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

• Journal of KIISE:Software and Applications
• /
• v.31 no.3
• /
• pp.343-352
• /
• 2004

Recently, the information processing of ever increasing bio-related data is becoming a very important issue. One of the main sources of these bio-data comes with the form of biopathways, which includes molecular transactions and processes that are part of biochemical systems. The information represented by biopathways includes various organic relations among its components. However, most of the current systems to represent biopathways have been initially developed without computer processing in mind, and hence suffer from inconsistencies and ambiguities. In this paper, we propose an improved notation, called UniPath, for clear and systematic representation of biopathways. The proposed system is designed to provide a unified representation of metabolic and regulatory pathways. We also designed and implemented a graphic editor for UniPath to draw biopathwavs map according to the proposed notation. The graphic editor is designed so that biopathway data can be easily transformed into XML format.

• Genomics & Informatics
• /
• v.7 no.3
• /
• pp.171-174
• /
• 2009

The characteristics of metabolic pathways make them particularly amenable to layered graph drawing methods. This paper presents a visual Java-based tool for drawing and annotating biological pathways in two- and a-half dimensions (2.5D) as an alternative to three-dimensional (3D) visualizations. Such visualization allows user to display different groups of clustered nodes, in different parallel planes, and to see a detailed view of a group of objects in focus and its place in the context of the whole system. This tool is an extended version of J2dPathway.

• BMB Reports
• /
• v.57 no.1
• /
• pp.30-39
• /
• 2024

Directed evolution (DE) of desired locus by targeted random mutagenesis (TRM) tools is a powerful approach for generating genetic variations with novel or improved functions, particularly in complex genomes. TRM-based DE involves developing a mutant library of targeted DNA sequences and screening the variants for the desired properties. However, DE methods have for a long time been confined to bacteria and yeasts. Lately, CRISPR/Cas and DNA deaminase-based tools that circumvent enduring barriers such as longer life cycle, small library sizes, and low mutation rates have been developed to facilitate DE in native genetic environments of multicellular organisms. Notably, deaminase-based base editing-TRM (BE-TRM) tools have greatly expanded the scope and efficiency of DE schemes by enabling base substitutions and randomization of targeted DNA sequences. BE-TRM tools provide a robust platform for the continuous molecular evolution of desired proteins, metabolic pathway engineering, creation of a mutant library of desired locus to evolve novel functions, and other applications, such as predicting mutants conferring antibiotic resistance. This review provides timely updates on the recent advances in BE-TRM tools for DE, their applications in biology, and future directions for further improvements.