Mario G. Rosso

1.7k total citations · 1 hit paper
11 papers, 1.4k citations indexed

About

Mario G. Rosso is a scholar working on Plant Science, Molecular Biology and Environmental Engineering. According to data from OpenAlex, Mario G. Rosso has authored 11 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Plant Science, 9 papers in Molecular Biology and 1 paper in Environmental Engineering. Recurrent topics in Mario G. Rosso's work include Chromosomal and Genetic Variations (5 papers), Plant tissue culture and regeneration (5 papers) and Plant Molecular Biology Research (4 papers). Mario G. Rosso is often cited by papers focused on Chromosomal and Genetic Variations (5 papers), Plant tissue culture and regeneration (5 papers) and Plant Molecular Biology Research (4 papers). Mario G. Rosso collaborates with scholars based in Germany and Italy. Mario G. Rosso's co-authors include Yong Li, Bernd Weißhaar, N. Strizhov, Koen Dekker, Bernd Reiss, Sabine Zachgo, Shuping Xing, Björn Usadel, Markus Pauly and Nora Eckermann and has published in prestigious journals such as Nature Biotechnology, Bioinformatics and The Plant Cell.

In The Last Decade

Mario G. Rosso

11 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An Arabidopsis thaliana T-DNA mutagenized population (GABI-Kat) for flanking sequence tag-based reverse genetics

2003 634 citations Mario G. Rosso, Yong Li et al. Plant Molecular Biology profile →

Peers

Countries citing papers authored by Mario G. Rosso

Since Specialization

Citations

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

Fields of papers citing papers by Mario G. Rosso

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mario G. Rosso. 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 Mario G. Rosso. The network helps show where Mario G. Rosso may publish in the future.

Co-authorship network of co-authors of Mario G. Rosso

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

All Works

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11 of 11 papers shown

#	Work	Indexed citations
1	Combining next‐generation sequencing and progeny testing for rapid identification of induced recessive and dominant mutations in maize M₂ individuals 2019 ·The Plant Journal ·(unknown), Mario G. Rosso, Martin Mascher, Ronny Brandt, Henning Tschiersch, Lothar Altschmied, Thomas Altmann	7
2	T-DNA–mediated transfer of Agrobacterium tumefaciens chromosomal DNA into plants 2008 ·Nature Biotechnology ·Bekir Ülker, Yong Li, Mario G. Rosso, Elke Logemann, Imre E. Somssich, Bernd Weißhaar	51
3	Analysis of T-DNA insertion site distribution patterns in Arabidopsis thaliana reveals special features of genes without insertions 2006 ·Genomics ·Yong Li, Mario G. Rosso, Bekir Ülker, Bernd Weißhaar	32
4	ROXY1 , a member of the plant glutaredoxin family, is required for petal development in Arabidopsis thaliana 2005 ·Development ·Shuping Xing, Mario G. Rosso, Sabine Zachgo	147
5	The Arabidopsis Plastidic Glucose 6-Phosphate/Phosphate Translocator GPT1 Is Essential for Pollen Maturation and Embryo Sac Development 2005 ·The Plant Cell ·(unknown), (unknown), Stefan Geimer, Karsten Fischer, Burkhard Schulz, (unknown), Mario G. Rosso, Peter Ache, Ulf‐Ingo Flügge, Anja Schneider	176
6	Mutational and expression analysis of ELIP1 and ELIP2 in Arabidopsis thaliana 2005 ·Plant Molecular Biology ·Anna Paola Casazza, (unknown), Mario G. Rosso, C. Soave	53
7	Identification of Three Urease Accessory Proteins That Are Required for Urease Activation in Arabidopsis 2005 ·PLANT PHYSIOLOGY ·Claus‐Peter Witte, Mario G. Rosso, Tina Romeis	59
8	RHM2 Is Involved in Mucilage Pectin Synthesis and Is Required for the Development of the Seed Coat in Arabidopsis 2004 ·PLANT PHYSIOLOGY ·Björn Usadel, (unknown), Mario G. Rosso, Nora Eckermann, Markus Pauly	122
9	An Arabidopsis thaliana T-DNA mutagenized population (GABI-Kat) for flanking sequence tag-based reverse genetics breakdown → 2003 ·Plant Molecular Biology ·Mario G. Rosso, Yong Li, N. Strizhov, Bernd Reiss, Koen Dekker, Bernd Weißhaar	634
10	GABI-Kat SimpleSearch: a flanking sequence tag (FST) database for the identification of T-DNA insertion mutants in Arabidopsisthaliana 2003 ·Bioinformatics ·Yong Li, Mario G. Rosso, N. Strizhov, Prisca Viehoever, Bernd Weißhaar	54
11	High-throughput generation of sequence indexes from T-DNA mutagenized Arabidopsis thaliana lines 2003 ·BioTechniques ·N. Strizhov, Yong Li, Mario G. Rosso, Prisca Viehoever, Koen Dekker, Bernd Weißhaar	25

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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