• Molecules and Cells
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• v.37 no.6
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• pp.473-479
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• 2014

Spermatogonial stem cells (SSCs, also called germline stem cells) are self-renewing unipotent stem cells that produce differentiating germ cells in the testis. SSCs can be isolated from the testis and cultured in vitro for long-term periods in the presence of feeder cells (often mouse embryonic fibroblasts). However, the maintenance of SSC feeder culture systems is tedious because preparation of feeder cells is needed at each subculture. In this study, we developed a Matrigel-based feeder-free culture system for long-term propagation of SSCs. Although several in vitro SSC culture systems without feeder cells have been previously described, our Matrigel-based feeder-free culture system is time- and cost-effective, and preserves self-renewability of SSCs. In addition, the growth rate of SSCs cultured using our newly developed system is equivalent to that in feeder cultures. We confirmed that the feeder-free cultured SSCs expressed germ cell markers both at the mRNA and protein levels. Furthermore, the functionality of feeder-free cultured SSCs was confirmed by their transplantation into germ cell-depleted mice. These results suggest that our newly developed feeder-free culture system provides a simple approach to maintaining SSCs in vitro and studying the basic biology of SSCs, including determination of their fate.

• Bulletin of the Korean Chemical Society
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• v.25 no.7
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• pp.1061-1064
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• 2004

Molecular visualization software has the common objective of manipulation and interpretation of data from numerical simulations. They visualize many complicated molecular structures with personal computer and workstation, to help analyze a large quantity of data produced by various computational methods. However, users are often discouraged from using these tools for visualization and analysis due to the difficult and complicated user interface. In this regard, we have developed an easy-to-use three-dimensional molecular visualization and analysis program named POSMOL. This has been developed on the Microsoft Windows platform for the easy and convenient user environment, as a compact program which reads outputs from various computational chemistry software without editing or changing data. The program animates vibration modes which are needed for locating minima and transition states in computational chemistry, draws two and three dimensional (2D and 3D) views of molecular orbitals (including their atomic orbital components and these partial sums) together with molecular systems, measures various geometrical parameters, and edits molecules and molecular structures.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.17-20
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• 2000

Structural genomics aims to provide a good experimental structure or computational model of every tractable protein in a complete genome. Underlying this goal is the immense value of protein structure, especially in permitting recognition of distant evolutionary relationships for proteins whose sequence analysis has failed to find any significant homolog. A considerable fraction of the genes in all sequenced genomes have no known function, and structure determination provides a direct means of revealing homology that may be used to infer their putative molecular function. The solved structures will be similarly useful for elucidating the biochemical or biophysical role of proteins that have been previously ascribed only phenotypic functions. More generally, knowledge of an increasingly complete repertoire of protein structures will aid structure prediction methods, improve understanding of protein structure, and ultimately lend insight into molecular interactions and pathways. We use computational methods to select families whose structures cannot be predicted and which are likely to be amenable to experimental characterization. Methods to be employed included modern sequence analysis and clustering algorithms. A critical component is consultation of the presage database for structural genomics, which records the community's experimental work underway and computational predictions. The protein families are ranked according to several criteria including taxonomic diversity and known functional information. Individual proteins, often homologs from hyperthermophiles, are selected from these families as targets for structure determination. The solved structures are examined for structural similarity to other proteins of known structure. Homologous proteins in sequence databases are computationally modeled, to provide a resource of protein structure models complementing the experimentally solved protein structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.365-370
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• 2007

Many engineering problems often require the large amount of computing resources for iterative simulations of problems treating many parameters and input files. In order to overcome the situation, this paper proposes an e-Science based computational system. The system exploits the Grid computing technology to establish an integrated web service environment which supports distributed high throughput computational simulations and remote executions. The proposed system provides an easy-to-use parametric study service where a computational service includes real time monitoring. To verify usability of the proposed system, two kinds of applications were introduced. The first application is an Aerospace Integrated Research System (e-AIRS). The e-AIRS adapts the proposed computational system to solve CFD problems. The second one is design and optimization of protein 3-dimensional structures in structural biology.

• Applied Microscopy
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• v.51
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• pp.6.1-6.9
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• 2021

Histopathology is a well-established standard diagnosis employed for the majority of malignancies, including breast cancer. Nevertheless, despite training and standardization, it is considered operator-dependent and errors are still a concern. Fractal dimension analysis is a computational image processing technique that allows assessing the degree of complexity in patterns. We aimed here at providing a robust and easily attainable method for introducing computer-assisted techniques to histopathology laboratories. Slides from two databases were used: A) Breast Cancer Histopathological; and B) Grand Challenge on Breast Cancer Histology. Set A contained 2480 images from 24 patients with benign alterations, and 5429 images from 58 patients with breast cancer. Set B comprised 100 images of each type: normal tissue, benign alterations, in situ carcinoma, and invasive carcinoma. All images were analyzed with the FracLac algorithm in the ImageJ computational environment to yield the box count fractal dimension (Db) results. Images on set A on 40x magnification were statistically different (p = 0.0003), whereas images on 400x did not present differences in their means. On set B, the mean Db values presented promising statistical differences when comparing. Normal and/or benign images to in situ and/or invasive carcinoma (all p < 0.0001). Interestingly, there was no difference when comparing normal tissue to benign alterations. These data corroborate with previous work in which fractal analysis allowed differentiating malignancies. Computer-aided diagnosis algorithms may beneficiate from using Db data; specific Db cut-off values may yield ~ 99% specificity in diagnosing breast cancer. Furthermore, the fact that it allows assessing tissue complexity, this tool may be used to understand the progression of the histological alterations in cancer.

