Timo Koski

1.7k total citations
79 papers, 1.0k citations indexed

About

Timo Koski is a scholar working on Artificial Intelligence, Molecular Biology and Statistics and Probability. According to data from OpenAlex, Timo Koski has authored 79 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 20 papers in Molecular Biology and 11 papers in Statistics and Probability. Recurrent topics in Timo Koski's work include Bayesian Methods and Mixture Models (18 papers), Bayesian Modeling and Causal Inference (13 papers) and Genomics and Phylogenetic Studies (9 papers). Timo Koski is often cited by papers focused on Bayesian Methods and Mixture Models (18 papers), Bayesian Modeling and Causal Inference (13 papers) and Genomics and Phylogenetic Studies (9 papers). Timo Koski collaborates with scholars based in Sweden, Finland and Czechia. Timo Koski's co-authors include John M. Noble, Mats Gyllenberg, Jukka Corander, Martin Verlaan, Johan Pensar, Óscar Puig, Elisabeth Bragado‐Nilsson, Bertrand Séraphin, Helge Gyllenberg and Mark S. Johnson and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Journal of Molecular Biology.

In The Last Decade

Timo Koski

75 papers receiving 933 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Timo Koski Sweden 16 466 238 129 126 101 79 1.0k
Tomi Silander Finland 17 484 1.0× 207 0.9× 73 0.6× 60 0.5× 28 0.3× 54 992
Cédric Archambeau United Kingdom 19 606 1.3× 150 0.6× 145 1.1× 108 0.9× 20 0.2× 49 1.1k
Michael U. Gutmann Finland 16 1.1k 2.3× 185 0.8× 165 1.3× 130 1.0× 77 0.8× 51 1.9k
Edward B. Fowlkes United States 12 659 1.4× 217 0.9× 234 1.8× 178 1.4× 27 0.3× 21 1.5k
David J. Marchette United States 20 612 1.3× 98 0.4× 162 1.3× 158 1.3× 36 0.4× 72 1.3k
Alessandro Rinaldo United States 20 565 1.2× 139 0.6× 567 4.4× 77 0.6× 84 0.8× 57 1.5k
Yubin Yubin China 9 225 0.5× 120 0.5× 370 2.9× 68 0.5× 35 0.3× 48 1.0k
G. Govaert France 9 698 1.5× 132 0.6× 266 2.1× 147 1.2× 41 0.4× 14 1.1k
Gal Elidan Israel 18 575 1.2× 607 2.6× 52 0.4× 59 0.5× 77 0.8× 45 1.6k
Jie Ding United States 13 247 0.5× 153 0.6× 78 0.6× 96 0.8× 27 0.3× 64 869

Countries citing papers authored by Timo Koski

Since Specialization
Citations

This map shows the geographic impact of Timo Koski'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 Timo Koski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timo Koski more than expected).

Fields of papers citing papers by Timo Koski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Timo Koski. 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 Timo Koski. The network helps show where Timo Koski may publish in the future.

Co-authorship network of co-authors of Timo Koski

This figure shows the co-authorship network connecting the top 25 collaborators of Timo Koski. A scholar is included among the top collaborators of Timo Koski based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Timo Koski. Timo Koski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Westerlind, Helga, Ryan Ramanujam, Kjell‐Morten Myhr, et al.. (2014). Identity-by-descent mapping in a Scandinavian multiple sclerosis cohort. European Journal of Human Genetics. 23(5). 688–692. 13 indexed citations
2.
Xiong, Jie, et al.. (2013). Sparse Markov Chains for Sequence Data. Scandinavian Journal of Statistics. 41(3). 639–655. 17 indexed citations
3.
Koski, Timo, et al.. (2012). Performance Evaluation of Artificial Neural Networks in the Foreign Exchange Market. 1 indexed citations
4.
5.
Corander, Jukka, Mats Gyllenberg, & Timo Koski. (2010). Learning Genetic Population Structures Using Minimization of. 1 indexed citations
6.
Koski, Timo & John M. Noble. (2009). Bayesian Networks. Wiley series in probability and statistics. 79 indexed citations
7.
Koski, Timo, et al.. (2009). The Likelihood Ratio Statistic for Testing Spatial Independence using a Separable Covariance Matrix. 1 indexed citations
8.
Koski, Timo, et al.. (2006). Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation. Journal of Machine Learning Research. 7(87). 2449–2480. 5 indexed citations
9.
Corander, Jukka, Mats Gyllenberg, & Timo Koski. (2006). Random Partition Models and Exchangeability for Bayesian Identification of Population Structure. Bulletin of Mathematical Biology. 69(3). 797–815. 32 indexed citations
10.
Austin, Brian, Peter Dawyndt, Mats Gyllenberg, et al.. (2004). Sliding window discretization: a new method for multiple band matching of bacterial genotyping fingerprints. Bulletin of Mathematical Biology. 66(6). 1575–1596. 3 indexed citations
11.
Gyllenberg, Mats, et al.. (2003). A Bayesian molecular interaction library. Journal of Computer-Aided Molecular Design. 17(7). 435–461. 11 indexed citations
12.
Gyllenberg, Mats, Timo Koski, Peter Dawyndt, et al.. (2002). New Methods for the Analysis of Binarized BIOLOG GN Data of Vibrio species: Minimization of Stochastic Complexity and Cumulative Classification. Systematic and Applied Microbiology. 25(3). 403–415. 4 indexed citations
13.
Gyllenberg, Mats, et al.. (2002). A dissimilarity matrix between protein atom classes basedon Gaussian mixtures. Bioinformatics. 18(9). 1257–1263. 4 indexed citations
14.
Gyllenberg, Mats & Timo Koski. (2002). Bayesian predictiveness, exchangeability and sufficientness in bacterial taxonomy. Mathematical Biosciences. 177-178. 161–184. 9 indexed citations
15.
Gyllenberg, Helge, et al.. (2000). Singling out Ill-fit Items in a Classification. Application to the Taxonomy of Enterobacteriaceae. Archives of Control Sciences. 9. 97–105. 1 indexed citations
16.
Fränti, Pasi, Helge Gyllenberg, Mats Gyllenberg, et al.. (2000). Minimizing stochastic complexity using local search and GLA with applications to classification of bacteria. Biosystems. 57(1). 37–48. 5 indexed citations
17.
Gyllenberg, Helge, Mats Gyllenberg, Timo Koski, & Torben E. Lund. (1998). Stochastic complexity as a taxonomic tool. Computer Methods and Programs in Biomedicine. 56(1). 11–22. 11 indexed citations
18.
Gyllenberg, Mats, Timo Koski, & Martin Verlaan. (1997). Classification of Binary Vectors by Stochastic Complexity. Journal of Multivariate Analysis. 63(1). 47–72. 35 indexed citations
19.
Koski, Timo, Lars‐Erik Persson, & J. Peetre. (1994). ϵ-Entropy, ϵ-Rate, and Interpolation Spaces Revisited with an Application to Linear Communication Channels. Journal of Mathematical Analysis and Applications. 186(1). 265–276. 1 indexed citations
20.
Koski, Timo. (1987). Martingale Methods for Log Likelihood Identification of Some Stochastic Evolution Equations. IFAC Proceedings Volumes. 20(1). 11–15. 1 indexed citations

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.

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