• Genomics & Informatics
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• v.11 no.4
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• pp.191-199
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• 2013

High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.125.1-125
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• 2003

Pepper anthracnose is one of the major limiting factors in pepper production. Boring last over 10 years, Colletotrichum gloeosporioides has been known as the most prevalent species among five Colletotrichum spp. involved as anthracnose causing agents. Recently, however, the change of major species with pepper anthracnose has been proposed. Identification study was peformed on 12 test isolates collected from anthracnose disease symptoms on pepper during 2001-2002 and 25 reference isolates obtained from several other host plants. The identification of the isolates with morphological observation and IfS region sequence comparison resulted that 11 ones from 12 test isolates colleted from pepper anthracnose during 2001-2002 were identified as C. acutatum. PCR using species-specific primers designed from ITS region sequence suggested a rapid diagnosis method in identifying C. acutatum from C. gloeosporioides.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.3-26
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• 2001

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the cross correlation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is ...

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.357-364
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• 1996

This paper presents a new blind identification method of nonminimum phase FIR systems without employing higher-order statistics. It is based on the observation that the absolute mean of a second-order white sequence can measure the higher-order whiteness of the sequence. The proposed method may be a new alternative way to the higher-order statistics approaches. Some computer simulations show that the absolute mean is exactly estimated and the proposed method can overcome the disadvantages of the higher-order statistics approaches.

• Entomological Research
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• v.48 no.5
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• pp.339-347
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• 2018

Seven different strains of Beauveria bassiana were used in a bioassay on Pieris rapae larvae. The results showed that an B. bassiana strain showed relatively high pathogenicity towards P. rapae larvae. The adjusted mortality rate was 92.86 %, and the infection rate was 85.71 % in 10 days post inoculation. Molecular identification was performed to identify the unknown strain. Internal Transcribed Spacer sequence analysis showed that the polymerase chain reaction amplicon length of the unknown strain of Beauveria sp. was 573 bp, and sequence similarity to the known B. bassiana sequences in the NCBI database was 99 %. The B. bassiana strain was named Bb01. The changes of proteins and PPO of P. rapae larvae infected by B. bassiana Bb01 strain at different times was determined. The activity of PPO increased in 1-6 d and decreased in 7 d again after inoculation. The B. bassiana invaded into the insect body affected the balance of the proteins and PPO.

• Animal cells and systems
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• v.3 no.1
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• pp.69-72
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• 1999

A tandemly repeated DNA sequence was identified and characterized y the combined RAPD and FISH data from a total genomic DNA of Welsh onion (Allium fistulosum). A clone containing this repeating sequence was selected and sequenced. This repeating unit of 314 bp inserted into pAf 072 contained 54.1% adenine and thymine residues, and showed the primer sequence used, 5'-GAAACGGGTG-3', in both terminals of the sequence. Fluorescence in situ hybridization using this tandemly repeated sequence as a probe indicated that the detected sites were coincident with the major C-banded constitutive heterochromatin in the terminal regions of both arms of all 6 chromosomes.

• Journal of Biosystems Engineering
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• v.16 no.2
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• pp.111-117
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• 1991

An empirical model for diesel engine control was obtained using a system identification method. A pseudo-random binary sequence was used as an input signal. Spectral anaylsis was used to find the frequency response of system. Model parameters of transfer functions were obtained using nonlinear regression.

• Genomics & Informatics
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• v.11 no.4
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• pp.272-276
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• 2013

Sequence analysis of the 16S rRNA gene has been widely used for the classification of microorganisms. However, we have been unable to clearly identify five Flavobacterium species isolated from a freshwater by using the gene as a single marker, because the evolutionary history is incomplete and the pace of DNA substitutions is relatively rapid in the bacteria. In this study, we tried to classify Flavobacterium species through multilocus sequence analysis (MLSA), which is a practical and reliable technique for the identification or classification of bacteria. The five Flavobacterium species isolated from freshwater and 37 other strains were classified based on six housekeeping genes: gyrB, dnaK, tuf, murG, atpA, and glyA. The genes were amplified by PCR and subjected to DNA sequencing. Based on the combined DNA sequence (4,412 bp) of the six housekeeping genes, we analyzed the phylogenetic relationship among the Flavobacterium species. The results indicated that MLSA, based on the six housekeeping genes, is a trustworthy method for the identification of closely related Flavobacterium species.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.141-144
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• 1999

The authors have recently developed a new method for identification of Volterra kernels of nonlinear systems by use of pseudorandom M-sequence and correlation technique. And it is shown that nonlinear systems which can be expressed by Volterra series expansion are well identified by use of this method. However, there exist many nonlinear systems which can not be expressed by Volterra series mathematically. A nonlinear system having backlash type nonliear element is one of those systems, since backlash type nonlinear element has multi-valued function between its input and output. Since Volterra kernel expression of nonlinear system is one of the most useful representations of non-linear dynamical systems, it is of interest how the method of Volterra kernel identification can be ar plied to such backlash type nonlinear system. The authors have investigated the effect of application of Volterra kernel identification to those non-linear systems which, accurately speaking, is difficult to express by use of Volterra kernel expression. A pseudorandom M-sequence is applied to a nonlinear backlash-type system, and the crosscorrelation function is measured and Volterra kernels are obtained. The comparison of actual output and the estimated output by use of measured Volterra kernels show that we can still use Volterra kernel representation for those backlash-type nonlinear systems.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.314-319
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• 2019

Computing chromagram similarity is indispensable in constructing cover song identification system. This paper proposes a code-based chromagram similarity to reduce the computational and the storage costs for cover song identification. By learning a song-specific codebook, a chromagram sequence is converted into a code sequence, which results in the reduction of the feature storage cost. We build a lookup table over the learned codebooks to compute chromagram similarity efficiently. Experiments on two music datasets were performed to compare the proposed code-based similarity with the conventional one in terms of cover song search accuracy, feature storage, and computational cost.