• Fisheries and Aquatic Sciences
• /
• v.19 no.8
• /
• pp.33.1-33.7
• /
• 2016

Antifreeze proteins (AFPs) lower the freezing point but not the melting point of aqueous solutions by inhibiting the growth of ice crystals via an adsorption-inhibition mechanism. However, the function of type IV AFP (AFP IV) is questionable, as its antifreeze activity is on the verge of detectable limits, its physiological concentration in adult fish blood is too low to function as a biological antifreeze, and its homologues are present even in fish from tropic oceans as well as freshwater. Therefore, we speculated that AFP IV may have gained antifreeze activity not by selective pressure but by chance. To test this hypothesis, we cloned, expressed, and assayed AFP IV from cultured subtropical olive flounder (Paralichthys olivaceus), which do not require antifreeze protein for survival. Among the identified expressed sequence tags of the flounder liver sample, a 5'-deleted complementary DNA (cDNA) sequence similar to the afp4 gene of the longhorn sculpin was identified, and its full-length cDNA and genome structure were examined. The deduced amino acid sequence of flounder AFP IV shared 55, 53, 52, and 49 % identity with those of Pleuragramma antarcticum, Myoxocephalus octodecemspinosus, Myoxocephalus scorpius, and Notothenia coriiceps, respectively. Furthermore, the genomic structure of this gene was conserved with those of other known AFP IVs. Notably, the recombinant AFP IV showed a weak but distinct thermal hysteresis of $0.07{\pm}0.01^{\circ}C$ at the concentration of 0.5 mg/mL, and ice crystals in an AFP IV solution grew star-shaped, which are very similar to those obtained from other polar AFP IVs. Taken together, our results do not support the hypothesis of evolution of AFP IV by selective pressure, suggesting that the antifreeze activity of AFP IV may have been gained by chance.

• Animal cells and systems
• /
• v.5 no.3
• /
• pp.163-177
• /
• 2001

Most, if not all, aphids harbor intracellular bacterial symbionts, called Buchnera, in their bacteriocytes, huge cells differentiated for this purpose. The association between Buchnera and aphids is so intimate, mutualistic and obligate that neither of them can any longer reproduce independently. Buchnera are vertically transmitted through generations of the host insects. Evidence suggests that Buchnera were acquired by a common ancestor of aphids 160-280 million years ago, and have been diversified, since then, in parallel with their aphid hosts. Molecular phylogenetic analyses indicate that Buchnera belong to the g subdivision of the Proteobacteria. Although Buchnera are close relatives of Escherichia coli, they contain move than 100 genomic copies per cell, and their genome size is only one seventh that of E. coli. The complete genome sequence of Buchnera revealed that their gene repertoire is quite different from those of parasitic bacteria such as Mycoplasma, Rickettsia and Chlamydia, though their genome sizes have been reduced to a similar extent. Whereas these parasitic bacteria have lost most genes for the biosynthesis of amino acids, Buchnera retain many of them. In particular, Buchnera's gene repertoire is characteristic in the richness of the genes for the biosynthesis of essential amino acids that the eukaryotic hosts are not able to synthesize, reflecting a nutritional role played by these symbionts. Buchnera, when housed in the bacteriocyte, selectively synthesize a large amount of symbionin, which is a homolog of GroEL, the major stress protein of E. coli. Symbionin not only functions as molecular chaperone, like GroEL, but also has evolutionarily acquired the phosphotransferase activity through amino acid substitutions. Aphids usually profit from Buchnera's fuction as a nutritional supplier and, when faced with an emergency, consume the biomass of Buchnera cells as nutrient reserves.

• 한국균학회소식:학술대회논문집
• /
• 2014.10a
• /
• pp.29-29
• /
• 2014

Since Darwin and Wallace introduced the concept on the evolution of species, scientists have been furiously debating what species are, and how to define them. This basic yet intriguing question has bothered us ever since, as communicating to fellow biologists about fungal species is the very cornerstone of mycology. For the species presently known, this has largely been accomplished via Latin binomials linked to morphology in the absence of DNA barcodes. In recent years mycologists have embraced the ribosomal ITS as official barcode region for Fungi, and this locus is also mainly used in environmental pyrosequencing studies. Furthermore, DNA data can now also be used to describe sterile species in the absence or lack of distinct morphological structures. Recent developments such as the registration of names in MycoBank, and linking the phenotype to the genotype, have significantly changed the face of fungal systematics. By employing the Consolidated Species Concept, incorporating genealogical concordance, ecology and morphology, robust species recognition is now possible. Several international initiatives have since built on these developments, such as the DNA barcoding of holdings of Biological Resource Centres, followed by the Genera of Fungi Project, aiming to recollect, and epitypify all type species of all genera. What these data have revealed, is that most genera are poly- and paraphyletic, and that morphological species normally encompass several genetic entities, which may be cryptic species. Once we provide a stable genetic backbone capturing our existing knowledge of the past 250 years, we will be able to accommodate novelties obtained via environmental sequencing platforms. Being able to communicate these species to other biologists in a clear manner that is DNA-based, will enable scientists to elucidate the importance, role and ecological interactions that these fungi have on our planet.

