Lan Žagar

2.1k total citations · 1 hit paper
8 papers, 1.5k citations indexed

About

Lan Žagar is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Biophysics. According to data from OpenAlex, Lan Žagar has authored 8 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Biophysics. Recurrent topics in Lan Žagar's work include Gene expression and cancer classification (4 papers), Pluripotent Stem Cells Research (2 papers) and Single-cell and spatial transcriptomics (2 papers). Lan Žagar is often cited by papers focused on Gene expression and cancer classification (4 papers), Pluripotent Stem Cells Research (2 papers) and Single-cell and spatial transcriptomics (2 papers). Lan Žagar collaborates with scholars based in Slovenia, Italy and United States. Lan Žagar's co-authors include Blaž Zupan, Tomaž Curk, Janez Demšar, Marko Toplak, Marinka Žitnik, Lan Umek, Miha Štajdohar, Jure Žbontar, Tomaž Hočevar and Martin Možina and has published in prestigious journals such as Nature Communications, Bioinformatics and Scientific Reports.

In The Last Decade

Lan Žagar

8 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Orange: data mining toolbox in python

2013 1.2k citations Janez Demšar, Tomaž Curk et al. Journal of Machine Learning Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lan Žagar Slovenia	6	400	220	116	103	99	8	1.5k
Miha Štajdohar Slovenia	5	323 0.8×	209 0.9×	138 1.2×	98 1.0×	99 1.0×	10	1.4k
Marko Toplak Slovenia	8	337 0.8×	223 1.0×	135 1.2×	116 1.1×	100 1.0×	12	1.6k
Martin Možina Slovenia	15	328 0.8×	376 1.7×	103 0.9×	100 1.0×	120 1.2×	41	1.9k
Tomaž Hočevar Slovenia	4	305 0.8×	268 1.2×	90 0.8×	87 0.8×	103 1.0×	5	1.4k
Ernst C. Wit Netherlands	25	1.0k 2.6×	281 1.3×	90 0.8×	111 1.1×	42 0.4×	136	2.7k
Jure Žbontar United States	4	234 0.6×	217 1.0×	147 1.3×	85 0.8×	98 1.0×	6	1.4k
Jake Lever Canada	13	539 1.3×	328 1.5×	153 1.3×	122 1.2×	47 0.5×	22	2.1k
Chao Sima United States	21	907 2.3×	286 1.3×	111 1.0×	43 0.4×	52 0.5×	53	1.9k
Jing Xu China	23	547 1.4×	436 2.0×	97 0.8×	25 0.2×	111 1.1×	161	1.9k
Wenbin Liu China	27	828 2.1×	536 2.4×	122 1.1×	37 0.4×	36 0.4×	147	2.4k

Countries citing papers authored by Lan Žagar

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Lan Žagar

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Kuzman, Drago, et al.. (2021). Long-term stability predictions of therapeutic monoclonal antibodies in solution using Arrhenius-based kinetics. Scientific Reports. 11(1). 20534–20534. 56 indexed citations

2.

Stražar, Martin, Ajda Pretnar Žagar, Janez Demšar, et al.. (2019). Democratized image analytics by visual programming through integration of deep models and small-scale machine learning. Nature Communications. 10(1). 4551–4551. 61 indexed citations

3.

Stražar, Martin, Lan Žagar, Janez Demšar, et al.. (2019). scOrange—a tool for hands-on training of concepts from single-cell data analytics. Bioinformatics. 35(14). i4–i12. 7 indexed citations

4.

Demšar, Janez, Tomaž Curk, Tomaž Hočevar, et al.. (2013). Orange: data mining toolbox in python. Journal of Machine Learning Research. 14(1). 2349–2353. 1239 indexed citations breakdown →

5.

Mulas, Francesca, Lan Žagar, Blaž Zupan, & Riccardo Bellazzi. (2012). Supporting Regenerative Medicine by Integrative Dimensionality Reduction. Methods of Information in Medicine. 51(4). 341–347. 5 indexed citations

6.

Mulas, Francesca, Lucia Sacchi, Lan Žagar, et al.. (2012). Knowledge-based bioinformatics for the study of mammalian oocytes. The International Journal of Developmental Biology. 56(10-11-12). 859–866. 1 indexed citations

7.

Žagar, Lan, Francesca Mulas, Silvia Garagna, et al.. (2011). Stage prediction of embryonic stem cell differentiation from genome-wide expression data. Bioinformatics. 27(18). 2546–2553. 15 indexed citations

8.

Parikh, Anup, Edward Roshan Miranda, Mariko Katoh‐Kurasawa, et al.. (2010). Conserved developmental transcriptomes in evolutionarily divergent species. Genome biology. 11(3). R35–R35. 139 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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