Andreas Tillmar

2.5k total citations
51 papers, 1.2k citations indexed

About

Andreas Tillmar is a scholar working on Genetics, Molecular Biology and Ecology. According to data from OpenAlex, Andreas Tillmar has authored 51 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Genetics, 29 papers in Molecular Biology and 9 papers in Ecology. Recurrent topics in Andreas Tillmar's work include Forensic and Genetic Research (37 papers), Genetic Associations and Epidemiology (21 papers) and Molecular Biology Techniques and Applications (21 papers). Andreas Tillmar is often cited by papers focused on Forensic and Genetic Research (37 papers), Genetic Associations and Epidemiology (21 papers) and Molecular Biology Techniques and Applications (21 papers). Andreas Tillmar collaborates with scholars based in Sweden, Norway and United States. Andreas Tillmar's co-authors include Daniel Kling, Thore Egeland, Christopher Phillips, Gunilla Holmlund, Petter Mostad, Debbie Kennett, Jenny Welander, Raed Samara, Bertil Lindblom and Kimberly Sturk‐Andreaggi and has published in prestigious journals such as PLoS ONE, Analytical Biochemistry and BMC Bioinformatics.

In The Last Decade

Andreas Tillmar

46 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andreas Tillmar Sweden 20 1.0k 663 202 132 52 51 1.2k
Jianye Ge United States 22 1.1k 1.1× 869 1.3× 205 1.0× 148 1.1× 29 0.6× 69 1.3k
Arwin Ralf Netherlands 19 952 1.0× 744 1.1× 148 0.7× 179 1.4× 16 0.3× 30 1.2k
Lori K. Hennessy United States 17 819 0.8× 802 1.2× 248 1.2× 105 0.8× 7 0.1× 27 1.1k
Hwan Young Lee South Korea 25 1.1k 1.1× 1.3k 2.0× 167 0.8× 229 1.7× 17 0.3× 75 1.7k
Daniel Kling Norway 12 583 0.6× 317 0.5× 69 0.3× 91 0.7× 31 0.6× 32 660
Athina Vidaki Netherlands 16 431 0.4× 687 1.0× 92 0.5× 85 0.6× 27 0.5× 27 857
Cydne Holt United States 17 666 0.7× 732 1.1× 227 1.1× 63 0.5× 10 0.2× 31 1.0k
Rebecca S. Just United States 19 945 0.9× 922 1.4× 235 1.2× 172 1.3× 8 0.2× 40 1.2k
Rixun Fang United States 10 615 0.6× 469 0.7× 119 0.6× 44 0.3× 19 0.4× 15 747
Carey Davis United States 11 575 0.6× 591 0.9× 207 1.0× 57 0.4× 9 0.2× 16 735

Countries citing papers authored by Andreas Tillmar

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Tillmar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Tillmar

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Tillmar. A scholar is included among the top collaborators of Andreas Tillmar 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 Andreas Tillmar. Andreas Tillmar 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.
Kling, Daniel, et al.. (2025). Forensic investigative genetic genealogy using genotypes generated or imputed from transcriptomes. Forensic Science International Genetics. 78. 103277–103277.
2.
Parsons, Thomas J., Andreas Tillmar, Mayra Eduardoff, et al.. (2025). Inter-platform evaluation of the MPSplex large-scale tri-allelic SNP panel for forensic identification. Forensic Science International Genetics. 77. 103233–103233.
3.
Tillmar, Andreas & Daniel Kling. (2025). Comparative Study of Statistical Approaches and SNP Panels to Infer Distant Relationships in Forensic Genetics. Genes. 16(2). 114–114. 5 indexed citations
4.
Tillmar, Andreas & Daniel Kling. (2024). SNP Genotype Imputation in Forensics—A Performance Study. Genes. 15(11). 1386–1386.
5.
Jansson, Linda, Siri Fagerholm, Arvid H. Gynnå, et al.. (2024). Assessment of DNA quality for whole genome library preparation. Analytical Biochemistry. 695. 115636–115636. 4 indexed citations
6.
Kling, Daniel, Petter Mostad, & Andreas Tillmar. (2024). FamLink2 – A comprehensive tool for likelihood computations in pedigrees analyses involving linked DNA markers accounting for genotype uncertainties. Forensic Science International Genetics. 74. 103150–103150. 2 indexed citations
7.
8.
Mostad, Petter, Andreas Tillmar, & Daniel Kling. (2023). Improved computations for relationship inference using low-coverage sequencing data. BMC Bioinformatics. 24(1). 90–90. 8 indexed citations
9.
10.
Tillmar, Andreas, et al.. (2021). Getting the conclusive lead with investigative genetic genealogy – A successful case study of a 16 year old double murder in Sweden. Forensic Science International Genetics. 53. 102525–102525. 47 indexed citations
11.
Kling, Daniel, Christopher Phillips, Debbie Kennett, & Andreas Tillmar. (2021). Investigative genetic genealogy: Current methods, knowledge and practice. Forensic Science International Genetics. 52. 102474–102474. 103 indexed citations
12.
Tillmar, Andreas, et al.. (2021). Evaluation of microhaplotypes in forensic kinship analysis from a Swedish population perspective. International Journal of Legal Medicine. 135(4). 1151–1160. 24 indexed citations
13.
Tillmar, Andreas, et al.. (2020). Whole-genome sequencing of human remains to enable genealogy DNA database searches – A case report. Forensic Science International Genetics. 46. 102233–102233. 47 indexed citations
14.
Tillmar, Andreas, et al.. (2018). DNA identification of compromised samples with massive parallel sequencing. Forensic Sciences Research. 4(4). 331–336. 15 indexed citations
15.
Tillmar, Andreas, Daniel Kling, John M. Butler, et al.. (2017). DNA Commission of the International Society for Forensic Genetics (ISFG): Guidelines on the use of X-STRs in kinship analysis. Forensic Science International Genetics. 29. 269–275. 61 indexed citations
16.
Samara, Raed, et al.. (2016). A SNP panel for identity and kinship testing using massive parallel sequencing. International Journal of Legal Medicine. 130(4). 905–914. 56 indexed citations
17.
Kling, Daniel, et al.. (2015). FamLinkX – implementation of a general model for likelihood computations for X-chromosomal marker data. Forensic Science International Genetics. 17. 1–7. 38 indexed citations
18.
Kling, Daniel, Andreas Tillmar, Thore Egeland, & Petter Mostad. (2014). A general model for likelihood computations of genetic marker data accounting for linkage, linkage disequilibrium, and mutations. International Journal of Legal Medicine. 129(5). 943–954. 25 indexed citations
19.
Kling, Daniel, Andreas Tillmar, & Thore Egeland. (2014). Familias 3 – Extensions and new functionality. Forensic Science International Genetics. 13. 121–127. 150 indexed citations
20.
Tillmar, Andreas, et al.. (2008). Analysis of linkage and linkage disequilibrium for eight X-STR markers. Forensic Science International Genetics. 3(1). 37–41. 42 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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