The prediction of a protein’s structure from its amino-acid sequence is one of the most important problems in computational biology. In the current focus on a widely studied abst...
Wepresent a novel, fast methodfor associationminingill high-dimensionaldatasets. OurCoincidence Detection method, which combines random sampling and Chernoff-Hoeffding bounds with...
Many algorithms for motif finding that are commonly used in bioinformatics start by sampling r potential motif occurrences from n input sequences. The motif is derived from these s...
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...