Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

Abstract

Background: Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets.

Ariadne's ChemEffect and Pathway Studio knowledge base

“…All of them were created by manual curation and therefore have limited scope and usability. The results of information extraction by manual curation and by NLP technology were compared previously [3,4]. In brief, they concluded that NLP provides significantly higher recovery rate and consistency of extracted data while manually curated dataset usually provides higher accuracy.…”

Data mining of microarray for differentially expressed genes in liver metastasis from gastric cancer

“…Therefore, biomedical researchers always wish to explore the pathogenesis of abnormal expressing genes, such as those genes confirmed by cDNA microarray analysis, and furthermore, literature mining is an important method for completing them [7]. At present, there have been a variety of mining tools and methods to extract keywords from literatures or gene networks from functional genes and to make them visualized [8][9][10][11][12][13][14][15]. However, based on specific keywords, these tools cannot automatically and simply establish gene networks that are helpful to explore diseaserelated signal transduction pathways.…”

An Optimized Prediction Model Based on Feature Probability for Functional Identification of Large-Scale Ubiquitous Data

“…Option " " is the value to conduct the inflation and expansion in the Markov model; thus, it is possible to see the changes of elements inside the clustering depending on the value of . Another function prediction method is the context-free method; it utilizes the context of several DBs of Uniprot or PubMed [15].…”