• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.3-6
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• 2007

한국과학기술정보연구원(KISTI) CCBB(Center for Computational Biology & Bioinformatics) 웹사이트에서는 IT 기반의 생명정보 인프라 구축을 위해 생명정보 콘텐트(DB, 분석도구) 21종을 구축 서비스하고 있다. 또한, 국내 생명정보 연구개발 지원 및 인프라 조성을 위한 업무를 수행하고 있다. 하지만 CCBB에 대한 인식이 널리 확산되어 있지 않아 CCBB에서 구축하고 개발된 생명정보 콘텐트가 활발히 이용되지 못하고 있는 실정이다. 따라서 생명과학 분야의 연구자를 대상으로 이용자조사를 실시하였다. 조사내용은 생명정보 데이터 베이스 및 분석도구 이용에 관한 내용과 생명과학 연구학술정보 네트워크(BioInfoNet)에 관한 내용으로 구성하였다. 설문조사를 통해 나타난 결과는 정리 분석한 후 이용자들이 필요로 하는 데이터베이스, 분석도구 등 생명정보 인프라를 제공하는데 활용될 것이다.

• Asian Pacific Journal of Cancer Prevention
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• 제17권sup3호
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• pp.65-70
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• 2016

Lung cancer is one of the most common malignancies in the world. Its incidence and mortality rates are on the rise in Pakistan. However, epidemiological studies to identify common lung cancer determinants in the Pakistani population have been limited. In this study, data of 440 cases and 323 controls were collected from different hospitals in Peshawar and Islamabad, along with information about socio-demographic factors including age, sex and smoking. Univariate and multi-factorial analyses of socio-demographic factors in association with each other were also performed. Overall survival analysis highlighted that, out of 440 patients in the lung cancer dataset, 204 people were uncensored with a median survival time of 13 months (95% CI=12-18). There were 41 femaleand 399 male patients. Differences were observed between length of survival in the males and females (${\chi}12$ = 6.1; p-value = 0.01). Gender was observed to be significantly related to survival (p-value< 0.01), with better survival in females (hazard ratio=2). Cox regression was extended to adjust for the covariate age (z = 2.5; p-value = 0.02). Survival analysis was also performed on the basis of smoking groups (current smokers, former smokers and never smoked individuals) and smoking duration (smoking duration >10 years, <10 years and never smoked). Smoking duration was significantly associated with survival (p-value < 0.01), with better survival in never smokers in comparison to both smoking for greater or less than 10 years. Strong associations were observed for smoking group with duration greater than 10 years, OR=6.1(3.9-9.5) on univariate and multifactorial analysis OR=11.3(CI=6.8-19.3).

• Asian Pacific Journal of Cancer Prevention
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• 제17권sup3호
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• pp.71-75
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• 2016

Pancreatic cancer is a leading cause of fatality worldwide. Several population studies have been conducted on genetic diagnosis of pancreatic cancer but the results from epidemiologic studies are very limited. CYP17A gene has a role in disease formation but its influence on pancreatic cancer is unclear. A polymorphism in the 5'UTR promoter region of CYP17A1-34T/C (A1/A2) has been associated with multiple cancers. The aim of the current study was to assess associations of this polymorphism and socio-demographic risk factors with pancreatic cancer. A total of 255 and 320 controls were enrolled in the study, and were genetically analyzed through PCR-RFLP. Statistical analysis was conducted with observed genotype frequencies and odds ratios (ORs) and 95% CIs were estimated using unconditional logistic regression. The impact of socio-demographic factors was accessed through Kaplen-Meir analysis. According to our results, the A2/A2 genotype was significantly associated with pancreatic cancer (OR=2.1, 95%CI = 1.3-3.5). Gender female (OR=2.6, 95%CI=1.8-3.7), age group 80s/80+ years (OR=2.2, 95% CI=1.2-4), smoking both former (OR=4.6, 95% CIs=2.5-8.8) and current (OR=3.6, 95% CI=2-6.7), and family history (OR=7.1; 95%CI = 4.6-11.4) were also found associated with increased risk. Current study suggests that along with established risk factors for pancreatic cancer CYP17A1-34T/C may play a role. However, on the basis of small sample size the argument cannot be fully endorsed and larger scale studies are recommended.

