Current Bioinformatics - Volume 5, Issue 3, 2010

Epigenetics has become a cornerstone of cancer research and is an increasingly important factor in the continuous efforts to try and unravel the biology of oncogenesis. Consequently the analyses of epigenetic data have evolved towards genome wide and high-throughput approaches, generating large data sets for which computational data mining is indispensable. Bioinformatics has proven to be useful and beneficial f Read More

The goal of tumor immunology is to understand the interactions between tumor cells and immune system, and ultimately to devise immune basedapproaches to fight cancer. We discuss here recent advances in tumor immunology and in the interaction between immunology and informatics that provide new perspectives for the development of cancer therapy. Cancer immunoprevention is a novel approach to can Read More

There has been substantial evidence that functional and structural analyses of genes and proteins can help develop new drugs, diagnose medical conditions and find cures for diseases. However, these biological sequence analyses require large-scale computational power due to the exponential growth of genomic information. During the past two decades considerable efforts have been expended in trying to accelera Read More

Predicting the thermostability of a biomolecule, given its sequence, is one of the big challenges of protein engineering and developing tools to screen thermostable mutants is of great interest. Here we used various screening, clustering, decision tree and generalized rule induction models to search for patterns of thermostability. Arg was solely found as N-terminal amino acid in proteins at temperatures higher than 70°C. Fi Read More

Microarray technology enables the monitoring of the expression patterns of a huge number of genes across different experimental conditions or time points simultaneously. Biclustering of microarray data is an important technique to discover a group of genes that are co-regulated in a subset of experimental conditions. Traditional clustering algorithms find groups of genes/conditions over the complete feature space. Therefore Read More

The theoretical prediction of protein structures has become a field of increasing importance in both biology and physics. Reliable prediction methods in fact, would spare time consuming experimental X-ray and NMR techniques and they would represent a challenge for computational protein modeling as well. The well known limitations of all-atom models call for the development of coarse-grained protein descriptions i Read More