Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
The first paradigm of plant breeding involves direct selection-based phenotypic observation,
followed by predictive breeding using statistical models for quantitative traits constructed …
followed by predictive breeding using statistical models for quantitative traits constructed …
Plant genome resequencing and population genomics: Current status and future prospects
Advances in DNA sequencing technology have sparked a genomics revolution, driving
breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from …
breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from …
Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding
Inversions, a type of chromosomal structural variation, significantly influence plant
adaptation and gene functions by impacting gene expression and recombination rates …
adaptation and gene functions by impacting gene expression and recombination rates …
[HTML][HTML] Leveraging machine learning to streamline the development of liposomal drug delivery systems
Drug delivery systems efficiently and safely administer therapeutic agents to specific body
sites. Liposomes, spherical vesicles made of phospholipid bilayers, have become a …
sites. Liposomes, spherical vesicles made of phospholipid bilayers, have become a …
Application of machine learning and genomics for orphan crop improvement
Orphan crops are important sources of nutrition in develo** regions and many are tolerant
to biotic and abiotic stressors; however, modern crop improvement technologies have not …
to biotic and abiotic stressors; however, modern crop improvement technologies have not …
Analysis and comparison of feature selection methods towards performance and stability
The amount of gathered data is increasing at unprecedented rates for machine learning
applications such as natural language processing, computer vision, and bioinformatics. This …
applications such as natural language processing, computer vision, and bioinformatics. This …
Image-based phenoty** of seed architectural traits and prediction of seed weight using machine learning models in soybean
Among seed attributes, weight is one of the main factors determining the soybean harvest
index. Recently, the focus of soybean breeding has shifted to improving seed size and …
index. Recently, the focus of soybean breeding has shifted to improving seed size and …
Stacked kinship CNN vs. GBLUP for genomic predictions of additive and complex continuous phenotypes
Deep learning is impacting many fields of data science with often spectacular results.
However, its application to whole-genome predictions in plant and animal science or in …
However, its application to whole-genome predictions in plant and animal science or in …
Large sample size and nonlinear sparse models outline epistatic effects in inflammatory bowel disease
Background Despite clear evidence of nonlinear interactions in the molecular architecture of
polygenic diseases, linear models have so far appeared optimal in genotype-to-phenotype …
polygenic diseases, linear models have so far appeared optimal in genotype-to-phenotype …
DeepAProt: Deep learning based abiotic stress protein sequence classification and identification tool in cereals
The impact of climate change has been alarming for the crop growth. The extreme weather
conditions can stress the crops and reduce the yield of major crops belonging to Poaceae …
conditions can stress the crops and reduce the yield of major crops belonging to Poaceae …