title: Wavelet analysis in current cancer genome research: a survey.
abstract: With the rapid development of next generation sequencing technology, the amount of biological sequence data of the cancer genome increases exponentially, which calls for efficient and effective algorithms that may identify patterns hidden underneath the raw data that may distinguish cancer Achilles' heels. From a signal processing point of view, biological units of information, including DNA and protein sequences, have been viewed as one-dimensional signals. Therefore, researchers have been applying signal processing techniques to mine the potentially significant patterns within these sequences. More specifically, in recent years, wavelet transforms have become an important mathematical analysis tool, with a wide and ever increasing range of applications. The versatility of wavelet analytic techniques has forged new interdisciplinary bounds by offering common solutions to apparently diverse problems and providing a new unifying perspective on problems of cancer genome research. In this paper, we provide a survey of how wavelet analysis has been applied to cancer bioinformatics questions. Specifically, we discuss several approaches of representing the biological sequence data numerically and methods of using wavelet analysis on the numerical sequences.
authors.affiliation: University of Miami, Coral Gables.
authors.forename: Tao
authors.initials: T
authors.lastname: Meng
authors.affiliation: University of Miami, Coral Gables.
authors.forename: Ahmed T
authors.initials: AT
authors.lastname: Soliman
authors.affiliation: University of Miami, Coral Gables.
authors.forename: Mei-Ling
authors.initials: ML
authors.lastname: Shyu
authors.affiliation: Florida International University, Miami.
authors.forename: Yimin
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Florida International University , Miami.
authors.forename: Shu-Ching
authors.initials: SC
authors.lastname: Chen
authors.affiliation: Florida International University, Miami.
authors.forename: S S
authors.initials: SS
authors.lastname: Iyengar
authors.affiliation: University of Texas Southwestern Medical Center, Dallas.
authors.forename: John S
authors.initials: JS
authors.lastname: Yordy
authors.affiliation: University of Texas Southwestern Medical Center, Dallas.
authors.forename: Puneeth
authors.initials: P
authors.lastname: Iyengar
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D000596:Amino Acids / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D018628:Gene Dosage; D015894:Genome, Human; D006801:Humans; D008432:Mathematical Computing; D008962:Models, Theoretical; D009154:Mutation; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D017433:Protein Structure, Secondary; D017422:Sequence Analysis, DNA; D012815:Signal Processing, Computer-Assisted; D058067:Wavelet Analysis
chemical_list: D000596:Amino Acids