Current Bioinformatics - Volume 5, Issue 4, 2010

Biomacromolecular information is hinged by sequence and structure representations. Because structure is often more conserved than sequence, achieving function inference from structural similarity is easier than from sequence analysis. However, structural information is sparse and only available for a small part of the protein space. Detecting subtle similarities between proteins from sequence depends strongly on the re Read More

The post-genomic era, beginning at the end of the Human Genome Project, has led to new needs and challenges in the management of clinical and -omics data. One of the main issues in this new context for biomedical data management is the integration of heterogeneous sources, enabling access to different, remote biological data sources and the interpretation and discovery of new knowledge. Many researchers and practi Read More

Microarray technology has revolutionized biomedical research because it is now possible to concurrently determine the gene expression levels for the whole genome of a target organism. The accuracy of the computed gene expression levels is extremely important for the successful use of this technology. However, microarray gene expression measurements are inherently very ‘noisy’, meaning that appropriate techniques are r Read More

Microarray technology is expanding rapidly providing an extensive as well as promising source of data for better addressing complex questions involving biological processes. The ever increasing number and publicly available gene expression studies of human and other organisms provide strong motivation to carry out cross-study analyses. Besides, microarray technology provides several platforms to investigators that incl Read More

With the advances in bioinformatics, drug design strategies have been advanced with the focus on target discovery. ‘Proteins and enzymes’ target class represents potential drug target for different diseases. A networking of biochemical pathway of a disease and their drug target needs a thorough understanding. The accessibility of fully sequenced genomes, its total information and their product (proteins and enzymes) ha Read More

Ensemble learning is an intensively studied technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complex data structures. The aim of this article is two-fold. Firstly, it is to provide a review of the most widely used ensemble learning m Read More