Autoencoder imputation of missing heterogeneous data for Alzheimer's disease classification.

Missing Alzheimer's disease (AD) data is prevalent and poses significant challenges for AD diagnosis. Previous studies have explored various data imputation approaches on AD data, but the systematic evaluation of deep learning algorithms for imputing heterogeneous and comprehensive AD data is limited. This study investigates the efficacy of denoising autoencoder-based imputation of missing key features of heterogeneous data that comprised tau-PET, MRI, cognitive and functional assessments, genotype, sociodemographic, and medical history.

Mapping resistance to Sclerotinia white mold in two pinto bean recombinant inbred line populations.

White mold, caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary, is a devastating disease affecting common bean (Phaseolus vulgaris L.) production worldwide.

GWAS of resistance to three bacterial diseases in the Andean common bean diversity panel.

Bacterial brown spot (BBS) caused by pv. (), common bacterial blight (CBB) caused by pv. () and subsp.

T and Z, partial seed coat patterning genes in common bean, provide insight into the structure and protein interactions of a plant MBW complex.

Flavonoids are secondary metabolites associated with plant seed coat and flower color. These compounds provide health benefits to humans as anti-inflammatory and antioxidant compounds. The expression of the late biosynthetic genes in the flavonoid pathway is controlled by a ternary MBW protein complex consisting of interfacing MYB, beta-helix-loop-helix (bHLH), and WD40 Repeat (WDR) proteins.