Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

ABSTRACT:

Background

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lun

SUBMITTER: Srivastava M 

PROVIDER: S-EPMC3532198 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature