Body Height Effect on Brain Volumes in Youth Decreases in Old Age in Koreans

Koh, In-Song Korean Society for Bioinformatics 2011 Interdisciplinary Bio Central (IBC) Vol.3 No.3

The MRI (magnetic resonance imaging) volumetric analysis of the brain was performed in 59 healthy elderly Koreans (aged 62-76 years; 34 male, 25 female) to investigate whether the previously reported significant correlations between body height and brain volumes in the young aged Koreans (20's) still exist in the old aged Koreans (60's and 70's). Unlike previously reported significant correlations in the young aged Koreans, neither the correlation between whole brain volume and body height in male nor the correlation between cerebellar volume and body height in female show any significance in the old aged Koreans. The significant correlation between body height and whole brain volume was still observed when both male and female data were combined (r=0.27, P<0.05), but the correlation coef-ficient and the level of significance markedly decreased from those of previously reported Korean youth data (r=0.67, P<0.01). Simple linear regression analysis shows decrease of explanatory power of height (measured in $r^2$) from 44% in the youth group to 7% in the old age group on the variance of whole brain volume. Multiple linear regression analysis shows that age and sex, rather than height, are major explanatory variables for whole brain volume in the old aged Koreans. The loss of correlations in the aged group is suspected to be mainly due to age related brain volume changes.

IntoPub: A Directory Server for Bioinformatics Tools and Databases

Jung, Dong-Soo,Kim, Ji-Han,Lee, Sang-Hyuk,Lee, Byung-Wook Korean Society for Bioinformatics 2011 Interdisciplinary Bio Central (IBC) Vol.3 No.3

Bioinformatics tools and databases are useful for understanding and processing various biological data. Numerous resources are being published each year. It is not a trivial task to find up-to-date relevant tools and databases. Moreover, no server is available to provide comprehensive coverage on bioinformatics resources in all biological fields. Here, we present a directory server called IntoPub that provides information on web resources. First, we downloaded XML-formatted abstracts containing web URLs from the NCBI PubMed database by using 'ESearch-EFetch' function in the NCBI E-utilities. The information is obtained from abstracts in the PubMed by extracting 'www' or 'http' prefixes. Then, we cu-rate the downloaded abstracts both in automatic and manual fashion. As of July 2011, the IntoPub database has 12,118 abstracts containing web URLs from 174 journals. Our anal-ysis shows that the number of abstracts containing web resources has increased signifi-cantly every year. The server has been tested by many biologists from several countries to get opinion on user satisfaction, usefulness, practicability, and ease of use since January 2010. In the IntoPub web server, users can easily find relevant bioinformatics resources, as compared to searching in PubMed. IntoPub will continue to update and incorporate new web resources from PubMed and other literature databases. IntoPub, available at http://into.kobic.re.kr/, is updated every day.

Urokinase Inhibitor Design Based on Pharmacophore Model Derived from Diverse Classes of Inhibitors

Shui, Liu,Bharatham, Nagakumar,Bharatham, Kavitha,Lee, Keun-Woo Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

A three-dimensional pharmacophore model was developed based on 24 currently available inhibitors, which were rationally selected from 472 compounds with diverse molecular structure and bioactivity, for generating pharmacophore of uPA (Urokinase Plasminogen Activator) inhibitors. The best hypothesis (Hypo1) comprised of five features, namely, one positive ionizable group, one hydrogen-bond acceptor group and three hydrophobic aromatic groups. The correlation coefficient, root mean square deviation and cost difference were 0.973, 0.695, and 94.291 respectively, suggesting that a highly predictive pharmacophore model was successfully obtained. The application of the model showed great success in predicting the activities of 251 known uPA inhibitors (test set) with a correlation coefficient of 0.837, and there was also none of the outcome hypotheses that had similar cost difference and RMS deviation (RMSD) with that of the initial hypothesis generated by Cat-Scramble validation test with 95% confidence level. Accordingly, our model should be reliable in identifying structurally diverse compounds with desired biological activity.

Retrieving Protein Domain Encoding DNA Sequences Automatically Through Database Cross-referencing

Choi, Yoon-Sup,Yang, Jae-Seong,Ryu, Sung-Ho,Kim, Sang-Uk Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

Recent proteomic studies of protein domains require high-throughput and systematic approaches. Since most experiments using protein domains, the modules of protein-protein interactions, require gene cloning, the first experimental step should be retrieving DNA sequences of domain encoding regions from databases. For a large scale proteomic research, however, it is a laborious task to extract a large number of domain sequences manually from several inter-linked databases. We present a new methodology to retrieve DNA sequences of domain encoding regions through automatic database cross-referencing. To extract protein domain encoding regions, it traverses several inter-connected database with validation process. And we applied this method to retrieve all the EGF domain encoding DNA sequences of homo sapiens. This new algorithm was implemented using Python library PAMIE, which enables to cross-reference across distinct databases automatically.

