We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
Background: Computational methods to predict transcription factor binding sites (TFBS) based on exhaustive algorithms are guaranteed to find the best patterns but are often limite...
Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of ...
Ting-Hua Huang, Bin Fan, Max F. Rothschild, Zhi-Li...
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
Background: Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epi...