PPI discovery using proteome coevolution

Structure discovery in PPI networks using pattern-based network decomposition

MOTIVATION The large, complex networks of interactions between proteins provide a lens through which one can examine the structure and function of biological systems. Previous analyses of these continually growing networks have primarily followed either of two approaches: large-scale statistical analysis of holistic network properties, or small-scale analysis of local topological features. Mean...

Coevolution Analysis using Protein Sequences

Proteome-scale Protein-protein Interaction Site Prediction and Novel Motif Discovery Using Re-occurring Polypeptide Sequences

vii Acknowledgements viii Chapter

Selecting Negative Samples for PPI Prediction Using Hierarchical Clustering Methodology

Protein-protein interactions PPIs play a crucial role in cellular processes. In the present work, a new approach is proposed to construct a PPI predictor training a support vector machine model through a mutual information filter-wrapper parallel feature selection algorithm and an iterative and hierarchical clustering to select a relevance negative training set. By means of a selected suboptimu...

Technologies for Proteome-Wide Discovery of Extracellular Host-Pathogen Interactions

Pathogens have evolved unique mechanisms to breach the cell surface barrier and manipulate the host immune response to establish a productive infection. Proteins exposed to the extracellular environment, both cell surface-expressed receptors and secreted proteins, are essential targets for initial invasion and play key roles in pathogen recognition and subsequent immunoregulatory processes. The...