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Building quality software is expensive and software quality assurance (QA) budgets are limited. Data miners can learn defect predictors from static code features which can be used to control QA resources; e.g. to focus on the parts of the code predicted to be more defective. Recent results show that better data mining technology is not leading to better(More)
PURPOSE To investigate expression, regulation, potential role and targets of miR-195 and miR-497 in breast cancer. EXPERIMENTAL DESIGN The expression patterns of miR-195 and miR-497 were initially examined in breast cancer tissues and cell lines by Northern blotting and quantitative real-time PCR. Combined bisulfite restriction analysis and bisulfite(More)
The objective of this study was to document and compare the lipid class and fatty acid composition of the green microalga Chlorella zofingiensis cultivated under photoautotrophic and heterotrophic conditions. Compared with photoautotrophic cells, a 900% increase in lipid yield was achieved in heterotrophic cells fed with 30 g L(-1) of glucose. Furthermore(More)
Many statistical techniques have been proposed to predict fault-proneness of program modules in software engineering. Choosing the " best " candidate among many available models involves performance assessment and detailed comparison, but these comparisons are not simple due to the applicability of varying performance measures. Classifying a software module(More)
The green microalga Chlorella protothecoides was grown heterotrophically in batch mode in a 3.7-L fermenter containing 40 g/L glucose and 3.6 g/L urea. In the late exponential phase, concentrated nutrients containing glucose and urea were fed into the culture, in which the nitrogen source was sufficient compared to carbon source. As a result, a maximum cell(More)
Context: There are many methods that input static code features and output a predictor for faulty code modules. These data mining methods have hit a "performance ceiling"; i.e., some inherent upper bound on the amount of information offered by, say, static code features when identifying modules which contain faults. Objective: We seek an explanation for(More)
MOTIVATION The development of high-throughput sequencing technologies has enabled novel methods for detecting structural variants (SVs). Current methods are typically based on depth of coverage or pair-end mapping clusters. However, most of these only report an approximate location for each SV, rather than exact breakpoints. RESULTS We have developed(More)
The prediction of fault-prone modules in a software project has been the topic of many studies. In this paper, we investigate whether metrics available early in the development lifecycle can be used to identify fault-prone software modules. More precisely, we build predictive models using the metrics that characterize textual requirements. We compare the(More)
Gastric cancer, including the cardia and non-cardia types, is the second leading cause of cancer-related deaths worldwide. To identify genetic risk variants for non-cardia gastric cancer, we performed a genome-wide association study in 3,279 individuals (1,006 with non-cardia gastric cancer and 2,273 controls) of Chinese descent. We replicated significant(More)
Endocytic sorting is achieved through the formation of morphologically and functionally distinct sub-domains within early endosomes. Cargoes destined for recycling are sorted to and transported through newly-formed tubular membranes, but the processes that regulate membrane tubulation are poorly understood. Here, we identified a novel Caenorhabditis elegans(More)