Reading review papers helped me with mental rehabilitation after COVID-19

A few weeks ago, I was infected with COVID, such thousands of people every day here in Brazil. Fortunately, I had a good recovery from the physical symptoms, yet some psychiatric issues remained (bad concentration, anxiety). Because of this last, I took some time to rest and a few days ago I started some ‘mind therapy’ to warm up my concentration and came back to work with 100% power. This mental exercise consists of reading good review papers, that you already know (or read some time ago), in order to refresh some key concepts useful for your field of work. In my case, I share here with you some review papers from Quantitative Genetics, Genomic Selection, and Envirotyping. All these papers I read sometimes before, but yet I’m still learning new things from them. I hope you enjoy it and take care of yourself and yours to avoid contamination from COVID.

Nakaya and Isobe (2012) Will genomic selection be a practical method for plant breeding? Akihiro https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3478044/.

Des Marais et al (2013) Genotype-by-Environment Interaction and Plasticity: Exploring Genomic Responses of Plants to the Abiotic Environment https://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110512-135806

Cooper et al. (2014) Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction https://www.publish.csiro.au/cp/cp14007

Crossa et al. (2017) Genomic Selection in Plant Breeding: Methods, Models, and Perspectives. https://www.sciencedirect.com/science/article/abs/pii/S136013851730184X

Xu (2016) Envirotyping for deciphering environmental impacts on crop plants. https://link.springer.com/article/10.1007/s00122-016-2691-5

Wallace et al (2018) On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics https://pubmed.ncbi.nlm.nih.gov/30285496/

Voss-Fels et al (2019) Accelerating crop genetic gains with genomic selection https://link.springer.com/article/10.1007/s00122-018-3270-8

Bernardo (2020) Reinventing quantitative genetics for plant breeding: something old, something new, something borrowed, something BLUE https://www.nature.com/articles/s41437-020-0312-1

PLUS: Montesinos-López e tal. (2021). A review of deep learning applications for genomic selection https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-07319-x . This is a very nice paper about the use of Deep Learning (DL) in genomic prediction just publish a few weeks ago.

OBS: If you had any issue downloading these papers, please let me know and I can share them.

So, did you knew some of those papers? have more suggestions?

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