About Plant Computational and Quantitative Genomics

Twenty-two years after the publication of the first-ever plant genome sequence, the generation and broad availability of genomic and transcriptomic sequence information has now become commonplace, essentially having reached the stage that for every plant species and even individual specimens, complete genomic and transcriptome sequence and expression information can be easily generated. While the sheer amount of information poses challenges with regards to computational data analysis and management, it also opens new avenues of research. In particular, the enormous depth of available sequence information allows exploiting of the detected sequence variation in a broad range of studies that aim at discerning genotype-phenotype relationships using computational means that rely on statistical models.

This collection invites contributions that present computational studies, software solutions, databases, and online services that focus on the use of sequence-variant information in plants. The envisioned scope of studies ranges from variant calling, profiling of SNPs in genomic regions with the goal to identify sequence motifs, to the identification of candidate genes via GWAS, and the application and development of statistical/machine learning models for genomic selection and their use in breeding projects. We look forward to receiving a wide range of article types including Research Articles, Brief Reports, Software Tool Articles, Method Articles, Reviews and Opinion Articles.

Keywords: Sequencing; genome annotation; variant calling; SNPs; motif discovery; GWAS; genomic selection; breeding; pan-genome/transcriptome analyses; statistical models.

This collection is part of the Bioinformatics and Plant Science Gateways.

Any questions about this collection? Please get in contact directly with research@f1000.com.