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DNA methylation changes could provide a mechanism for DNA plasticity and dynamism for short-term adaptation, enabling a type of cell memory to register cellular history under different environmental conditions. Some environmental insults may also result in pathological methylation with corresponding alteration of gene expression patterns. Evidence from(More)
The goal of these experiments was to understand DNA changes relevant to schizophrenia. This work compared DNA of monozygotic (MZ) twins surrounding (CAG)(n) repeating sequences, and characterized the relationship between fragile sites and schizophrenia. Twelve twin-pairs, previously classified as MZ and 18 unrelated sib-pairs, from seven families were(More)
Increasing evidence links genomic and epigenomic instability, including multiple fragile sites regions to neuropsychiatric diseases including schizophrenia and autism. Cancer is the only other disease associated with multiple fragile site regions, and genome and epigenomic instability is a characteristic of cancer. Research on cancer is far more advanced(More)
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resample the original training set into a smaller set of representative training exemplars, represented by weighted cluster centers and their target outputs. Based on the proposed(More)
This paper presents an efficient training approach for support vector machines that will improve their ability to learn from a large or imbalanced data set. Given an original training set, the proposed approach applies unsupervised learning to extract a smaller set of salient training exemplars, which are represented by weighted cluster centers and the(More)
In this article, we propose a new supervised learning approach for pattern classification applications involving large or imbalanced data sets. In this approach, a clustering technique is employed to reduce the original training set into a smaller set of representative training exemplars, represented by weighted cluster centers and their target outputs.(More)
— Pedestrian detection is a vision task with many practical applications in video surveillance, road safety, autonomous driving and military. However, it is much more difficult compared to the detection of other visual objects, because of the tremendous variations in the inner region as well as the outer shape of the pedestrian pattern. In this paper, we(More)
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