Armin O. Schmitt

2.9k total citations
100 papers, 2.0k citations indexed

About

Armin O. Schmitt is a scholar working on Genetics, Molecular Biology and Plant Science. According to data from OpenAlex, Armin O. Schmitt has authored 100 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Genetics, 40 papers in Molecular Biology and 18 papers in Plant Science. Recurrent topics in Armin O. Schmitt's work include Genetic and phenotypic traits in livestock (24 papers), Genetic Mapping and Diversity in Plants and Animals (21 papers) and RNA and protein synthesis mechanisms (13 papers). Armin O. Schmitt is often cited by papers focused on Genetic and phenotypic traits in livestock (24 papers), Genetic Mapping and Diversity in Plants and Animals (21 papers) and RNA and protein synthesis mechanisms (13 papers). Armin O. Schmitt collaborates with scholars based in Germany, Italy and United States. Armin O. Schmitt's co-authors include Hanspeter Herzel, W. Ebeling, André Rosenthal, Christian Piepenbrock, Péter Adorján, Mehmet Gültaş, Thomas Hildmann, Jörn Lewin, Gudrun A. Brockmann and Christian Pilarsky and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Nature Genetics.

In The Last Decade

Armin O. Schmitt

92 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Armin O. Schmitt Germany	23	994	369	238	159	131	100	2.0k
Jing Liang China	26	2.4k 2.4×	354 1.0×	525 2.2×	299 1.9×	184 1.4×	53	4.0k
Sébastien Dejean France	25	1.5k 1.5×	420 1.1×	211 0.9×	82 0.5×	35 0.3×	86	3.0k
Ying Zhang China	32	1.9k 1.9×	247 0.7×	434 1.8×	89 0.6×	122 0.9×	206	3.8k
Honglei Wang China	28	819 0.8×	344 0.9×	347 1.5×	52 0.3×	43 0.3×	115	2.1k
Solve Sæbø Norway	22	528 0.5×	373 1.0×	233 1.0×	133 0.8×	101 0.8×	56	3.0k
Deepayan Sarkar India	16	1.2k 1.3×	318 0.9×	320 1.3×	29 0.2×	240 1.8×	42	3.2k
Hong Yu China	29	1.9k 1.9×	200 0.5×	270 1.1×	31 0.2×	142 1.1×	119	3.3k
Tal Galili Israel	13	620 0.6×	228 0.6×	363 1.5×	25 0.2×	97 0.7×	24	2.0k
Ryota Suzuki Japan	6	743 0.7×	247 0.7×	308 1.3×	25 0.2×	91 0.7×	15	1.9k

Countries citing papers authored by Armin O. Schmitt

Since Specialization

Citations

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

Fields of papers citing papers by Armin O. Schmitt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Armin O. Schmitt. 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 Armin O. Schmitt. The network helps show where Armin O. Schmitt may publish in the future.

Co-authorship network of co-authors of Armin O. Schmitt

This figure shows the co-authorship network connecting the top 25 collaborators of Armin O. Schmitt. A scholar is included among the top collaborators of Armin O. Schmitt 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 Armin O. Schmitt. Armin O. Schmitt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Gültaş, Mehmet, et al.. (2025). optRF: Optimising random forest stability by determining the optimal number of trees. BMC Bioinformatics. 26(1). 95–95. 2 indexed citations

Heinrich, Felix, et al.. (2025). Genomic analysis of three medieval parchments from German monasteries. Scientific Reports. 15(1). 3156–3156.

Gültaş, Mehmet, et al.. (2024). Deep learning the cis-regulatory code for gene expression in selected model plants. Nature Communications. 15(1). 3488–3488. 26 indexed citations

Schmitt, Armin O., et al.. (2023). Estimates of Water Consumption of Growing Pigs under Practical Conditions Based on Climate and Performance Data. Animals. 13(9). 1547–1547.

Reißmann, Monika, et al.. (2023). Identification of Differentially Expressed Genes after Endurance Runs in Karbadian Horses to Determine Candidates for Stress Indicators and Performance Capability. Genes. 14(11). 1982–1982. 2 indexed citations

Bertram, Hendrik, et al.. (2022). Comparative Investigation of Gene Regulatory Processes Underlying Avian Influenza Viruses in Chicken and Duck. Biology. 11(2). 219–219. 5 indexed citations

Schmitt, Armin O., et al.. (2022). Deciphering Pleiotropic Signatures of Regulatory SNPs in Zea mays L. Using Multi-Omics Data and Machine Learning Algorithms. International Journal of Molecular Sciences. 23(9). 5121–5121. 4 indexed citations

Heinrich, Felix, et al.. (2021). MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes. Biology. 10(9). 921–921. 3 indexed citations

Bertram, Hendrik, et al.. (2021). In Silico Identification of the Complex Interplay between Regulatory SNPs, Transcription Factors, and Their Related Genes in Brassica napus L. Using Multi-Omics Data. International Journal of Molecular Sciences. 22(2). 789–789. 12 indexed citations

10.

Schmitt, Armin O., Jens Tetens, Bertram Brenig, et al.. (2021). In Silico Prediction of Transcription Factor Collaborations Underlying Phenotypic Sexual Dimorphism in Zebrafish (Danio rerio). Genes. 12(6). 873–873.

11.

Rajavel, Abirami, et al.. (2021). Unravelling the Complex Interplay of Transcription Factors Orchestrating Seed Oil Content in Brassica napus L.. International Journal of Molecular Sciences. 22(3). 1033–1033. 12 indexed citations

12.

Schmitt, Armin O., et al.. (2020). Animal Welfare Assessment of Fattening Pigs: A Case Study on Sample Validity. Animals. 10(3). 389–389. 3 indexed citations

13.

Khan, Muhammad Sajjad, et al.. (2020). Survey data to identify the selection criteria used by breeders of four strains of Pakistani beetal goats. SHILAP Revista de lepidopterología. 32. 106051–106051. 2 indexed citations

14.

Hummel, Jürgen, et al.. (2020). An Innovative Concept for a Multivariate Plausibility Assessment of Simultaneously Recorded Data. Animals. 10(8). 1412–1412. 4 indexed citations

15.

Koch, Alexandra, et al.. (2020). Acceptance and Feasibility of a Guideline for the Animal Welfare Assessment of Fattening Pigs from Farmers’ Point of View. Animals. 10(4). 711–711. 5 indexed citations

16.

Schmitt, Armin O., et al.. (2019). Inter- and intra-observer reliability of animal welfare indicators for the on-farm self-assessment of fattening pigs. animal. 13(8). 1712–1720. 18 indexed citations

17.

Bartho, J.D., Dom Bellini, Jochen Wuerges, et al.. (2017). The crystal structure of Erwinia amylovora AmyR, a member of the YbjN protein family, shows similarity to type III secretion chaperones but suggests different cellular functions. PLoS ONE. 12(4). e0176049–e0176049. 3 indexed citations

18.

Borruso, Luigimaria, et al.. (2017). Conservation of Erwinia amylovora pathogenicity-relevant genes among Erwinia genomes. Archives of Microbiology. 199(10). 1335–1344. 22 indexed citations

19.

Schmitt, Armin O. & Hanspeter Herzel. (1997). Estimating the Entropy of DNA Sequences. Journal of Theoretical Biology. 188(3). 369–377. 104 indexed citations

20.

Schmitt, Armin O., W. Ebeling, & Hanspeter Herzel. (1996). The modular structure of informational sequences. Biosystems. 37(3). 199–210. 14 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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