Max Käller

12.6k total citations · 1 hit paper
31 papers, 5.0k citations indexed

About

Max Käller is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Max Käller has authored 31 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 7 papers in Genetics and 4 papers in Plant Science. Recurrent topics in Max Käller's work include Genomics and Phylogenetic Studies (8 papers), RNA and protein synthesis mechanisms (5 papers) and Single-cell and spatial transcriptomics (4 papers). Max Käller is often cited by papers focused on Genomics and Phylogenetic Studies (8 papers), RNA and protein synthesis mechanisms (5 papers) and Single-cell and spatial transcriptomics (4 papers). Max Käller collaborates with scholars based in Sweden, United States and Germany. Max Käller's co-authors include Sverker Lundin, Philip Ewels, Måns Magnusson, Joakim Lundeberg, Afshin Ahmadian, Francesco Vezzi, Henrik Stranneheim, Lars Arvestad, Remi‐André Olsen and Björn Andersson and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Max Käller

30 papers receiving 5.0k citations

Hit Papers

MultiQC: summarize analysis results for multiple tools an... 2016 2026 2019 2022 2016 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Max Käller Sweden 12 2.6k 746 693 679 474 31 5.0k
Måns Magnusson Sweden 6 2.4k 0.9× 713 1.0× 636 0.9× 640 0.9× 454 1.0× 7 4.7k
Philip Ewels Sweden 12 3.3k 1.3× 860 1.2× 855 1.2× 704 1.0× 524 1.1× 20 5.9k
Jian Ye China 15 3.3k 1.3× 826 1.1× 1.0k 1.5× 807 1.2× 833 1.8× 37 6.6k
Aleš Tichopád Czechia 19 3.9k 1.5× 688 0.9× 655 0.9× 573 0.8× 376 0.8× 57 6.1k
Dave Bouvier United States 6 2.7k 1.0× 555 0.7× 658 0.9× 624 0.9× 320 0.7× 9 4.5k
Patrick J. Biggs New Zealand 31 2.6k 1.0× 967 1.3× 564 0.8× 566 0.8× 287 0.6× 162 5.0k
Fernando García-Alcalde Spain 13 2.1k 0.8× 686 0.9× 682 1.0× 350 0.5× 334 0.7× 24 3.8k
Marius van den Beek France 12 2.6k 1.0× 469 0.6× 664 1.0× 559 0.8× 318 0.7× 21 4.2k
Nives Škunca Switzerland 12 3.1k 1.2× 772 1.0× 1.2k 1.7× 504 0.7× 401 0.8× 15 5.3k

Countries citing papers authored by Max Käller

Since Specialization
Citations

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

Fields of papers citing papers by Max Käller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Käller

This figure shows the co-authorship network connecting the top 25 collaborators of Max Käller. A scholar is included among the top collaborators of Max Käller based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Max Käller. Max Käller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mezger, Anja, Max Käller, Claudia Fredolini, et al.. (2026). Exploration of immune phenotypes in self-sampling citizens. iScience. 29(2). 114611–114611.
2.
Eisfeldt, Jesper, Maria Pettersson, Francesco Vezzi, et al.. (2019). Comprehensive structural variation genome map of individuals carrying complex chromosomal rearrangements. PLoS Genetics. 15(2). e1007858–e1007858. 30 indexed citations
3.
Tiukova, Ievgeniia, Mats E. Pettersson, Marc P. Hoeppner, et al.. (2019). Chromosomal genome assembly of the ethanol production strain CBS 11270 indicates a highly dynamic genome structure in the yeast species Brettanomyces bruxellensis. PLoS ONE. 14(5). e0215077–e0215077. 8 indexed citations
4.
Käller, Max, et al.. (2019). High throughput barcoding method for genome-scale phasing. Scientific Reports. 9(1). 18116–18116. 9 indexed citations
5.
García, Miguel, Szilveszter Juhos, Maria Larsson, et al.. (2018). CAW - Cancer Analysis Workflow to process normal/tumor WGS data. European Journal of Human Genetics. 26. 702–702. 1 indexed citations
6.
Hu, Yue, Nelson Ndegwa, Johannes Alneberg, et al.. (2018). Stationary and portable sequencing-based approaches for tracing wastewater contamination in urban stormwater systems. Scientific Reports. 8(1). 11907–11907. 23 indexed citations
7.
Juhos, Szilveszter, et al.. (2018). Comprehensive haplotyping of the HLA gene family using nanopore sequencing. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1 indexed citations
8.
Engström, Karin, Tomasz K. Wojdacz, Francesco Marabita, et al.. (2016). Transcriptomics and methylomics of CD4-positive T cells in arsenic-exposed women. Archives of Toxicology. 91(5). 2067–2078. 26 indexed citations
10.
Prezza, Nicola, Francesco Vezzi, Max Käller, & Alberto Policriti. (2016). Fast, accurate, and lightweight analysis of BS-treated reads with ERNE 2. BMC Bioinformatics. 17(S4). 69–69. 4 indexed citations
11.
Lundin, Sverker, Anders Jemt, Erik Pettersson, et al.. (2015). Endonuclease Specificity and Sequence Dependence of Type IIS Restriction Enzymes. PLoS ONE. 10(1). e0117059–e0117059. 9 indexed citations
12.
Grünewald, Johan, Ylva Kaiser, Mahyar Ostadkarampour, et al.. (2015). T-cell receptor–HLA-DRB1 associations suggest specific antigens in pulmonary sarcoidosis. European Respiratory Journal. 47(3). 898–909. 55 indexed citations
13.
Gréen, Henrik, Cédric Oréar, Pierre Validire, et al.. (2014). Assessment of Whole Genome Amplification for Sequence Capture and Massively Parallel Sequencing. PLoS ONE. 9(1). e84785–e84785. 9 indexed citations
14.
Gyarmati, Péter, et al.. (2013). Chemical fragmentation for massively parallel sequencing library preparation. Journal of Biotechnology. 168(1). 95–100. 4 indexed citations
15.
Avesson, Lotta, et al.. (2013). Identification and Verification of microRNAs by High-Throughput Sequencing. Methods in molecular biology. 983. 125–138. 6 indexed citations
16.
Pettersson, Erik, Patrik L. Ståhl, Hovsep Mahdessian, et al.. (2009). Visual DNA as a diagnostic tool. Electrophoresis. 30(21). 3691–3695. 4 indexed citations
17.
Käller, Max, Joakim Lundeberg, & Afshin Ahmadian. (2006). Arrayed identification of DNA signatures. Expert Review of Molecular Diagnostics. 7(1). 65–76. 24 indexed citations
18.
Käller, Max, Emilie Hultin, Kristina Holmberg, et al.. (2006). Comparison of PrASE and Pyrosequencing for SNP Genotyping. BMC Genomics. 7(1). 291–291. 6 indexed citations
19.
Käller, Max, Emilie Hultin, Biying Zheng, et al.. (2005). Tag-array based HPV genotyping by competitive hybridization and extension. Journal of Virological Methods. 129(2). 102–112. 5 indexed citations
20.
Käller, Max, Afshin Ahmadian, & Joakim Lundeberg. (2004). Microarray-based AMASE as a novel approach for mutation detection. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 554(1-2). 77–88. 9 indexed citations

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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