Silke Janitza

24 papers receiving 1.6k citations

Silke Janitza's Hit Papers

Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics 2012 · 618 citations
6180+4+9Years since publication200400600

Peers

Silke Janitza
Comparison fields: 5 of 204
  • Ecological Modeling 53
  • Statistics and Probability 97
  • Health Information Management 45
  • Environmental Engineering 125
  • Global and Planetary Change 162
Replace Jochen Kruppa with:
Jochen Kruppa Germany
Sara Álvarez de Andrés Spain
Jaime L. Speiser United States
Nicola L. C. Talbot United Kingdom
André Altmann United Kingdom
Miron B. Kursa Poland
Markus Neuhäuser Germany
Matthias Templ Austria
Daniel J. Stekhoven Switzerland
Gerhard Tutz Germany
Silke Janitza relative to Jochen Kruppa Germany Jochen Kruppa's profile →
Citations per field
00.5×1.5×2.3×
Jochen Kruppa · 1×
Citations per year

Countries citing papers authored by Silke Janitza

Since Specialization
Citations

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

Fields of papers citing papers by Silke Janitza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Silke Janitza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Silke Janitza Line = papers co-authored together Silke Janitza links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics
Hit paper breakdown →
2012618
2 2013193
3 2018173
4 2015169
5 2016127
6 201568
7 201859
8 201656
9 201929
10 201728
11 201419
12 201617
13 201617
14 201813
15 201513
16 201812
17 201611
18 201710
19 20139
20 20165

About Silke Janitza

Silke Janitza is a scholar working on Statistics and Probability, Artificial Intelligence, Molecular Biology, Surgery and Pulmonary and Respiratory Medicine, having authored 24 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (10 papers), Gene expression and cancer classification (4 papers), Advanced Statistical Methods and Models (3 papers), Transplantation: Methods and Outcomes (3 papers), Data Mining Algorithms and Applications (3 papers), Advanced Chemical Sensor Technologies (2 papers), Bayesian Methods and Mixture Models (2 papers) and Genetic and phenotypic traits in livestock (2 papers). The work is most often cited by research in Ecological Modeling (53 citations), Statistics and Probability (97 citations), Health Information Management (45 citations), Environmental Engineering (125 citations) and Global and Planetary Change (162 citations). Silke Janitza has collaborated with scholars based in Germany, Netherlands and Switzerland. Frequent co-authors include Anne‐Laure Boulesteix, Jochen Kruppa, Inke R. König, Roman Hornung, Carolin Strobl, Gerhard Tutz, Riccardo De Bin, Willi Sauerbrei, Heike Hölling and Thomas Weig. Their work appears in journals such as Biometrical Journal, Advances in Data Analysis and Classification, PLoS ONE, Journal of Clinical Monitoring and Computing and BMC Psychiatry.

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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