Motivation: Although manual curation of proteinprotein interactions from literature resulted in several large databases, many interactions are still available only in manuscripts. Though PubMed does include a search engine, protein-protein interactions remain difficult to find in an automated manner. Results: OPHID Text Miner (OTM) is an information extraction system dedicated to finding specif...

In this paper, we introduce a novel fuzzy method which is combined fuzzy relation, interaction probability values and hub structure to detect sub-communities in complex networks. We apply our method on yeast proteinprotein interaction network to identify the protein complexes. Compared with traditional method, more protein complexes have been identified by this new fuzzy method. Meanwhile, we e...

Summary: We present a software framework and tool called PIANA that facilitates working with protein interaction networks by 1) integrating data from multiple sources, 2) providing a library that handles graph-related tasks and 3) automating the analysis of proteinprotein interaction networks. PIANA can also be used as a standalone application to create protein interaction networks and perform ...

Human phenotypes – i.e. our characteristics, conditions and diseases – are not merely a product of our genetic constitution, but rather arise out of an intricate system of interactions between the proteins and other molecules in our cells. 1 This fact has inspired a huge effort to document and understand the network of those protein-protein interactions which we’ll refer to collectively as the ...

Protein networks have a great importance in biological activities. ProteinProtein interaction occurs when two or more proteins interact together to carry out some biological activities. For example signals from the exterior of a cell are mediated to the interior through these interactions. Identification of these interaction have a great significance in understanding complex diseases and also f...

Biological networks provide insight into the complex organization of biological processes in a cell at the system level. They are an effective tool for understanding the comprehensive map of functional interactions, finding the functional modules and pathways. Reconstruction and comparative analysis of these networks provide useful information to identify functional modules, prioritization of d...

In this paper, a new method for PPI (proteinprotein interaction) prediction is proposed. In PPI prediction, a reliable and sufficient number of training samples is not available, but a large number of unlabeled samples is in hand. In the proposed method, the denoising autoencoders are employed for learning robust features. The obtained robust features are used in order to train a classifier wit...

Characterizing protein function is a crucial part of understanding biological systems. Here we improve protein function prediction by accounting for data quality issues inherent in protein-protein interaction (PPI) databases. To accomplish this, we incorporate confidence information into the function prediction pipeline. The model pipeline uses weighted majority voting on the proteinprotein int...

In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as proteinprotein interaction from the massive literature. The system recognizes biological term...