Lan Žagar
Impact in
- Biophysics top 5%
- Spectroscopy Techniques in Biomedical and Chemical Research
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses
Papers in
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- Genetics, Bioinformatics, and Biomedical Research 1
- Protein purification and stability 1
- Gene expression and cancer classification 1
- Viral Infectious Diseases and Gene Expression in Insects 1
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- Advanced Image and Video Retrieval Techniques 1
- Data Visualization and Analytics 1
- Co-authors
- Blaž Zupan (7 shared papers)Tomaž Curk (2 shared papers)Janez Demšar (3 shared papers)Marko Toplak (2 shared papers)Miha Štajdohar (1 shared paper)Tomaž Hočevar (1 shared paper)Marinka Žitnik (1 shared paper)Martin Možina (1 shared paper)
- Journals
- Bioinformatics (2 papers)Nature Communications (1 paper)Scientific Reports (1 paper)Journal of Machine Learning Research (1 paper)Genome biology (1 paper)
- Partner nations
- SloveniaItalyUnited States
In The Last Decade
Lan Žagar
8 papers receiving 1.5k citations
Lan Žagar's Hit Papers
Peers
Comparison fields: 5 of 202
- Biophysics 84
- Analytical Chemistry 72
- Artificial Intelligence 214
- Aging 11
- Computer Science Applications 34
Countries citing papers authored by Lan Žagar
This map shows the geographic impact of Lan Žagar'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 Lan Žagar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan Žagar more than expected).
Fields of papers citing papers by Lan Žagar
This network shows the impact of papers produced by Lan Žagar. 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 Lan Žagar. The network helps show where Lan Žagar may publish in the future.
Co-authors
The 25 scholars most cited alongside Lan Žagar, 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 | Orange: data mining toolbox in python Hit paper breakdown → | 2013 | 1250 |
| 2 | 2010 | 139 | |
| 3 | 2019 | 64 | |
| 4 | 2021 | 63 | |
| 5 | 2011 | 15 | |
| 6 | 2019 | 7 | |
| 7 | 2012 | 5 | |
| 8 | 2012 | 1 |
About Lan Žagar
Lan Žagar is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 8 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Physics and Python Applications (1 paper), Genetics, Bioinformatics, and Biomedical Research (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Protein purification and stability (1 paper), Gene expression and cancer classification (1 paper), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Biophysics (84 citations), Analytical Chemistry (72 citations), Artificial Intelligence (214 citations), Aging (11 citations) and Computer Science Applications (34 citations). Lan Žagar has collaborated with scholars based in Slovenia, Italy and United States. Frequent co-authors include Blaž Zupan, Tomaž Curk, Janez Demšar, Marko Toplak, Miha Štajdohar, Tomaž Hočevar, Marinka Žitnik, Martin Možina, Lan Umek and Jure Žbontar. Their work appears in journals such as Bioinformatics, Nature Communications, Scientific Reports, Journal of Machine Learning Research and Genome biology.
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.