title: Finding top-k covering irreducible contrast sequence rules for disease diagnosis.
abstract: Diagnostic genes are usually used to distinguish different disease phenotypes. Most existing methods for diagnostic genes finding are based on either the individual or combinatorial discriminative power of gene(s). However, they both ignore the common expression trends among genes. In this paper, we devise a novel sequence rule, namely, top-k irreducible covering contrast sequence rules (TopkIRs for short), which helps to build a sample classifier of high accuracy. Furthermore, we propose an algorithm called MineTopkIRs to efficiently discover TopkIRs. Extensive experiments conducted on synthetic and real datasets show that MineTopkIRs is significantly faster than the previous methods and is of a higher classification accuracy. Additionally, many diagnostic genes discovered provide a new insight into disease diagnosis.
authors: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
authors: Yuhai
authors: Y
authors: Zhao
authors: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
authors: Yuan
authors: Y
authors: Li
authors: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
authors: Ying
authors: 0000-0002-7995-8590
authors: Y
authors: Yin
authors: Software Center, Northeastern University, Shenyang, Liaoning 110004, China.
authors: Gang
authors: 0000-0001-7089-1302
authors: G
authors: Sheng
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D020022:Genetic Predisposition to Disease; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D015203:Reproducibility of Results; D012984:Software