• Journal of Animal Science and Technology
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• 제55권6호
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• pp.515-520
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• 2013

Pyruvate kinase M2 (PKM2) is a key regulatory enzyme in the glycolytic pathway. It is one of four pyruvate kinase isoenzymes that widely differ in their occurrence according to tissue type. PKM2 is expressed in differentiated tissues, such as fat tissues, lung, as well as normal proliferating cells, embryonic cells, and tumor cells. The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) in the PKM2 gene with meat quality traits in Berkshire pigs. We detected a SNP (g.34341 A>G) in the 3'UTR region of the PKM2 gene in 670 Berkshire pigs through DNA sequencing. Three genotypes, AA, AG, and GG, were found for this SNP, but based on an association analysis with meat quality traits, genotype AA was significantly associated with thicker back fat than genotype GG (p=0.027). Therefore, the g.34341 A>G polymorphism in the 3'UTR region of the porcine PKM2 gene could be applied in pig breeding programs to improve back fat thickness.

• Reproductive and Developmental Biology
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• 제37권4호
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• pp.205-211
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• 2013

The swine is one of the most widespread mammalian throughout the whole world. Presently, many studies concerning microsatellites in swine, especially domestic pigs, have been carried out in order to investigate general diversity patterns among either populations or breeds. Until now, a lot of time and effort spend into a single PCR method. But simple and more rapid multiplex PCR methods have been developed. The purpose of this study is to develop a robust set of microsatellites markers (MS marker) for traceability and individual identification. Using multiplex-PCR method with 23 MS marker divided 2 set, various alleles occurring to 5 swine breed (Berkshire, Landrace, Yorkshire, Duroc and Korea native pig) used markers to determine allele frequency and heterozygosity. MS marker found 4 alleles at SW403, S0227, SWR414, SW1041 and SW1377. The most were found 10 alleles at SW1920. Heterozygosity represented the lowest value of 0.102 at SWR414 and highest value of 0.861 at SW1920. So, it was recognized appropriate allele frequency for individual identification in swine. Using multiplex-PCR method, MS markers used to determine individual identification biomarker and breed-specific marker for faster, more accurate and lower analysis cost. Based on this result, a scientific basis was established to the existing pedigree data by applying genetics additionally. Swine traceability is expected to be very useful system and be conducted nationwide in future.

• Bulletin of the Korean Chemical Society
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• 제32권4호
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• pp.1127-1128
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• 2011

• 한국생명과학회:학술대회논문집
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• 한국생명과학회 2006년도 제47회 학술심포지움 및 추계국제학술대회
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• pp.63.2-63.2
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• 2006

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 2002년도 제9회 학술 발표회 프로그램과 논문초록
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• pp.14-14
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• 2002

Genome project is a research for discovering genomic information. Human genome sequence, under the title of HGP(human genome project), was drafted successfully at the end of June, 2000. And the academic world soon predicted that related research field would be activated and since then bioinformatics has been in the spotlight.(omitted)

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보학 국제심포지엄
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• pp.103-127
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• 2001

Gene expression studies require statistical experimental designs and validation before laboratory confirmation. Various clustering approaches, such as hierarchical, Kmeans, SOM are commonly used for unsupervised learning in gene expression data. Several classification methods, such as gene voting, SVM, or discriminant analysis are used for supervised lerning, where well-defined response classification is possible. Estimating gene-condition interaction effects require advanced, computationally-intensive statistical approaches.

• IMMUNE NETWORK
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• 제2권3호
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• pp.125-132
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• 2002

In the past, bioinformatics was often regarded as a difficult and rather remote field, practiced only by computer scientists and not a practical tool available to biologists. However, the various on-going genome projects have had a serious impact on biological sciences in various ways and now there is little doubt that bioinformatics is an essential part of the research environment, with a wealth of biological information to analyze and predict. Fully sequenced genomes made us to have additional insights into the functional properties of the encoded proteins and made it possible to develop new tools and schemes for functional biology on a proteomic scale. Among those are the yeast two-hybrid system, mass spectrometry and microarray: the technology of choice to detect protein-protein interactions. These functional insights emerge as networks of interacting proteins, also known as "pathway informatics" or "interactomics". Without exception it is no longer possible to make advances in the signaling/regulatory pathway studies without integrating information technologies with experimental technologies. In this paper, we will introduce the databases of protein interaction worldwide and discuss several challenging issues regarding the actual implementation of databases.