Genomic and metabolic prediction of complex heterotic traits in hybrid maize

439 indexed citations

Abstract

loading...

About

This paper, published in 2012, received 439 indexed citations. Written by Christian Riedelsheimer, Angelika Czedik‐Eysenberg, Christoph Grieder, Jan Lisec, Frank Technow, Ronan Sulpice, Thomas Altmann, Mark Stitt, Lothar Willmitzer and Albrecht E. Melchinger covering the research area of Genetics and Plant Science. It is primarily cited by scholars working on Plant Science (362 citations), Genetics (301 citations) and Molecular Biology (99 citations). Published in Nature Genetics.

In The Last Decade

doi.org/10.1038/ng.1033 →

Countries where authors are citing Genomic and metabolic prediction of complex heterotic traits in hybrid maize

Specialization
Citations

This map shows the geographic impact of Genomic and metabolic prediction of complex heterotic traits in hybrid maize. 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 Genomic and metabolic prediction of complex heterotic traits in hybrid maize with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Genomic and metabolic prediction of complex heterotic traits in hybrid maize more than expected).

Fields of papers citing Genomic and metabolic prediction of complex heterotic traits in hybrid maize

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Genomic and metabolic prediction of complex heterotic traits in hybrid maize.

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.

This paper is also available at doi.org/10.1038/ng.1033.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026