Daniel Müllner
Impact in
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- Data Management and Algorithms
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- Genomics and Phylogenetic Studies
- Gene expression and cancer classification
- Genomics and Chromatin Dynamics
- RNA Research and Splicing
- Bioinformatics and Genomic Networks
Papers in
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- Advanced Clustering Algorithms Research 2
- Algorithms and Data Compression 1
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- Genomics and Chromatin Dynamics 1
- Ubiquitin and proteasome pathways 1
- RNA Research and Splicing 1
- Co-authors
- Mareike Herzog (1 shared paper)Frank Alber (1 shared paper)Karsten Weis (1 shared paper)Christopher Loewen (1 shared paper)Elisa Dultz (1 shared paper)Harianto Tjong (1 shared paper)Barry P. Young (1 shared paper)
- Journals
- Journal of Statistical Software (1 paper)The Journal of Cell Biology (1 paper)Algebraic & Geometric Topology (1 paper)
- Partner nations
- United StatesSwitzerlandCanada
In The Last Decade
Daniel Müllner
4 papers receiving 453 citations
Daniel Müllner's Hit Papers
Peers
Comparison fields: 5 of 138
- Signal Processing 33
- Molecular Biology 140
- Biophysics 12
- Structural Biology 3
- Artificial Intelligence 68
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 | 428 |
| 2 | 2016 | 24 | |
| 3 | 2009 | 7 | |
| 4 | Fast Hierarchical Clustering Routines for R and Python | 2015 | 4 |
About Daniel Müllner
Daniel Müllner is a scholar working on Artificial Intelligence, Molecular Biology, Mathematical Physics, Geometry and Topology and Signal Processing, having authored 4 papers that have together received 463 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (2 papers), Genomics and Chromatin Dynamics (1 paper), Ubiquitin and proteasome pathways (1 paper), Geometric and Algebraic Topology (1 paper), Data Management and Algorithms (1 paper), Algorithms and Data Compression (1 paper), RNA Research and Splicing (1 paper) and Homotopy and Cohomology in Algebraic Topology (1 paper). The work is most often cited by research in Signal Processing (33 citations), Molecular Biology (140 citations), Biophysics (12 citations), Structural Biology (3 citations) and Artificial Intelligence (68 citations). Daniel Müllner has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Mareike Herzog, Frank Alber, Karsten Weis, Christopher Loewen, Elisa Dultz, Harianto Tjong and Barry P. Young. Their work appears in journals such as Journal of Statistical Software, The Journal of Cell Biology 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.