Norway and United Kingdom. Frequent co-authors include Jukka Corander, Santeri Puranen, Maiju Pesonen, Timo Koski, Ida Scheel, Anders Hjort, Dag Einar Sommervoll, Rob J. L. Willems, Sergio Arredondo-Alonso and Anita C. Schürch. Their work appears in journals such as International Journal of Approximate Reasoning, Nature Communications, Microbial Genomics, Statistics and Computing and Bayesian Analysis.
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.