• Genomics & Informatics
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• v.12 no.4
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• pp.165-170
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• 2014

Genome-wide association (GWA) studies have found many important genetic variants that affect various traits. Since these studies are useful to investigate untyped but causal variants using linkage disequilibrium (LD), it would be useful to explore the haplotypes of single-nucleotide polymorphisms (SNPs) within the same LD block of significant associations based on high-density variants from population references. Here, we tried to make a haplotype catalog affecting body mass index (BMI) through an integrative analysis of previously published whole-genome next-generation sequencing (NGS) data of 7 representative Korean individuals and previously known Korean GWA signals. We selected 435 SNPs that were significantly associated with BMI from the GWA analysis and searched 53 LD ranges nearby those SNPs. With the NGS data, the haplotypes were phased within the LDs. A total of 44 possible haplotype blocks for Korean BMI were cataloged. Although the current result constitutes little data, this study provides new insights that may help to identify important haplotypes for traits and low variants nearby significant SNPs. Furthermore, we can build a more comprehensive catalog as a larger dataset becomes available.

• Genomics & Informatics
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• v.9 no.2
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• pp.64-68
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• 2011

Monomelic amyotrophy (MA), also known as Hirayama disease, occurs mainly in young men and manifests as weakness and wasting of the muscles of the distal upper limbs. Here, we sought to identify a genetic basis for MA. Given the predominance of MA in males, we focused on candidate neurological disease genes located on the X chromosome, selecting two X-linked candidate genes, androgen receptor (AR ) and ubiquitin-like modifier activating enzyme 1 (UBA1). Screening for genetic variants using patients' genomic DNA revealed three known genetic variants in the coding region of the AR gene: one nonsynonymous single-nucleotide polymorphism (SNP; rs78686797) encoding Leu57Gln, and two variants of polymorphic trinucleotide repeat segments that encode polyglutamine (CAG repeat; rs5902610) and polyglycine (GGC repeat; rs3138869) tracts. Notably, the Leu57Gln polymorphism was found in two patients with MA from 24 MA patients, whereas no variants were found in 142 healthy male controls. However, the numbers of CAG and GGC repeats in the AR gene were within the normal range. These data suggest that the Leu57Gln polymorphism encoded by the X-linked AR gene may contribute to the development of MA.

• Animal cells and systems
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• v.3 no.1
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• pp.1-7
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• 1999

Gonadotropin-releasing hormone (GnRH) was originally isolated as a hypothalamic peptide that regulates reproduction by stimulating the release of gonadotropins. Using comparative animal models has led to the discovery that GnRH has a more ancient evolutionary origin. Durinq evolution GnRH peptide underwent gene duplication and structural changes to give rise to multiple molecular forms of GnRHs. Mammalian GnRH initially considered to be the sole molecular form, is now grouped as a family of peptides along with GnRH variants determined from representatives in all classes of vertebrates. Vertebrate species including primates and humanshave more than one GnRH variant in individual brains; a unique GnRH form in the forebrain and chicken IIGnRH in the midbrain. Furthermore, several species of bony fish have three molecular variants of GnRH: salmon GnRH sea-bream GnRH and chicken II GnRH. Also, it has been shown that in addition to the olfactory placodes and the midbrain, there is a third embryonic source of GnRH neurons from the basal diencephalon in birds and fish, which might be true for other vertebrates. Therefore, comparative animal models like fish with discrete sites of expression of three molecular variants of GnRH in individual brains, could provide insight into novel functions of GnRH variants, conservation of gene regulation, and mechanisms governing reproduction in vertebrates.

• Coupled systems mechanics
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• v.6 no.1
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• pp.41-54
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• 2017

Shape-memory alloys (SMA) have interesting behaviors and important mechanical properties due to the solid-solid phase transformation. These phenomena are dominated by the evolution of microstructures. In recent years, the microstructures in SMAs have been studied extensively and modeled using molecular dynamics (MD) simulations. However, it remains difficult to identify the crystal variants in the simulation results, which consist of large numbers of atoms. In the present work, a method is developed to identify the austenite phase and the monoclinic martensite crystal variants in MD results. The transformation matrix of each lattice is calculated to determine the corresponding crystal variant. Evolution of the volume fraction of the crystal variants and the microstructure in Ni-Ti SMAs under thermal and mechanical boundary conditions are examined. The method is validated by comparing MD-simulated interface normals with theoretical solutions. In addition, the results show that, in certain cases, the interatomic potential used in the current study leads to inconsistent monoclinic lattices compared with crystallographic theory. Thus, a specific modification is applied and the applicability of the potential is discussed.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.137-142
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• 2021

Although the internet has gained many conveniences and benefits, it is causing economic and social damage to users due to intelligent malware. Most of the signature-based anti-virus programs are used to detect and defend this, but it is insufficient to prevent malware variants becoming more intelligent. Therefore, we proposes a model that detects and defends the intelligent malware that is pouring out in the paper. The proposed model learns by imaging the characteristics of malware based on deeplearning, and detects newly detected malware variants using the learned model. It was shown that the proposed model detects not only the existing malware but also most of the variants that transform the existing malware.

