Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
The design of new quantum algorithms has proven to be an extremely difficult task. This paper considers a different approach to the problem, by studying the problem of 'quant...
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...