Transdermal delivery of FITC-Dextrans with different molecular weights using radiofrequency microporation.

BACKGROUND: Transdermal delivery is of great importance for the effective delivery of bioactive or therapeutic agents into a body. The microporation device based on radiofrequency can be used to enhance delivery efficiency by removing the epidermis layer. METHODS: The micropores were developed on pig skin and human cadaver skin with dermal and epidermal layers by the microporation device. The regeneration of micropores in the human cadaver skin caused by microporation was confirmed using an optical microscope and haematoxylin/eosin (H&E) staining. The permeability of fluorescein isothiocyanate-dextrans (FITC-dextrans) with different molecular weights through the pig and human cadaver skins were measured using Franz diffusion cell. RESULTS: The optical image and histological analysis confirmed that the micropores on the skin were recovered over time. The enhanced permeability through micropores was confirmed by Franz diffusion cell. The lower molecular weight of FITC-dextran permeated more on both human and pig skin. In addition, the permeation rate was higher in pig skin than in human skin. CONCLUSIONS: We believe that the microporation device can be used as a potential technique for effective transdermal drug delivery.

A pathway-based classification of breast cancer integrating data on differentially expressed genes, copy number variations and microRNA target genes.

Breast cancer is a clinically heterogeneous disease characterized by distinct molecular aberrations. Understanding the heterogeneity and identifying subgroups of breast cancer are essential to improving diagnoses and predicting therapeutic responses. In this paper, we propose a classification scheme for breast cancer which integrates data on differentially expressed genes (DEGs), copy number variations (CNVs) and microRNAs (miRNAs)-regulated mRNAs. Pathway information based on the estimation of molecular pathway activity is also applied as a postprocessor to optimize the classifier. A total of 250 malignant breast tumors were analyzed by k-means clustering based on the patterns of the expression profiles of 215 intrinsic genes, and the classification performances were compared with existing breast cancer classifiers including the BluePrint and the 625-gene classifier. We show that a classification scheme which incorporates pathway information with various genetic variations achieves better performance than classifiers based on the expression levels of individual genes, and propose that the identified signature serves as a basic tool for identifying rational therapeutic opportunities for breast cancer patients.

DNA barcode-based molecular identification system for fish species.

In this study, we applied DNA barcoding to identify species using short DNA sequence analysis. We examined the utility of DNA barcoding by identifying 53 Korean freshwater fish species, 233 other freshwater fish species, and 1339 saltwater fish species. We successfully developed a web-based molecular identification system for fish (MISF) using a profile hidden Markov model. MISF facilitates efficient and reliable species identification, overcoming the limitations of conventional taxonomic approaches. MISF is freely accessible at http://bioinfosys.snu.ac.kr:8080/MISF/misf.jsp .

BioBarcode: a general DNA barcoding database and server platform for Asian biodiversity resources.

BACKGROUND: DNA barcoding provides a rapid, accurate, and standardized method for species-level identification using short DNA sequences. Such a standardized identification method is useful for mapping all the species on Earth, particularly when DNA sequencing technology is cheaply available. There are many nations in Asia with many biodiversity resources that need to be mapped and registered in databases. RESULTS: We have built a general DNA barcode data processing system, BioBarcode, with open source software - which is a general purpose database and server. It uses mySQL RDBMS 5.0, BLAST2, and Apache httpd server. An exemplary database of BioBarcode has around 11,300 specimen entries (including GenBank data) and registers the biological species to map their genetic relationships. The BioBarcode database contains a chromatogram viewer which improves the performance in DNA sequence analyses. CONCLUSION: Asia has a very high degree of biodiversity and the BioBarcode database server system aims to provide an efficient bioinformatics protocol that can be freely used by Asian researchers and research organizations interested in DNA barcoding. The BioBarcode promotes the rapid acquisition of biological species DNA sequence data that meet global standards by providing specialized services, and provides useful tools that will make barcoding cheaper and faster in the biodiversity community such as standardization, depository, management, and analysis of DNA barcode data. The system can be downloaded upon request, and an exemplary server has been constructed with which to build an Asian biodiversity system http://www.asianbarcode.org.

A computational approach for the classification of protein tyrosine kinases.

Protein tyrosine kinases (PTKs) play a central role in the modulation of a wide variety of cellular events such as differentiation, proliferation and metabolism, and their unregulated activation can lead to various diseases including cancer and diabetes. PTKs represent a diverse family of proteins including both receptor tyrosine kinases (RTKs) and non-receptor tyrosine kinases (NRTKs). Due to the diversity and important cellular roles of PTKs, accurate classification methods are required to better understand and differentiate different PTKs. In addition, PTKs have become important targets for drugs, providing a further need to develop novel methods to accurately classify this set of important biological molecules. Here, we introduce a novel statistical model for the classification of PTKs that is based on their structural features. The approach allows for both the recognition of PTKs and the classification of RTKs into their subfamilies. This novel approach had an overall accuracy of 98.5% for the identification of PTKs, and 99.3% for the classification of RTKs.

A machine learning based method for the prediction of G protein-coupled receptor-binding PDZ domain proteins.

G protein-coupled receptors (GPCRs) are part of multi-protein networks called 'receptosomes'. These GPCR interacting proteins (GIPs) in the receptosomes control the targeting, trafficking and signaling of GPCRs. PDZ domain proteins constitute the largest protein family among the GIPs, and the predominant function of the PDZ domain proteins is to assemble signaling pathway components into close proximity by recognition of the last four C-terminal amino acids of GPCRs. We present here a machine learning based approach for the identification of GPCR-binding PDZ domain proteins. In order to characterize the network of interactions between amino acid residues that contribute to the stability of the PDZ domain-ligand complex and to encode the complex into a feature vector, amino acid contact matrices and physicochemical distance matrix were constructed and adopted. This novel machine learning based method displayed high performance for the identification of PDZ domain-ligand interactions and allowed the identification of novel GPCR-PDZ domain protein interactions.

Two genetic lineages of sea slaters, Ligia (Crustacea: Isopoda) in South Korea: a population genetic approach.

In this study, the species composition and population genetic properties of the sea slater, Ligia, in South Korea were investigated using mitochondrial and nuclear gene sequences. Two groups of sea slaters, genetically isolated from each other, a Western Group (WG) and an Eastern Group (EG) were identified. These groups exhibited considerable genetic divergence from Ligia exotica, previously recorded as a species inhabiting this country. These results indicate that there may be two species of Ligia in South Korea, but there is a small probability that both groups are L. exotica. A comparison of their genetic properties indicates that WG has a higher effective population size than EG, and that EG may have experienced a recent expansion, implying that it has a shorter history in South Korea than WG. These findings suggest that the South Korean sea slater populations may have been established as a result of several colonization events that can be traced on a continental scale by phylogeographic studies of sea slaters.

A combined approach for the classification of G protein-coupled receptors and its application to detect GPCR splice variants.

G protein-coupled receptors (GPCRs) constitute the largest family of cell surface receptors and play a central role in cellular signaling pathways. The importance of GPCRs has led to their becoming the targets of more than 50% of prescription drugs. However, drug compounds that do not differentiate between receptor subtypes can have considerable side effects and efficacy problems. An accurate classification of GPCRs can solve the side effect problems and raise the efficacy of drugs. Here, we introduce an approach that combines a fingerprint method, statistical profiles and physicochemical properties of transmembrane (TM) domains for a highly accurate classification of the receptors. The approach allows both the recognition and classification for GPCRs at the subfamily and subtype level, and allows the identification of splice variants. We found that the approach demonstrates an overall accuracy of 97.88% for subfamily classification, and 94.57% for subtype classification.

A combined approach for locating box H/ACA snoRNAs in the human genome.

A novel combined method for locating box H/ACA small nucleolar RNAs (snoRNAs) is described, together with a software tool. The method adopts both a probabilistic hidden Markov model (HMM) and a minimum free energy (MFE) rule, and filters possible candidate box H/ACA snoRNAs obtained from genomic DNA sequences. With our novel method 12 known box H/ACA snoRNAs, and one strong candidate were identified in 30 nucleolar protein genomic sequences.