• Mass Spectrometry Letters
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• v.12 no.3
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• pp.60-65
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• 2021

As a part of the Chromosome-centric Human Proteome Project (C-HPP), we have developed a few algorithms for accurate identification of missing proteins, alternative splicing variants, single amino acid variants, and characterization of function unannotated proteins. We have found missing proteins, novel and known ASVs, and SAAVs using LC-MS/MS data from human brain and olfactory epithelial tissue, where we validated their existence using synthetic peptides. According to the neXtProt database, the number of missing proteins in chromosome 11 shows a decreasing pattern. The development of genomic and transcriptomic sequencing techniques make the number of protein variants in chromosome 11 tremendously increase. We developed a web solution named as SAAvpedia for identification and function annotation of SAAVs, and the SAAV information is automatically transformed into the neXtProt web page using REST API service. For the 73 uPE1 in chromosome 11, we have studied the function annotaion of CCDC90B (NX_Q9GZT6), SMAP (NX_O00193), and C11orf52 (NX_Q96A22).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3756-3777
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• 2019

Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.

• Phonetics and Speech Sciences
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• v.13 no.1
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• pp.37-44
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• 2021

While recent acoustic studies have reported associations of fronted sibilants (fricatives /s s⁎/ and affricates /tɕ tɕ⁎/) with gender in Seoul Korean, there have not been any studies examining the relationship of the variants with adult speakers' ages. The current study analyzes sibilant productions from 39 adult speakers born between 1942 and 2008 (19 females) in terms of spectral peak frequencies (SPFs) in frication, an acoustic index of place of articulation (POA). The results indicate some phonetic contexts where higher sibilant SPFs, i.e., fronter POAs, are associated with younger adults and those fronted variants are realized in a gender-differentiated manner -- tense affricates and word-initial tense fricatives before /i/ in the females' productions, and word-medial tense fricatives before /a/ in the males' productions. The findings confirm that the distributions of the fronted sibilants are accounted for not only by the speakers' gender but also by their ages, indicating that the fronted variants are innovative forms of realizing sibilants in Seoul Korean. In addition, the current results convincingly show that the fronted sibilant variants are not mere reflections of individuals' physiological differences since they are not observed across all of the examined phonetic contexts.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.219-230
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• 2022

In implementing a robust automatic target recognition(ATR) system with synthetic aperture radar(SAR) imagery, one of the most important issues is accurate classification of target variants, which are the same targets with different serial numbers, configurations and versions, etc. In this paper, a deep learning network with channel attention modules is proposed to cope with the recognition problem for target variants based on the previous research findings that the channel attention mechanism selectively emphasizes the useful features for target recognition. Different from other existing attention methods, this paper employs the channel attention modules without dimensionality reduction along the channel direction from which direct correspondence between feature map channels can be preserved and the features valuable for recognizing SAR target variants can be effectively derived. Experiments with the public benchmark dataset demonstrate that the proposed scheme is superior to the network with other existing channel attention modules.

• IMMUNE NETWORK
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• v.23 no.2
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• pp.13.1-13.24
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• 2023

The coronavirus disease 2019 (COVID-19) pandemic is one of the most consequential global health crises in over a century. Since its discovery in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to mutate into different variants and sublineages, rendering previously potent treatments and vaccines ineffective. With significant strides in clinical and pharmaceutical research, different therapeutic strategies continue to be developed. The currently available treatments can be broadly classified based on their potential targets and molecular mechanisms. Antiviral agents function by disrupting different stages of SARS-CoV-2 infection, while immune-based treatments mainly act on the human inflammatory response responsible for disease severity. In this review, we discuss some of the current treatments for COVID-19, their mode of actions, and their efficacy against variants of concern. This review highlights the need to constantly evaluate COVID-19 treatment strategies to protect high risk populations and fill in the gaps left by vaccination.