A graph model for genomic prediction in the context of a linear mixed model framework
Genomic selection is revolutionizing both plant and animal breeding, with its practical application depending critically on high prediction accuracy. In this study, we aimed to enhance prediction accuracy by exploring the use of graph models within a ...
Osval A. Montesinos‐López +4 more
doaj +1 more source
Bayesian inference of graph-based dependencies from mixed-type data
Mixed data comprise measurements of different types, with both categorical and continuous variables, and can be found in various areas, such as in life science or industrial processes.
Castelletti Federico, Peluso Stefano
core +1 more source
Edge, vertex and mixed fault diameters of Cartesian graph products and bundels
V disertaciji raziskujemo povezanost in okvarne premere kartezičnih grafovskih svežnjev in kartezičnih produktov. Vpeljemo mešano povezanost in mešani okvarni premer grafa, ki posplošujeta povezanosti in okvarna premera definirana glede na eno vrsto ...
Erveš, Rija
core
Evolutionary Kuramoto dynamics unravels origins of chimera states in neural populations. [PDF]
Zdyrski T, Pauls S, Fu F.
europepmc +1 more source
From sugarcane to polyploid crops: Graph pangenomes usher in a new era of complex-genome breeding. [PDF]
Wang C, Han B.
europepmc +1 more source
Continuous Emotion Recognition Using EDA-Graphs: A Graph Signal Processing Approach for Affective Dimension Estimation. [PDF]
Mercado-Diaz LR +3 more
europepmc +1 more source
Application scope of knowledge graphs in nursing: a scoping review. [PDF]
Wang Y +6 more
europepmc +1 more source
Edge, vertex and mixed fault diameters of Cartesian graph products and bundels
V disertaciji raziskujemo povezanost in okvarne premere kartezičnih grafovskih svežnjev in kartezičnih produktov. Vpeljemo mešano povezanost in mešani okvarni premer grafa, ki posplošujeta povezanosti in okvarna premera definirana glede na eno vrsto ...
Erveš, Rija
core
scHilda: Hierarchical Integration of LLM with KG database for single cell type annotation. [PDF]
Li Y +9 more
europepmc +1 more source
Simultaneous Representation Learning of Multi-Omics and Clinical Outcome Data via a Supervised Knowledge-Guided Bayesian Factor Model. [PDF]
Zhang Q, Chang C, Jin C, Shen L, Long Q.
europepmc +1 more source

