linked and/or gene-based molecular markers have been used widely in marker-assisted selection (mas) to differentiate resistant and susceptible genotypes. resistance to meloidogyne spp. in beta vulgaris l. is mediated by a single dominant gene (r6m-1). using allele-specific primers (asps), an snp marker harboring a single nucleotide polymorphism (a/g), linked to the resistance gene was developed...

The DNA Microarray technology can measure the expression levels of thousands of genes simultaneously, and produces huge volumes of gene expression data. Such gene data include complex variations among expression levels of genes in the various classes of samples, which allows for classifying and clustering the samples based on only a small subset of genes. We aim to identify those genes that dem...

Selecting relevant and discriminative genes for sample classification is a common and critical task in gene expression analysis (e.g. disease diagnostic). It is desirable that gene selection can improve classification performance of learning algorithm effectively. In general, for most gene selection methods widely used in reality, an individual gene subset will be chosen according to its discri...

complex vertebral malformation(cvm) isanautosomal recessivehereditarydisorder caused bya point mutation in position 559 inexon 4 of the slc35a3 gene on chromosome 3 inholstein dairy cattle.this mutationchanges the function of uridine 5-diphosphate-n-acetylglucosamine transporter protein bythe substitution of valine for phenylalanine at position 180 of this protein. the disease causes premature ...

Given the potential for rapid and microgeographical adaptation, ecologists increasingly are exploring evolutionary explanations for community patterns. Biotic selection can generate local adaptations that alter species interactions. Although some gene flow might be necessary to fuel local adaptation, higher gene flow can homogenise traits across regions and generate local maladaptation. Herein,...

MOTIVATION Given the thousands of genes and the small number of samples, gene selection has emerged as an important research problem in microarray data analysis. Support Vector Machine-Recursive Feature Elimination (SVM-RFE) is one of a group of recently described algorithms which represent the stat-of-the-art for gene selection. Just like SVM itself, SVM-RFE was originally designed to solve bi...