• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.632-642
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• 2004

The modern softwares have features of modularity and extensibility, and there are several researches on extensible programming languages and compilers. In this paper, we introduce Argos programming language, which provides the extensibility with the concept of plugin languages. A plugin language is used to define a method of a class, and the plugin language processors can be added and replaced dynamically The plugin languages may be used to support multiparadigm programming or domain specific languages.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.605-614
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• 2003

In this paper we introduce a new style multiparadigm language named Argos which applies a compositional approach [20] to multiparadigm programming. Argos is a superset of the Java, and its grammar has an extension point which allows other languages to be used in Argos programs. Therefore, Argos can support object-oriented programming and multiparadigm programming by enabling each method in a class to be implemented with one of the Java, C, Prolog, Python, and XML languages. Since Argos allows the existing languages to be used, it has advantages such as easiness of learning and high reusability. The Argos compiler is implemented according to the delegating compiler object (DCO) model[28,29]. The compiler partitions a program Into several parts according to the languages used in methods and delivers the parts the languages' processors which compile the parts.

• Journal of Microbiology and Biotechnology
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• v.32 no.3
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• pp.365-377
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• 2022

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.