Phillipp Schmidt

7 papers receiving 230 citations

Peers

Phillipp Schmidt
Comparison fields: 5 of 88
  • Biophysics 23
  • Management Science and Operations Research 24
  • Molecular Biology 125
  • Artificial Intelligence 52
  • Health Informatics 2
Replace Jon Ison with:
Jon Ison United Kingdom
Olufemi Aromolaran Nigeria
Emre Sefer Türkiye
Roy Varshavsky Israel
Steve McKeever United Kingdom
Andrea Splendiani United Kingdom
Olga Krebs Germany
Christine Froidevaux France
Bernd Rinn Switzerland
Yaning Yang China
Phillipp Schmidt relative to Jon Ison United Kingdom Jon Ison's profile →
Citations per field
00.5×1.5×1.9×
Jon Ison · 1×
Citations per year

Countries citing papers authored by Phillipp Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by Phillipp Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Phillipp Schmidt, 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 Phillipp Schmidt Line = papers co-authored together Phillipp Schmidt links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 201971
2
DataWig: Missing Value Imputation for Tables
201967
3 201765
4 199812
5 201911
6 20235
7 20233

About Phillipp Schmidt

Phillipp Schmidt is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition, having authored 7 papers that have together received 234 indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (1 paper), Ion channel regulation and function (1 paper), Effects and risks of endocrine disrupting chemicals (1 paper), Computational Drug Discovery Methods (1 paper), Statistical Methods and Bayesian Inference (1 paper), Mental Health Research Topics (1 paper), Time Series Analysis and Forecasting (1 paper) and Advanced Fluorescence Microscopy Techniques (1 paper). The work is most often cited by research in Biophysics (23 citations), Management Science and Operations Research (24 citations), Molecular Biology (125 citations), Artificial Intelligence (52 citations) and Health Informatics (2 citations). Phillipp Schmidt has collaborated with scholars based in Netherlands, Germany and United States. Frequent co-authors include Joachim Goedhart, Bas Teusink, Daan H. de Groot, Dennis Botman, Johan H. van Heerden, Frank J. Bruggeman, Niclas Nordholt, Sebastian Schelter, Dustin Lange and Felix Bießmann. Their work appears in journals such as Toxics, Journal of The Royal Society Interface, Journal of Machine Learning Research, Scientific Reports and The Journal of Membrane 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.

Explore authors with similar magnitude of impact