Jari Björne

4.1k total citations
32 papers, 1.7k citations indexed

About

Jari Björne is a scholar working on Molecular Biology, Artificial Intelligence and Health Informatics. According to data from OpenAlex, Jari Björne has authored 32 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 25 papers in Artificial Intelligence and 2 papers in Health Informatics. Recurrent topics in Jari Björne's work include Biomedical Text Mining and Ontologies (25 papers), Topic Modeling (19 papers) and Natural Language Processing Techniques (13 papers). Jari Björne is often cited by papers focused on Biomedical Text Mining and Ontologies (25 papers), Topic Modeling (19 papers) and Natural Language Processing Techniques (13 papers). Jari Björne collaborates with scholars based in Finland, United Kingdom and United States. Jari Björne's co-authors include Tapio Salakoski, Filip Ginter, Sampo Pyysalo, Juho Heimonen, Antti Airola, Tapio Pahikkala, Jorma Boberg, Jouni Järvinen, Jun’ichi Tsujii and Suwisa Kaewphan and has published in prestigious journals such as Bioinformatics, PLoS ONE and BMC Bioinformatics.

In The Last Decade

Jari Björne

31 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jari Björne Finland	18	1.5k	1.3k	126	40	31	32	1.7k
Florian Leitner Spain	13	967 0.6×	615 0.5×	116 0.9×	48 1.2×	47 1.5×	23	1.1k
Yuka Tateisi Japan	13	1.3k 0.9×	1.7k 1.3×	62 0.5×	68 1.7×	43 1.4×	41	1.9k
Xiang Yue China	15	772 0.5×	332 0.3×	514 4.1×	37 0.9×	6 0.2×	40	1.2k
Jasmin Šarić Germany	9	607 0.4×	345 0.3×	100 0.8×	46 1.1×	43 1.4×	13	727
Chris Williams United States	6	199 0.1×	152 0.1×	203 1.6×	20 0.5×	17 0.5×	12	529
Martin Romacker Germany	20	609 0.4×	624 0.5×	62 0.5×	119 3.0×	18 0.6×	42	890
Nicole Tourigny Canada	4	364 0.2×	300 0.2×	73 0.6×	87 2.2×	10 0.3×	11	526
Oleg Rokhlenko United States	14	202 0.1×	439 0.3×	42 0.3×	104 2.6×	10 0.3×	44	716
Víctor Martínez Spain	4	310 0.2×	359 0.3×	160 1.3×	50 1.3×	5 0.2×	7	676

Countries citing papers authored by Jari Björne

Since Specialization

Citations

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

Fields of papers citing papers by Jari Björne

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jari Björne

This figure shows the co-authorship network connecting the top 25 collaborators of Jari Björne. A scholar is included among the top collaborators of Jari Björne 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 Jari Björne. Jari Björne is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Laato, Samuli, Benedikt Morschheuser, Juho Hamari, & Jari Björne. (2023). AI-Assisted Learning with ChatGPT and Large Language Models: Implications for Higher Education. Trepo - Institutional Repository of Tampere University. 226–230. 32 indexed citations

Moen, Hans, Dari Alhuwail, Jari Björne, et al.. (2022). Towards Automated Screening of Literature on Artificial Intelligence in Nursing. Studies in health technology and informatics. 290. 637–640. 5 indexed citations

Collins, Charlotte, et al.. (2021). BioVerbNet: a large semantic-syntactic classification of verbs in biomedicine. Journal of Biomedical Semantics. 12(1). 12–12. 6 indexed citations

Hakala, Kai, Suwisa Kaewphan, Jari Björne, et al.. (2020). Neural Network and Random Forest Models in Protein Function Prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(3). 1772–1781. 17 indexed citations

Mehryary, Farrokh, Jari Björne, Tapio Salakoski, & Filip Ginter. (2018). Potent pairing: ensemble of long short-term memory networks and support vector machine for chemical-protein relation extraction. Database. 2018. 11 indexed citations

Mehryary, Farrokh, Kai Hakala, Suwisa Kaewphan, et al.. (2017). End-to-End System for Bacteria Habitat Extraction. 80–90. 10 indexed citations

Mehryary, Farrokh, Jari Björne, Sampo Pyysalo, Tapio Salakoski, & Filip Ginter. (2016). Deep Learning with Minimal Training Data: TurkuNLP Entry in the BioNLP Shared Task 2016. 25 indexed citations

Björne, Jari & Tapio Salakoski. (2016). UTU at SemEval-2016 Task 10: Binary Classification for Expression Detection (BCED). 925–930. 1 indexed citations

Björne, Jari. (2014). Biomedical Event Extraction with Machine Learning. Doria (University of Helsinki). 13 indexed citations

10.

Björne, Jari, Suwisa Kaewphan, & Tapio Salakoski. (2013). UTurku: Drug Named Entity Recognition and Drug-Drug Interaction Extraction Using SVM Classification and Domain Knowledge. Joint Conference on Lexical and Computational Semantics. 651–659. 62 indexed citations

11.

Björne, Jari & Tapio Salakoski. (2013). TEES 2.1: Automated Annotation Scheme Learning in the BioNLP 2013 Shared Task. Meeting of the Association for Computational Linguistics. 16–25. 75 indexed citations

12.

Landeghem, Sofie Van, Jari Björne, Chih-Hsuan Wei, et al.. (2013). Large-Scale Event Extraction from Literature with Multi-Level Gene Normalization. PLoS ONE. 8(4). e55814–e55814. 79 indexed citations

13.

Björne, Jari, Sofie Van Landeghem, Sampo Pyysalo, et al.. (2012). PubMed-Scale Event Extraction for Post-Translational Modifications, Epigenetics and Protein Structural Relations. Research Explorer (The University of Manchester). 82–90. 9 indexed citations

14.

Björne, Jari, Filip Ginter, & Tapio Salakoski. (2012). University of Turku in the BioNLP'11 Shared Task. BMC Bioinformatics. 13(S11). S4–S4. 52 indexed citations

15.

Landeghem, Sofie Van, Jari Björne, Thomas Abeel, et al.. (2012). Semantically linking molecular entities in literature through entity relationships. BMC Bioinformatics. 13(S11). S6–S6. 15 indexed citations

16.

Björne, Jari & Tapio Salakoski. (2011). Generalizing Biomedical Event Extraction. Meeting of the Association for Computational Linguistics. 183–191. 98 indexed citations

17.

Björne, Jari, Filip Ginter, Juho Heimonen, Sampo Pyysalo, & Tapio Salakoski. (2009). Learning to Extract Biological Event and Relation Graphs. DSpace repository (University of Tartu). 18–25. 5 indexed citations

18.

Airola, Antti, Sampo Pyysalo, Jari Björne, et al.. (2008). All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning. BMC Bioinformatics. 9(S11). S2–S2. 223 indexed citations

19.

Pyysalo, Sampo, Antti Airola, Juho Heimonen, et al.. (2008). Comparative analysis of five protein-protein interaction corpora. BMC Bioinformatics. 9(S3). S6–S6. 178 indexed citations

20.

Pyysalo, Sampo, Filip Ginter, Juho Heimonen, et al.. (2007). BioInfer: a corpus for information extraction in the biomedical domain. BMC Bioinformatics. 8(1). 50–50. 337 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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