Josef Špidlen
Impact in
- Biophysics top 1%
- Cell Image Analysis Techniques
-
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
Papers in
- Biophysics 17
- Cell Image Analysis Techniques 16
- Advanced Fluorescence Microscopy Techniques 3
-
- Electronic Health Records Systems 4
- Co-authors
- Ryan R. BrinkmanRichard HalpertJennifer Snyder‐CappioneAnna C. BelkinaRina AnnoRobert GentlemanPerry HaalandNolwenn Le Meur
- Journals
- Cytometry Part A (8 papers)Cytometry Part B Clinical Cytometry (3 papers)International Journal of Medical Informatics (2 papers)Nature Communications (2 papers)BMC Bioinformatics (2 papers)
- Partner nations
- CanadaUnited StatesCzechia
In The Last Decade
Josef Špidlen
28 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Biophysics 214
- Immunology 207
- Molecular Biology 603
- Health Information Management 30
- Artificial Intelligence 124
Countries citing papers authored by Josef Špidlen
This map shows the geographic impact of Josef Špidlen'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 Josef Špidlen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josef Špidlen more than expected).
Fields of papers citing papers by Josef Špidlen
This network shows the impact of papers produced by Josef Špidlen. 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 Josef Špidlen. The network helps show where Josef Špidlen may publish in the future.
Co-authors
The 25 scholars most cited alongside Josef Špidlen, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2021 | 23 | |
| 4 | 2020 | 1 | |
| 5 | 2020 | 9 | |
| 6 | Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets Hit paper breakdown → | 2019 | 374 |
| 7 | 2017 | 10 | |
| 8 | 2016 | 7 | |
| 9 | 2013 | 13 | |
| 10 | 2013 | 73 | |
| 11 | 2012 | 3 | |
| 12 | 2011 | 9 | |
| 13 | 2009 | 4 | |
| 14 | 2009 | 393 | |
| 15 | 2008 | 29 | |
| 16 | 2006 | 21 | |
| 17 | 2005 | 6 | |
| 18 | 2004 | 16 | |
| 19 | MUDRLite - health record tailored to your particular needs. | 2004 | 6 |
| 20 | Scientific papers: the internet in connecting electronics health record mobile clients | 2002 | 1 |
About Josef Špidlen
Josef Špidlen is a scholar working on Biophysics, Health Information Management, Information Systems and Management, Molecular Biology and Artificial Intelligence, having authored 31 papers that have together received 1.1k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (21 papers), Cell Image Analysis Techniques (16 papers), Gene expression and cancer classification (11 papers), Biomedical Text Mining and Ontologies (5 papers), Scientific Computing and Data Management (5 papers), Electronic Health Records Systems (4 papers), Microfluidic and Bio-sensing Technologies (3 papers) and Advanced Fluorescence Microscopy Techniques (3 papers). The work is most often cited by research in Biophysics (214 citations), Immunology (207 citations), Molecular Biology (603 citations), Health Information Management (30 citations) and Artificial Intelligence (124 citations). Josef Špidlen has collaborated with scholars based in Canada, United States and Czechia. Frequent co-authors include Ryan R. Brinkman, Richard Halpert, Jennifer Snyder‐Cappione, Anna C. Belkina, Rina Anno, Robert Gentleman, Perry Haaland, Nolwenn Le Meur, Florian Hahne and Byron Ellis. Their work appears in journals such as Cytometry Part A, Cytometry Part B Clinical Cytometry, International Journal of Medical Informatics, Nature Communications and BMC Bioinformatics.
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.