Gene Ontology-driven inference of protein–protein interactions using inducers
نویسندگان
چکیده
منابع مشابه
Gene Ontology-driven inference of protein-protein interactions using inducers
MOTIVATION Protein-protein interactions (PPIs) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. Most GO-driven algorithms for PPI inference combine machine learning and semantic similarity techniques. We introduce the concept of inducers as a method to integrate both approaches more effectivel...
متن کاملSupplementary material Gene Ontology-driven inference of protein-protein interactions using inducers
GO is divided into the three sub-ontologies: biological process (BP), molecular function (MF), cellular component (CC), represented as disjunct graphs. We are interested in the prediction accuracies of inducers for individual sub-ontologies and the accuracy when combining the information of the three sub-ontologies. Natively, inducers operate over individual sub-ontologies. To integrate informa...
متن کاملPredicting Network Attacks Using Ontology-Driven Inference
Graph knowledge models and ontologies are very powerful modeling and re asoning tools. We propose an effective approach to model network attacks and attack prediction which plays important roles in security management. The goals of this study are: First we model network attacks, their prerequisites and consequences using knowledge representation methods in order to provide description logic rea...
متن کاملgProt: Annotating Protein Interactions Using Google and Gene Ontology
With the increasing amount of biomedical literature, there is a need for automatic extraction of information to support biomedical researchers. Due to incomplete biomedical information databases, the extraction cannot be done straightforward using dictionaries, so several approaches using contextual rules and machine learning have previously been proposed. Our work is inspired by the previous a...
متن کاملMining Gene-Disease Relationships from Biomedical Literature: Weighting Proteinprotein Interactions and Connectivity
Motivation: The promises of the post-genome era disease-related discoveries and advances have yet to be fully realized, with many opportunities for discovery hiding in the millions of biomedical papers published since. Public databases give access to data extracted from the literature by teams of experts, but their coverage is often limited and lags behind recent discoveries. We present a compu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2011
ISSN: 1460-2059,1367-4803
DOI: 10.1093/bioinformatics/btr610