ABSTRACT
MOTIVATION: In a liquid chromatography-mass spectrometry (LC-MS)-based expressional proteomics, multiple samples from different groups are analyzed in parallel. It is necessary to develop a data mining system to perform peak quantification, peak alignment and data quality assurance. RESULTS: We have developed an algorithm for spectrum deconvolution. A two-step alignment algorithm is proposed for recognizing peaks generated by the same peptide but detected in different samples. The quality of LC-MS data is evaluated using statistical tests and alignment quality tests. AVAILABILITY: Xalign software is available upon request from the author.
Subject(s)
Algorithms , Chromatography, Liquid/methods , Databases, Protein , Mass Spectrometry/methods , Peptide Mapping/methods , Proteins/chemistry , Sequence Analysis, Protein/methods , Artificial Intelligence , Database Management Systems , Diagnosis, Computer-Assisted/methods , Gene Expression Profiling/methods , Humans , Information Storage and Retrieval/methods , Proteins/analysis , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Digital video now plays an important role in medical education, health care, telemedicine and other medical applications. Several content-based video retrieval (CBVR) systems have been proposed in the past, but they still suffer from the following challenging problems: semantic gap, semantic video concept modeling, semantic video classification, and concept-oriented video database indexing and access. In this paper, we propose a novel framework to make some advances toward the final goal to solve these problems. Specifically, the framework includes: 1) a semantic-sensitive video content representation framework by using principal video shots to enhance the quality of features; 2) semantic video concept interpretation by using flexible mixture model to bridge the semantic gap; 3) a novel semantic video-classifier training framework by integrating feature selection, parameter estimation, and model selection seamlessly in a single algorithm; and 4) a concept-oriented video database organization technique through a certain domain-dependent concept hierarchy to enable semantic-sensitive video retrieval and browsing.
