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Prediction of protein secondary structures is an important problem in bioinformatics and has many applications. The recent trend of secondary structure prediction studies is mostly based on the neural network or the support vector machine (SVM). The SVM method is a comparatively new learning system which has mostly been used in pattern recognition problems.(More)
Support vector machines (SVMs) have shown strong generalization ability in a number of application areas, including protein structure prediction. However, the poor comprehensibility hinders the success of the SVM for protein structure prediction. The explanation of how a decision made is important for accepting the machine learning technology, especially(More)
Recent discovery of the copy number variation (CNV) in normal individuals has widened our understanding of genomic variation. However, most of the reported CNVs have been identified in Caucasians, which may not be directly applicable to people of different ethnicities. To profile CNV in East-Asian population, we screened CNVs in 3578 healthy, unrelated(More)
The carboxylesterase Est55 has been cloned and expressed in Bacillus subtilis strains. Est55, which lacks a classical, cleavable N-terminal signal sequence, was found to be secreted during the stationary phase of growth such that there is more Est55 in the medium than inside the cells. Several cytoplasmic proteins were also secreted in large amounts during(More)
SecA is an important component of protein translocation in bacteria, and exists in soluble and membrane-integrated forms. Most membrane prediction programs predict SecA as being a soluble protein, with the exception of TMpred and Top-Pred. However, the membrane associated predicted segments by TMpred and TopPred are inconsistent across bacterial species in(More)
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite of these considerable results, the existing methods lack the ability to explain the process of how a learning result is reached and why a prediction decision is made. The(More)
Obesity is an increasing public health concern worldwide. According to the latest Organization for Economic Co-operation and Development (OECD) report (2014), the incidence of child obesity in Korea has exceeded the OECD average. To better understand and control this condition, the present study examined the composition of the gut microbial community in(More)
The horse (Equus ferus caballus) is one of the earliest domesticated species and has played an important role in the development of human societies over the past 5,000 years. In this study, we characterized the genome of the Marwari horse, a rare breed with unique phenotypic characteristics, including inwardly turned ear tips. It is thought to have(More)
The explanation of a decision is important for the acceptance of machine learning technology in bioinformatics applications such as protein structure prediction. In past research, we have already combined SVM with decision tree to extract rules for understanding transmembrane segments prediction. However, rules we have gotten are as many as about 20,000.(More)
The full extent of chromosomal alterations and their biological implications in early breast carcinogenesis has not been well examined. In this study, we aimed to identify chromosomal alterations associated with poor prognosis in early-stage breast cancers (EBC). A total of 145 EBCs (stage I and II) were examined in this study. We analyzed copy number(More)