• Journal for History of Mathematics
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• v.29 no.4
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• pp.243-254
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• 2016

This research identifies the elements of the methodologies of Newton's discovery of his dynamics. These methodologies involve the transformation of preceding theoretical concepts and the discovery of common cause. This essay consists of two parts within historical case studies of Newton's works. The elements of the method of discovery consists of the transformation of preceding concepts and the identification of common cause in the formation of the research program's hard cores and protective belts. Newton transformed their predecessors' concepts to find out appropriate common causes in his dynamical theory. The transformed theoretical concepts are synthesized to be constructed as the elements of common cause which provide the foundations of Newtonian research programs.

• Journal of Korean Philosophical Society
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• v.148
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• pp.157-181
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• 2018

The aim of this essay is to identify elements of methodologies to investigate the development of Newtonian dynamics. This methodology involves the transformation and synthesis of preceding theories. My essay attempts to confirm my assertion by analyzing historical case of Newton's discovery of his dynamics. While discovering his mechanistic theory, Newton reconstructed theoretical concepts and structures of intellectual predecessors, such as Aristotle, Descartes, Galileo, and Kepler. Newton's synthesis was possible only after carefully reconstructing the appropriate and useful ideas of previous natural philosophers' ideas. As a result, Newtonian dynamics are completed with these modified and integrated concepts incorporated into Newton's law of motion and space-time concepts. This study consists of two parts. First, Lakatos' research program has been applied in order to analyze the structure of Newtonian dynamics. Second, the aforementioned methodologies of discovery are distilled from the case study.

• Journal of Preventive Medicine and Public Health
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• v.49 no.2
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• pp.129-133
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• 2016

Objectives: The systematic review (SR) is a research methodology that aims to synthesize related evidence. Updating previously conducted SRs is necessary when new evidence has been produced, but no consensus has yet emerged on the appropriate update methodology. The authors have developed a new SR update method called 'adaptive meta-analysis' (AMA) using the 'cited by', 'similar articles', and 'related articles' citation discovery tools in the PubMed and Scopus databases. This study evaluates the usefulness of these citation discovery tools for updating SRs. Methods: Lists were constructed by applying the citation discovery tools in the two databases to the articles analyzed by a published SR. The degree of overlap between the lists and distribution of excluded results were evaluated. Results: The articles ultimately selected for the SR update meta-analysis were found in the lists obtained from the 'cited by' and 'similar' tools in PubMed. Most of the selected articles appeared in both the 'cited by' lists in Scopus and PubMed. The Scopus 'related' tool did not identify the appropriate articles. Conclusions: The AMA, which involves using both citation discovery tools in PubMed, and optionally, the 'related' tool in Scopus, was found to be useful for updating an SR.

• Proceedings of the Korean Society of Toxicology Conference
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• 2003.10b
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• pp.84-85
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• 2003

The process of drug development has seen major changes over the last two decades with the movement away from standard small molecule drug discovery programs, through computer-assisted drug design methodologies towards biotechnologically derived products. The aim of duplication of endogenously active materials to be administered exogenously has enormous impact on development practices and evaluation of safety.(omitted)

• BMB Reports
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• v.37 no.1
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• pp.28-34
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• 2004

The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.

• Journal of Integrative Natural Science
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• v.5 no.4
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• pp.216-219
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• 2012

Structure-based drug design possibly benefit from in silico methods that precisely predict the binding affinity of small molecules to target macromolecules. There are many limitations arise from the difficulty of predicting the binding affinity of a small molecule to a biological target with the current scoring functions. There is thus a strong interest in novel methodologies based on MD simulations that claim predictions of greater accuracy than current scoring functions, helpful for a regular use designed for drug discovery in the pharmaceutical industry. Herein, we report a short review on free energy calculations using MMPBSA method a useful method in structure based drug discovery.

• Journal of Integrative Natural Science
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• v.7 no.2
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• pp.75-78
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• 2014

Computer-aided drug design uses computational chemistry to discover, enhance, or study drugs and related biologically active molecules. It is now proved to be effective in reducing costs and speeding up drug discovery. In this short review, we discussed on the importance of combining molecular docking and molecular dynamics simulation methodologies. We also reviewed the importance of protein flexibility, refinement of docked complexes using molecular dynamics and the use of free energy calculations for the calculation of accurate binding energies has been reviewed.

• Genomics & Informatics
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• v.13 no.3
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• pp.76-80
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• 2015

Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

• Genomics & Informatics
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• v.6 no.1
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• pp.14-17
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• 2008

GENDISCAN study (Gene Discovery for Complex traits in Asian population of Northeast area) was designed to incorporate methodologies which enhance the power to identify genetic variations underlying complex disorders. Use of population isolates as the target population is a unique feather of this study. However, population isolates may have hidden inbreeding structures which can affect the validity of the study. To understand how this issue may affect results of GENDISCAN, we estimated inbreeding coefficients in two study populations in Mongolia. We analyzed the status of Hardy-Weinberg Equilibrium (HWE), polymorphism information contents (PIC), heterozygosity, allelic diversity, and inbreeding coefficients, using 317 and 1,044 STR (short tandem repeat) markers in Orkhontuul and Dashbalbar populations. HWE assumptions were generally met in most markers (88.6% and 94.2% respectively), and single marker PIC ranged between 0.2 and 0.9. Inbreeding coefficients were estimated to be 0.0023 and 0.0021, which are small enough to assure that conventional genetic analysis would work without any specific modification. We concluded that the population isolates used in GENDISCAN study would not present significant inflation of type I errors from inbreeding effects in its gene discovery analysis.

• Bulletin of the Korean Chemical Society
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• v.34 no.9
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• pp.2680-2684
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• 2013

Protein kinases (PKs) are an important source of drug targets, especially in oncology. With 500 or more kinases in the human genome and only few kinase inhibitors approved, kinase inhibitor discovery is becoming more and more valuable. Because the discovery of kinase inhibitors with an increased selectivity is an important therapeutic concept, many researchers have been trying to address this issue with various methodologies. Although many attempts to predict the activity and selectivity of kinase inhibitors have been made, the issue of selectivity has not yet been resolved. Here, we studied kinase selectivity by generating predictive models and analyzing their descriptors by using kinase-profiling data. The 5-fold cross-validation accuracies for the 51 models were between 72.4% and 93.7% and the ROC values for all the 51 models were over 0.7. The phylogenetic tree based on the descriptor distance is quite different from that generated on the basis of sequence alignment.