• Proceedings of the Korea Society of Environmental Biology Conference
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• 2001.12a
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• pp.82-82
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• 2001

• Proceedings of the Korea Society of Environmental Biology Conference
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• 2002.05a
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• pp.72-72
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• 2002

• Animal cells and systems
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• v.8
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• pp.45-45
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• 2004

• Journal of Microbiology and Biotechnology
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• v.22 no.8
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• pp.1054-1058
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• 2012

In order to predict biologically significant attributes such as function from protein sequences, searching against large databases for homologous proteins is a common practice. In particular, BLAST and HMMER are widely used in a variety of biological fields. However, sequence-homologous proteins determined by BLAST and proteins having the same domains predicted by HMMER are not always functionally equivalent, even though their sequences are aligning with high similarity. Thus, accurate assignment of functionally equivalent proteins from aligned sequences remains a challenge in bioinformatics. We have developed the FEP-BH algorithm to predict functionally equivalent proteins from protein-protein pairs identified by BLAST and from protein-domain pairs predicted by HMMER. When examined against domain classes of the Pfam-A seed database, FEP-BH showed 71.53% accuracy, whereas BLAST and HMMER were 57.72% and 36.62%, respectively. We expect that the FEP-BH algorithm will be effective in predicting functionally equivalent proteins from BLAST and HMMER outputs and will also suit biologists who want to search out functionally equivalent proteins from among sequence-homologous proteins.

• Experimental and Molecular Medicine
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• v.50 no.11
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• pp.7.1-7.12
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• 2018

Recent findings from The Cancer Genome Atlas project have provided a comprehensive map of genomic alterations that occur in hepatocellular carcinoma (HCC), including unexpected mutations in apolipoprotein B (APOB). We aimed to determine the clinical significance of this non-oncogenetic mutation in HCC. An Apob gene signature was derived from genes that differed between control mice and mice treated with siRNA specific for Apob (1.5-fold difference; P < 0.005). Human gene expression data were collected from four independent HCC cohorts (n = 941). A prediction model was constructed using Bayesian compound covariate prediction, and the robustness of the APOB gene signature was validated in HCC cohorts. The correlation of the APOB signature with previously validated gene signatures was performed, and network analysis was conducted using ingenuity pathway analysis. APOB inactivation was associated with poor prognosis when the APOB gene signature was applied in all human HCC cohorts. Poor prognosis with APOB inactivation was consistently observed through cross-validation with previously reported gene signatures (NCIP A, HS, high-recurrence SNUR, and high RS subtypes). Knowledge-based gene network analysis using genes that differed between low-APOB and high-APOB groups in all four cohorts revealed that low-APOB activity was associated with upregulation of oncogenic and metastatic regulators, such as HGF, MTIF, ERBB2, FOXM1, and CD44, and inhibition of tumor suppressors, such as TP53 and PTEN. In conclusion, APOB inactivation is associated with poor outcome in patients with HCC, and APOB may play a role in regulating multiple genes involved in HCC development.

• Microbiology and Biotechnology Letters
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• v.52 no.2
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• pp.141-151
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• 2024

Isochrysis sp. is a sea microalga that has become a species of interest because of the extreme lipid content and rapid growth rate of this organism indicating its potential for efficient biofuel production. Using genome sequencing/genome-scale modeling for the prediction of Isochrysis sp. metabolic utilities there is high scope for the identification of essential pathways for the extraction of byproducts of interest at a higher rate. In our work, we design and present iIsochr964, a genome-scale metabolic model of Isochrysis sp. including 4315 reactions, 934 genes, and 1879 metabolites, which are distributed among fourteen compartments. For model validation, experimental culture, and isolation of Isochrysis sp. were performed and biomass values were used for validation of the genome-scale model. OptFlux was instrumental in uncovering several novel metabolites that influence the organism's metabolism by increasing the flux of interacting metabolites, such as Malonyl-CoA, EPA, Protein and others. iIsochr964 provides a compelling resource of metabolic understanding to revolutionize its industrial applications, thereby fostering sustainable development and allowing estimations and simulations of the organism metabolism under varying physiological, chemical, and genetic conditions. It is also useful in principle to provide a systemic view of Isochrysis sp. metabolism, efficiently guiding research and granting context to omics data.

• KOGO NEWS
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• v.3 no.4
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• pp.7-9
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• 2003

• The Magazine of the IEIE
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• v.24 no.10
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• pp.63-72
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• 1997

Application of MEMS to biologic system mainly categorized into bio-electronics and micro-medical systems, Bio-electronics concerns on the biocompatible electronic device, in-vivo sensors, the sensors based on biological materials, biological materials for electronics and optics, the concepts and materials Inspired by biology and useful for electronics, the algorithm inspired by biology, artificial sense, and the biologic-inorganic hybrids. Micro-medical systems are utilited into the drug delivery systems, micro patient monitoring systems, micro prosthesis and artificial organs, cardiology related prothesis, analysis systems, and the minimal invasive surgery tools based on the m icrom achining technology.

• Animal cells and systems
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• v.8
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• pp.72-72
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• 2004

• Interdisciplinary Bio Central
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• v.1 no.2
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• pp.6.1-6.4
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• 2009

We stand at the brink of a fundamental change in how medicine will be practiced. Over the next 5-20 years medicine will move from being largely reactive to being predictive, personalized, preventive and participatory (P4). Technology and new scientific strategies have always been the drivers of revolutions and this is certainly the case for P4 medicine, where a systems approach to disease, new and emerging technologies and powerful computational tools will open new windows for the investigation of disease. Systems approaches are driving the emergence of fascinating new technologies that will permit billions of measurements on each individual patient. The challenge for health information technology will be how to reduce this enormous amount of data to simple hypotheses about health and disease. We predict that emerging technologies, together with the systems approaches to diagnosis, therapy and prevention will lead to a down turn in the escalating costs of healthcare. In time we will be able to export P4 medicine to the developing world and it will become the foundation of global medicine. The "democratization" of healthcare will come from P4 medicine. Its first real emergence will require the unprecedented integration of biology, medicine, technology and computation. as well as societal issues of major importance: ethical, regulatory, public policy, economic, and others. In order to effectively move the P4 scientific agenda forward new strategic partnerships are now being created with the large-scale integration of complementary skills, technologies, computational tools, patient records and samples and analysis of societal issues. It is evident that the business plans of every sector of the healthcare industry will need to be entirely transformed over the next 10 years.and the extent to which this will be done by existing companies as opposed to newly created companies is a fascinating question.