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OUGene 2.0: An updated disease-associated over- and under-expressed gene database by mining full-text articles

Erdi Qin, Xiaoyong PaniD, Hong‐Bin SheniD

Abstract

Many diseases are closely associated with over- or under-expressed genes. In order to cover more up to date associations between over- or under-expressed genes and various diseases, we develop an updated database OUGENE 2.0 for disease-associated over- and under-expressed genes by automatic full-text mining. In total, the new OUGene 2.0 includes 197,236 associations between 12,672 diseases and 11,542 over- or under-expressed genes, which increases by about 5 folds compared to the previous version of OUGene. A novel method for rescaling the raw score based on support evidences is designed to prioritize the mined associations. OUGene 2.0 provides a holistic view of disease-gene associations and it supports user-friendly data exploration at www.csbio.sjtu.edu.cn/bioinf/OUGene for academic use.

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02 /Specification & Classification

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