His primary scientific interests are in Genetics, Genome, Single-nucleotide polymorphism, Genetic marker and Gene mapping. His SNP genotyping, Quantitative trait locus, Genetic linkage, Glycine soja and Microsatellite investigations are all subjects of Genetics research. His Glycine soja research incorporates elements of Genome evolution, Genome project, Genome size and Genomics.
Qijian Song studies Gene density, a branch of Genome. His Single-nucleotide polymorphism research is multidisciplinary, relying on both Nucleotide diversity, Haplotype and Genotyping. His study in Genetic marker is interdisciplinary in nature, drawing from both Restriction fragment length polymorphism, Whole genome sequencing and DNA sequencing.
Qijian Song mainly focuses on Genetics, Quantitative trait locus, Single-nucleotide polymorphism, Gene and Genetic linkage. His research on Genetics often connects related topics like Germplasm. The concepts of his Germplasm study are interwoven with issues in Linkage disequilibrium, Haplotype and Glycine soja.
His studies in Glycine soja integrate themes in fields like Domestication and Genetic variation. His Quantitative trait locus research includes themes of Plant disease resistance, Genome-wide association study, Cultivar, Agronomy and Association mapping. The various areas that Qijian Song examines in his Single-nucleotide polymorphism study include Genotyping and Allele.
Qijian Song mostly deals with Genetics, Quantitative trait locus, Gene, Cultivar and Candidate gene. His work is connected to Single-nucleotide polymorphism, Genetic linkage, Plant disease resistance, Locus and Genotype, as a part of Genetics. Qijian Song has included themes like Genotyping, Inbred strain and Allele in his Quantitative trait locus study.
His Gene study combines topics from a wide range of disciplines, such as Software maintainer and Helianthus annuus. His work in Cultivar addresses subjects such as Domestication, which are connected to disciplines such as Haplotype, Molecular breeding, Glycine soja, Linkage disequilibrium and Germplasm. His study in DNA sequencing extends to Genome with its themes.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Genome sequence of the palaeopolyploid soybean
Jeremy Schmutz;Steven B. Cannon;Jessica Schlueter;Jessica Schlueter;Jianxin Ma.
A new integrated genetic linkage map of the soybean.
Q.J. Song;L.F. Marek;R.C. Shoemaker;K.G. Lark.
Theoretical and Applied Genetics (2004)
A reference genome for common bean and genome-wide analysis of dual domestications
Jeremy Schmutz;Phillip E McClean;Sujan Mamidi;G Albert Wu.
Nature Genetics (2014)
Development and mapping of microsatellite (SSR) markers in wheat.
Q. J. Song;Q. J. Song;J. R. Shi;S. Singh;E. W. Fickus.
Theoretical and Applied Genetics (2005)
Impacts of genetic bottlenecks on soybean genome diversity.
David L. Hyten;Qijian Song;Qijian Song;Youlin Zhu;Youlin Zhu;Ik Young Choi.
Proceedings of the National Academy of Sciences of the United States of America (2006)
DNA markers for Fusarium head blight resistance QTLs in two wheat populations
J. A. Anderson;R. W. Stack;S. Liu;B. L. Waldron.
Theoretical and Applied Genetics (2001)
Single-Nucleotide Polymorphisms in Soybean
Y. L. Zhu;Y. L. Zhu;Q. J. Song;Q. J. Song;D. L. Hyten;C. P. Van Tassell.
Development and evaluation of SoySNP50K, a high-density genotyping array for soybean.
Qijian Song;David L. Hyten;Gaofeng Jia;Charles V. Quigley.
PLOS ONE (2013)
A genome-wide association study of seed protein and oil content in soybean.
Eun-Young Hwang;Qijian Song;Gaofeng Jia;James E Specht.
BMC Genomics (2014)
A soybean transcript map: gene distribution, haplotype and single-nucleotide polymorphism analysis.
Ik Young Choi;David L. Hyten;Lakshmi K. Matukumalli;Qijian Song.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: