The application of regular expression-based pattern matching to profiling the developmental factors that contribute to the development of the inner ear.
The biomedical literature has always played a critical role in the development of hypotheses to test, experimental design, and the analysis of study results. Yet, the ever-expanding body of biomedical literature is starting to present new challenges, in which locating pertinent literature from among the millions of published research articles is often a challenging task. A regular expression-based pattern matching method has been developed to profile the various gene and protein factors that may play a role in various tissues contained within an organism. This methodology has been demonstrated through the profiling of the various factors that are involved in the development of the inner ear, and is shown to be both effective and accurate.
Frenz
Christopher M
CM
Department of Computer Engineering Technology, New York City College of Technology (CUNY), 300 Jay Street, Brooklyn, NY 11201, USA. cfrenz@citytech.cuny.edu
Frenz
Dorothy A
DA
D019295:Computational Biology; D057225:Data Mining; D007758:Ear, Inner / Q000254:growth & development* / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D018507:Gene Expression Regulation, Developmental; D006133:Growth Substances / Q000235:genetics / Q000378:metabolism; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D010363:Pattern Recognition, Automated; D040081:Protein Array Analysis / Q000706:statistics & numerical data; D012984:Software
D006133:Growth Substances