Inga Schmalenbach

985 total citations
8 papers, 724 citations indexed

About

Inga Schmalenbach is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Inga Schmalenbach has authored 8 papers receiving a total of 724 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Plant Science, 6 papers in Genetics and 2 papers in Molecular Biology. Recurrent topics in Inga Schmalenbach's work include Genetic Mapping and Diversity in Plants and Animals (6 papers), Wheat and Barley Genetics and Pathology (5 papers) and Plant Disease Resistance and Genetics (4 papers). Inga Schmalenbach is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (6 papers), Wheat and Barley Genetics and Pathology (5 papers) and Plant Disease Resistance and Genetics (4 papers). Inga Schmalenbach collaborates with scholars based in Germany, France and South Korea. Inga Schmalenbach's co-authors include Klaus Pillen, Jens Léon, José M. Jiménez‐Gómez, Soon Ju Park, Lei Zhang, Ke Jiang, Niels A. Müller, Ryosuke Hayama, Joyce Van Eck and Zachary B. Lippman and has published in prestigious journals such as Nature Genetics, Plant Cell & Environment and Theoretical and Applied Genetics.

In The Last Decade

Inga Schmalenbach

8 papers receiving 708 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Inga Schmalenbach Germany	8	668	291	265	58	24	8	724
Elise J. Tucker Australia	15	927 1.4×	642 2.2×	127 0.5×	47 0.8×	24 1.0×	17	1.0k
Aurore Vernet France	8	317 0.5×	232 0.8×	53 0.2×	11 0.2×	22 0.9×	12	450
Woo‐Jong Hong South Korea	18	656 1.0×	487 1.7×	71 0.3×	16 0.3×	16 0.7×	58	789
Darlene L. Sanchez United States	15	1.3k 2.0×	124 0.4×	418 1.6×	24 0.4×	6 0.3×	30	1.4k
Alvaro M. Pamplona Philippines	9	1000 1.5×	83 0.3×	316 1.2×	10 0.2×	20 0.8×	12	1.0k
Kerrie Ramm Australia	10	678 1.0×	347 1.2×	199 0.8×	110 1.9×	11 0.5×	14	728
K. V. Prabhu India	13	613 0.9×	149 0.5×	227 0.9×	66 1.1×	11 0.5×	36	695
Peter Pagh Denmark	3	226 0.3×	85 0.3×	45 0.2×	21 0.4×	17 0.7×	4	271
Haibin Wei China	12	668 1.0×	205 0.7×	216 0.8×	29 0.5×	8 0.3×	19	745
Serik Eliby Australia	10	571 0.9×	357 1.2×	41 0.2×	44 0.8×	10 0.4×	16	654

Countries citing papers authored by Inga Schmalenbach

Since Specialization

Citations

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

Fields of papers citing papers by Inga Schmalenbach

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Inga Schmalenbach

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

All Works

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8 of 8 papers shown

Soyk, Sebastian, Niels A. Müller, Soon Ju Park, et al.. (2016). Variation in the flowering gene SELF PRUNING 5G promotes day-neutrality and early yield in tomato. Nature Genetics. 49(1). 162–168. 304 indexed citations

Schmalenbach, Inga, Lei Zhang, Małgorzata Ryngajłło, & José M. Jiménez‐Gómez. (2014). Functional analysis of the Landsberg erecta allele of FRIGIDA. BMC Plant Biology. 14(1). 218–218. 21 indexed citations

Schmalenbach, Inga, et al.. (2011). High-Resolution Genotyping of Wild Barley Introgression Lines and Fine-Mapping of the Threshability Locus thresh-1 Using the Illumina GoldenGate Assay. G3 Genes Genomes Genetics. 1(3). 187–196. 67 indexed citations

Wang, Gongwei, Inga Schmalenbach, Maria von Korff, et al.. (2010). Association of barley photoperiod and vernalization genes with QTLs for flowering time and agronomic traits in a BC2DH population and a set of wild barley introgression lines. Theoretical and Applied Genetics. 120(8). 1559–1574. 98 indexed citations

Tisné, Sébastien, Inga Schmalenbach, Matthieu Reymond, et al.. (2010). Keep on growing under drought: genetic and developmental bases of the response of rosette area using a recombinant inbred line population. Plant Cell & Environment. 33(11). 1875–1887. 46 indexed citations

Schmalenbach, Inga & Klaus Pillen. (2009). Detection and verification of malting quality QTLs using wild barley introgression lines. Theoretical and Applied Genetics. 118(8). 1411–1427. 45 indexed citations

Schmalenbach, Inga, Niklas Körber, & Klaus Pillen. (2008). Selecting a set of wild barley introgression lines and verification of QTL effects for resistance to powdery mildew and leaf rust. Theoretical and Applied Genetics. 117(7). 1093–1106. 78 indexed citations

Schmalenbach, Inga, Jens Léon, & Klaus Pillen. (2008). Identification and verification of QTLs for agronomic traits using wild barley introgression lines. Theoretical and Applied Genetics. 118(3). 483–497. 65 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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