• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.3-6
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• 2007

KISTI(Korea Institute of Science & Technology Information) CCBB(Center for Computational Biology and Bioinformatics) Website has been providing bioinformatics contents(databases and analysis tools) services to construct IT-based bioinformatics infrastructure. It also carries out the services to support domestic bioinformatics R&D activity and to construct the infrastructure. But, these services are not actively available because this CCBB website is not wellknown to users. Therefore, we performed the user survey for the researchers who are studying in the field of biological science. The items of this survey consist of subjects on bioinformatics databases, analysis tools and BioInfoNet. After the user survey is rearranged and analyzed, the result of survey will be used to provide the good service to the users who are need of bioinformatics infrastructure such as databases and analysis tools etc.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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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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• v.17 no.sup3
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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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• v.55 no.6
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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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• v.37 no.4
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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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• v.32 no.4
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• pp.1127-1128
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• 2011

• Proceedings of the Korean Society of Life Science Conference
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• 2006.09a
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• pp.63.2-63.2
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• 2006

• Proceedings of the Korean Biophysical Society Conference
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• 2002.06b
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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)

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.08a
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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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• v.2 no.3
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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.