Daniel Müllner
Impact in
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- Data Management and Algorithms
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- Genomics and Phylogenetic Studies
- Genomics and Chromatin Dynamics
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- RNA Research and Splicing
Papers in ⓘ
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- Algebraic structures and combinatorial models 1
- Geometric and Algebraic Topology 1
- Co-authors
- Elisa Dultz (1 shared paper)Christopher Loewen (1 shared paper)Mareike Herzog (1 shared paper)Karsten Weis (1 shared paper)Harianto Tjong (1 shared paper)Frank Alber (1 shared paper)Barry P. Young (1 shared paper)
- Journals
- The Journal of Cell Biology (1 paper)Journal of Statistical Software (1 paper)Algebraic & Geometric Topology (1 paper)
- Partner nations
- United StatesSwitzerlandCanada
In The Last Decade
Daniel Müllner
4 papers receiving 432 citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Signal Processing 31
- Molecular Biology 154
- Biophysics 12
- Artificial Intelligence 63
- Computer Vision and Pattern Recognition 38
Countries citing papers authored by Daniel Müllner
This map shows the geographic impact of Daniel Müllner'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 Daniel Müllner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Müllner more than expected).
Fields of papers citing papers by Daniel Müllner
This network shows the impact of papers produced by Daniel Müllner. 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 Daniel Müllner. The network helps show where Daniel Müllner may publish in the future.
Co-authors
The 7 scholars most cited alongside Daniel Müllner, 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 | fastcluster: Fast Hierarchical, Agglomerative Clustering Routines forRandPython Hit paper breakdown → | 2013 | 410 |
| 2 | 2016 | 23 | |
| 3 | 2009 | 6 | |
| 4 | Fast Hierarchical Clustering Routines for R and Python | 2015 | 4 |
About Daniel Müllner
Daniel Müllner is a scholar working on Geometry and Topology, Mathematical Physics, Signal Processing, Artificial Intelligence and Molecular Biology, having authored 4 papers that have together received 443 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (2 papers), Algebraic structures and combinatorial models (1 paper), Algorithms and Data Compression (1 paper), Data Management and Algorithms (1 paper), RNA Research and Splicing (1 paper), Ubiquitin and proteasome pathways (1 paper), Geometric and Algebraic Topology (1 paper) and Genomics and Chromatin Dynamics (1 paper). The work is most often cited by research in Signal Processing (31 citations), Molecular Biology (154 citations), Biophysics (12 citations), Artificial Intelligence (63 citations) and Computer Vision and Pattern Recognition (38 citations). Daniel Müllner has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Elisa Dultz, Christopher Loewen, Mareike Herzog, Karsten Weis, Harianto Tjong, Frank Alber and Barry P. Young. Their work appears in journals such as The Journal of Cell Biology, Journal of Statistical Software and Algebraic & Geometric Topology.
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.