Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is...

Genomic duplication-divergence events, which are the primary source of new protein functions, occur stochastically at a wide range of genomic scales, from single gene to whole genome duplications. Clearly, this fundamental evolutionary process must have largely conditioned the emerging structure of proteinprotein interaction (PPI) networks, that control many cellular activities. We propose and ...

One main concern towards kernel classifiers is on their sensitivity to the choice of kernel function or kernel matrix which characterizes the similarity between instances. Many realworld data, such as web pages and proteinprotein interaction data, are relational in nature in the sense that different instances are correlated (linked) with each other. The relational information available in such ...

We present a high-throughput approach to study weak protein-protein interactions by coupling bimolecular fluorescent complementation (BiFC) to flow cytometry (FC). Bimolecular Fluorescence Complementation (BIFC) is a method to detect proteinprotein interactions based on the formation of a fluorescent complex by fragments of the yellow fluorescent protein (NYFP and CYFP) brought together by the ...

Since scientific journals are still the most important means of documenting biological findings, biomedical articles are the best source of information we have on protein-protein interactions. The mining of this information will provide us with specific knowledge of the presence and types of interactions, and the circumstances in which they occur. There are various linguistic constructions that...

Large-scale Protein-Protein interaction data sets exist in Saccharomyces cerevisiae due to many interaction detection methods such as yeast two-hybrid assay, mass spectrometry of purified complexes, correlated mRNA expression profile and so on. How to make use of these data sets to understand the protein function is very important. We use the algorithm [17] developed by Stijn van Dongen to desc...

Background: A prerequisite for successful embryo implantation is adequate preparation of receptive endometrium and the establishment and maintenance of a viable embryo. The success of implantation further relies upon a two-way dialogue between the embryo and uterus. However, molecular bases of these preimplantation and implantation processes in humans are not well known. Materials and Methods: ...

Protein-protein interactions have critical roles in many biological processes. We describe here the development of new approaches to detect, identify, and disrupt specific proteinprotein interactions. First. for the disruption of the interactions, a genetic selection was developed to select for dissociative inhibitors of dimeric enzymes from a genetically encoded combinatorial peptide library. ...

An important goal of systems biology is the identification and investigation of known and predicted proteinprotein interactions to obtain more information about new cellular pathways and processes. Proteins interact via domains, thus it is important to know which domains a protein contains and which domains interact with each other. Here we present the Java program ProDGe (Protein Domain Gene),...

Protein-protein interactions contribute to a variety of biological processes, including signal transduction, tissue integrity, and force generation (1,2). An inexpensive and reliable method to measure protein-protein interactions would be of considerable utility. Currently, co-immunoprecipitations (Co-IP) are routinely used to detect protein-protein interactions in cells, where one antibody is ...