This article reviews machine learning methods for bioinformatics. It presents modelling
methods, such as supervised classification, clustering and probabilistic graphical models for …

Powerful specialized software is essential for managing, quantifying, and ultimately deriving
scientific insight from results of a microarray experiment. We have developed a suite of …

MicroRNAs (miRNAs) are a non-coding family of genes involved in post-transcriptional gene
regulation. These transcripts are associated with cell proliferation, cell differentiation, cell …

The geometric framework for the support vector machine (SVM) classification problem
provides an intuitive ground for the understanding and the application of geometric …

Overwhelmed with genomic data, biologists are facing the first big post-genomic question—
what do all genes do? First, not only is the volume of pure sequence and structure data …

Background Non-invasive methods for diagnosis of urothelial carcinoma have reduced
specificity in patients with non-malignant genitourinary disease or other disorders. We aimed …

Background Diverse modeling approaches viz. neural networks and multiple regression
have been followed to date for disease prediction in plant populations. However, due to their …

Preoperative radiotherapy has been widely used to improve local control of disease and to
improve survival in the treatment of rectal cancer. However, the response to radiotherapy …

Abstract CARMAweb (Comprehensive R-based Microarray Analysis web service) is a web
application designed for the analysis of microarray data. CARMAweb performs data …

Motivation: Temporal gene expression profiles provide an important characterization of gene
function, as biological systems are predominantly developmental and dynamic. We propose …