Local structural alignment and classification of TIM barrel domains

Keum, Chang-Won,Kim, Ji-Hong,Jung, Jong-Sun Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

TIM barrel domain is widely studied since it is one of most common structure and mediates diverse function maintaining overall structure. TIM barrel domain's function is determined by local structural environment at the C-terminal end of barrel structure. We classified TIM barrel domains by local structural alignment tool, LSHEBA, to understand characteristics of TIM barrel domain's functionalvariation. TIM barrel domains classified as the same cluster share common structure, function and ligands. Over 80% of TIM barrels in clusters share exactly the same catalytic function. Comparing clustering result with that of SCOP, we found that it's important to know local structural environment of TIM barrel domains rather than overallstructure to understand specific structural detail of TIM barrel function. Non TIM barrel domains were associated to make different domain combination to form a different function. The relationship between domain combination, we suggested expected evolutional history. We finally analyzed the characteristics of amino acids around ligand interface.

Improved Statistical Testing of Two-class Microarrays with a Robust Statistical Approach

Oh, Hee-Seok,Jang, Dong-Ik,Oh, Seung-Yoon,Kim, Hee-Bal Korean Society for Bioinformatics 2010 Interdisciplinary Bio Central (IBC) Vol.2 No.2

The most common type of microarray experiment has a simple design using microarray data obtained from two different groups or conditions. A typical method to identify differentially expressed genes (DEGs) between two conditions is the conventional Student's t-test. The t-test is based on the simple estimation of the population variance for a gene using the sample variance of its expression levels. Although empirical Bayes approach improves on the t-statistic by not giving a high rank to genes only because they have a small sample variance, the basic assumption for this is same as the ordinary t-test which is the equality of variances across experimental groups. The t-test and empirical Bayes approach suffer from low statistical power because of the assumption of normal and unimodal distributions for the microarray data analysis. We propose a method to address these problems that is robust to outliers or skewed data, while maintaining the advantages of the classical t-test or modified t-statistics. The resulting data transformation to fit the normality assumption increases the statistical power for identifying DEGs using these statistics.

Informatics for protein identification by tandem mass spectrometry; Focused on two most-widely applied algorithms, Mascot and SEQUEST

Sohn, Chang-Ho,Jung, Jin-Woo,Kang, Gum-Yong,Kim, Kwang-Pyo Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

Mass spectrometry (MS) is widely applied for high throughput proteomics analysis. When large-scale proteome analysis experiments are performed, it generates massive amount of data. To search these proteomics data against protein databases, fully automated database search algorithms, such as Mascot and SEQUEST are routinely employed. At present, it is critical to reduce false positives and false negatives during such analysis. In this review we have focused on aspects of automated protein identification using tandem mass spectrometry (MS/MS) spectra and validation of the protein identifications of two most common automated protein identification algorithms Mascot and SEQUEST.

Proteomics Data Analysis using Representative Database

Kwon, Kyung-Hoon,Park, Gun-Wook,Kim, Jin-Young,Park, Young-Mok,Yoo, Jong-Shin Korean Society for Bioinformatics and Systems Biol 2007 Bioinformatics and Biosystems Vol.2 No.2

In the proteomics research using mass spectrometry, the protein database search gives the protein information from the peptide sequences that show the best match with the tandem mass spectra. The protein sequence database has been a powerful knowledgebase for this protein identification. However, as we accumulate the protein sequence information in the database, the database size gets to be huge. Now it becomes hard to consider all the protein sequences in the database search because it consumes much computing time. For the high-throughput analysis of the proteome, usually we have used the non-redundant refined database such as IPI human database of European Bioinformatics Institute. While the non-redundant database can supply the search result in high speed, it misses the variation of the protein sequences. In this study, we have concerned the proteomics data in the point of protein similarities and used the network analysis tool to build a new analysis method. This method will be able to save the computing time for the database search and keep the sequence variation to catch the modified peptides.

CiNet: GUI based Literature analysis tool using citation information

Lee, Se-Jun,Lee, Kwang-H. Korean Society for Bioinformatics and Systems Biol 2007 Bioinformatics and Biosystems Vol.2 No.1

Scientific literature is the most reliable and comprehensive source of knowledge for scientific and biomedical information. Citation information in the literature is also reliable source for linking between literatures. We proposed CiNet, a graphic user interface based tool that extracts the trend of the research using citation information. We can navigate related literatures and extract keywords from the linked literature using this tool. These extracted keywords will be helpful to researchers who want to survey the information.

Prediction Accuracy Evaluation of Domain and Domain Combination Based Prediction Methods for Protein-Protein Interaction

Han, Dong-Soo,Jang, Woo-Hyuk Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

This paper compares domain combination based protein-protein interaction prediction method with domain based protein-protein interaction method. The prediction accuracy and reliability of the methods are compared using the same prediction technique and interaction data. According to the comparison, domain combination based prediction method has showed superior prediction accuracy to domain based prediction method for protein pairs with fully overlapped domains with protein pairs in learning sets. When we consider that domain combination based method has the effects of assigning a weight to each domain interaction, it implies that we can improve the prediction accuracies of currently available domain or domain combination based protein interaction prediction methods further by developing more advanced weight assignment techniques. Several significant facts revealed from the comparative studies are also described in this paper.