• Journal of Korean Neurosurgical Society
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• v.61 no.3
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• pp.292-301
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• 2018

Medulloblastoma is the most common malignant brain tumor of childhood and remains a major cause of cancer related mortality in children. Significant scientific advancements have transformed the understanding of medulloblastoma, leading to the recognition of four distinct clinical and molecular subgroups, namely wingless (WNT), sonic hedgehog, group 3, and group 4. Subgroup classification combined with the recognition of subgroup specific molecular alterations has also led to major changes in risk stratification of medulloblastoma patients and these changes have begun to alter clinical trial design, in which the newly recognized subgroups are being incorporated as individualized treatment arms. Despite these recent advancements, identification of effective targeted therapies remains a challenge for several reasons. First, significant molecular heterogeneity exists within the four subgroups, meaning this classification system alone may not be sufficient to predict response to a particular therapy. Second, the majority of novel agents are currently tested at the time of recurrence, after which significant selective pressures have been exerted by radiation and chemotherapy. Recent studies demonstrate selection of tumor sub-clones that exhibit genetic divergence from the primary tumor, exist within metastatic and recurrent tumor populations. Therefore, tumor resampling at the time of recurrence may become necessary to accurately select patients for personalized therapy.

• BMB Reports
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• v.37 no.1
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• pp.83-92
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• 2004

As a result of the enormous amount of information that has been collected with E. coli over the past half century (e.g. genome sequence, mutant phenotypes, metabolic and regulatory networks, etc.), we now have detailed knowledge about gene regulation, protein activity, several hundred enzyme reactions, metabolic pathways, macromolecular machines, and regulatory interactions for this model organism. However, understanding how all these processes interact to form a living cell will require further characterization, quantification, data integration, and mathematical modeling, systems biology. No organism can rival E. coli with respect to the amount of available basic information and experimental tractability for the technologies needed for this undertaking. A focused, systematic effort to understand the E. coli cell will accelerate the development of new post-genomic technologies, including both experimental and computational tools. It will also lead to new technologies that will be applicable to other organisms, from microbes to plants, animals, and humans. E. coli is not only the best studied free-living model organism, but is also an extensively used microbe for industrial applications, especially for the production of small molecules of interest. It is an excellent representative of Gram-negative commensal bacteria. E. coli may represent a perfect model organism for systems biology that is aimed at elucidating both its free-living and commensal life-styles, which should open the door to whole-cell modeling and simulation.

• Molecules and Cells
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• v.26 no.3
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• pp.228-235
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• 2008

Thiol-dependent redox systems are involved in regulation of diverse biological processes, such as response to stress, signal transduction, and protein folding. The thiol-based redox control is provided by mechanistically similar, but structurally distinct families of enzymes known as thiol oxidoreductases. Many such enzymes have been characterized, but identities and functions of the entire sets of thiol oxidoreductases in organisms are not known. Extreme sequence and structural divergence makes identification of these proteins difficult. Thiol oxidoreductases contain a redox-active cysteine residue, or its functional analog selenocysteine, in their active sites. Here, we describe computational methods for in silico prediction of thiol oxidoreductases in nucleotide and protein sequence databases and identification of their redox-active cysteines. We discuss different functional categories of cysteine residues, describe methods for discrimination between catalytic and noncatalytic and between redox and non-redox cysteine residues and highlight unique properties of the redox-active cysteines based on evolutionary conservation, secondary and three-dimensional structures, and sporadic replacement of cysteines with catalytically superior selenocysteine residues.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.354-365
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• 2007

We present novel methods to generate a sequence of shapes that represents the pattern of morphological development or transformation of Bezier curves. The presented methods utilize the intrinsic geometric structures of a Bezier curve that are derived from rib and fan decomposition (RFD). Morphological development based on RFD shows a characteristic pattern of structural growth of a Bezier curve, which is the direct consequence of development path defined by fans. Morphological transformation based RFD utilizes development patterns of source and target curves to mimic the theory of evolutionary developmental biology: although the source and target curves are quite different in shapes, we can easily find similarities in their younger shapes, which makes it easier to set up feature correspondences for blending them. We also show that further controls on base transformation for intensity of feature blending, and extrapolation can compensate the immaturity of blended curves. We demonstrate the experimental results where transformation patterns are smoother and have unique geometric style that cannot be generated using conventional methods based on multi-linear blending.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.155-162
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• 1997

Genetic algorithms(GA) are based on the principles of natural genetics and natural selection. The algorithm searches an optimum design point using information based on the fitness function evaluated for the population of many design points. An application of GA on optimal design of a truss structure is studied. The terminology and the operating procedures common in GA are formalized by establishing similarities between GA and genetics from biology. In using GA, (1) coding of the design variables, (2) formulation of the fitness function, (3) setting of the termination condition, and (4) establishment of the probabilities are essential. These four points are discussed in the paper.