Tomislav Šmuc
Impact in
- Aging top 5%
- Molecular Biology top 2%
- Genomics and Phylogenetic Studies
- RNA Research and Splicing
- RNA modifications and cancer
- Bioinformatics and Genomic Networks
- Epigenetics and DNA Methylation
- RNA and protein synthesis mechanisms
Papers in
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- Computational Drug Discovery Methods 6
- Rough Sets and Fuzzy Logic 4
Tomislav Šmuc
66 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 186
- Aging 89
- Molecular Biology 2.6k
- Plant Science 1.1k
- Cancer Research 383
- Genetics 696
Countries citing papers authored by Tomislav Šmuc
This map shows the geographic impact of Tomislav Šmuc'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 Tomislav Šmuc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomislav Šmuc more than expected).
Fields of papers citing papers by Tomislav Šmuc
This network shows the impact of papers produced by Tomislav Šmuc. 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 Tomislav Šmuc. The network helps show where Tomislav Šmuc may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tomislav Šmuc, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 3 | |
| 2 | 2021 | 6 | |
| 3 | 2021 | 22 | |
| 4 | 2014 | 21 | |
| 5 | Analysis of World Bank indicators for countries with banking crises by subgroup discovery induction | 2013 | 1 |
| 6 | 2013 | 32 | |
| 7 | ECML-PKDD 2011 Discovery Challenge Overview | 2011 | 10 |
| 8 | REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms Hit paper breakdown → | 2011 | 4349 |
| 9 | 2011 | 26 | |
| 10 | 2011 | 20 | |
| 11 | 2010 | 67 | |
| 12 | 2010 | 4 | |
| 13 | 2009 | 17 | |
| 14 | 2008 | 7 | |
| 15 | 2007 | 21 | |
| 16 | 2007 | 23 | |
| 17 | Sensitivity of Differential Evolution Algorithm to Values of Control Parameters. | 2002 | 3 |
| 18 | Improving Convergence Properties of the Differential Evolution Algorithm | 2002 | 12 |
| 19 | Combining Unsupervised and Supervised Machine Learning | 2001 | 3 |
| 20 | 1998 | 0 |
About Tomislav Šmuc
Tomislav Šmuc is a scholar working on Computational Mathematics, Computational Theory and Mathematics, Information Systems, Signal Processing and Modeling and Simulation, having authored 69 papers that have together received 5.3k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (10 papers), Genomics and Phylogenetic Studies (7 papers), Computational Drug Discovery Methods (6 papers), Gene expression and cancer classification (5 papers), Bioinformatics and Genomic Networks (5 papers), Complex Systems and Time Series Analysis (5 papers), Rough Sets and Fuzzy Logic (4 papers) and Heart Rate Variability and Autonomic Control (4 papers). The work is most often cited by research in Aging (89 citations), Molecular Biology (2.6k citations), Plant Science (1.1k citations), Cancer Research (383 citations) and Genetics (696 citations). Tomislav Šmuc has collaborated with scholars based in Croatia, Slovenia and Spain. Frequent co-authors include Fran Supek, Nives Škunca, Matko Bošnjak, Marijeta Kralj, Anita Kriško, Nino Antulov-Fantulin, Vedrana Vidulin, Sašo Džeroski, Marko Marjanović and Mile Šikić. Their work appears in journals such as Molecules, Scientific Reports, PLoS ONE, Bioinformatics and IEEE Access.
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.