• The KIPS Transactions:PartD
• /
• v.10D no.6
• /
• pp.897-906
• /
• 2003

The traditional animal phylogenetic tree is to align the body structure of the animal phylums from simple to complex based on the initial development character. Currently, molecular systematics research based on the molecular, it is on the fly, is again estimating prior trend and show the new genealogy and interest of the evolution. In this paper, we generate the training set which is obtained from a DNA sequence ans apply to the classification. We made use of the mitochondrial DNA for the experiment, and then proved the accuracy using the MEGA program which is anaysis program, it is used in the biology field. Although the result of the mining has to proved through biological experiment, it can provede the methodology for the efficient classify and can reduce the time and effort to the experiment.

• Journal of Biomedical Engineering Research
• /
• v.20 no.3
• /
• pp.307-314
• /
• 1999

This paper describes an informatlon compression of electrically evoked myoelectric signal, M-wave. This wave shows a direct response m lato-response of nerve conductlQn study and has a characteristic with finite time support. M-wave is a useful factor for investing neurodi~ease and is often desirable to have a compact description of its shape and time evolution. The aim of this paper is to show that the AR modeling IS a effective method for compressing an information of M-wave. First, AR model parameters of real M-wave are estimated. And then. they are verified by approximatmg a M-wave using estimated AR parameters and by comparing to other melhod, Hermite tlansform[4]. To concretely evaluate the proposed method, the NMSE(normalized mean square error) of approximation curves are compared. As a result, AR modeling is effective for M-wave assessment because of its capability for the information compression.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.10
• /
• pp.2054-2061
• /
• 2015

Biologically inspired modeling techniques have received considerable attention for their robustness, scalability, and adaptability with simple local interactions and limited information. Among these modeling techniques, Gene Regulatory Networks (GRNs) play a central role in understanding natural evolution and the development of biological organisms from cells. In this paper, we apply GRN principles to the WSN system and propose a new GRN model for decentralized node scheduling design to achieve energy balancing while meeting delay requirements. Through this scheme, each sensor node schedules its state autonomously in response to gene expression and protein concentration, which are controlled by the proposed GRN-inspired node scheduling model. Simulation results indicate that the proposed scheme achieves superior performance with energy balancing as well as desirable delay compared with other well-known schemes.

• Biomedical Science Letters
• /
• v.24 no.3
• /
• pp.221-229
• /
• 2018

Trichophyton rubrum is one of the well-known pathogenic fungi and causes dermatophytosis and cutaneous mycosis in human world widely. However, there are not an available sequence type (ST) classification methods and previous studies for T. rubrum until now. Therefore, currently, molecular biological tools using their DNA sequences are used for genotype identification and classification. In the present study, in order to characterize the genetic diversity and the phylogenetic relation of T. rubrum clinical isolates, five different housekeeping genes, such as actin (ACT), calmodulin (CAL), RNA polymerase II (RPB2), superoxide dismutase 2 (SOD2), and ${\beta}$-tubulin (BT2) were analyzed using by multilocus sequence typing (MLST). Also, DNA sequence analysis was performed to examine the differences between the sequences of Trichophyton strains and the identified genetic variations sequence. As a result, most of the sequences were shown to have highly matched rates in their housekeeping genes. However, genetic variations were found on three different positions of ${\beta}$-tubulin gene and were shown to have changed from $C{\rightarrow}G$ (1766), $G{\rightarrow}T$ (1876), and $C{\rightarrow}A$ (1886). To confirm the association with T. rubrum inheritance, a phylogenetic tree analysis was performed. It was classified as four clusters, but there was little significant correlation. Even so, MLST analysis is believed to be helpful for determining the genetic variations of T. rubrum in cases where there is more large-scale data accumulation. In conclusion, the present study demonstrated the first MLST analysis of T. rubrum in Korea and explored the possibility that MLST could be a useful tool for studying the epidemiology and evolution of T. rubrum through further studies.

• Journal of the korean society of oceanography
• /
• v.32 no.4
• /
• pp.163-170
• /
• 1997

Some CMP gathers acquired from shallow marine seismic reflection survey in offshore Korea do not show the hyperbolic trend of moveout. It originated from so-called swell effect of source and streamer, which are towed under rough sea surface during the data acquisition. The observed time deviations of NMO-corrected traces can be entirely ascribed to the swell effect. To correct these time deviations, a residual statics is introduced using Genetic Algorithms (GA) into the swell correction. A new class of global optimization methods known as GA has recently been developed in the field of Artificial Intelligence and has a resemblance with the genetic evolution of biological systems. The basic idea in using GA as an optimization method is to represent a population of possible solutions or models in a chromosome-type encoding and manipulate these encoded models through simulated reproduction, crossover and mutation. GA parameters used in this paper are as follows: population size Q=40, probability of multiple-point crossover P$_c$=0.6, linear relationship of mutation probability P$_m$ from 0.002 to 0.004, and gray code representation are adopted. The number of the model participating in tournament selection (nt) is 3, and the number of expected copies desired for the best population member in the scaling of fitness is 1.5. With above parameters, an optimization run was iterated for 101 generations. The combination of above parameters are found to be optimal for the convergence of the algorithm. The resulting reflection events in every NMO-corrected CMP gather show good alignment and enhanced quality stack section.

• Journal of the Society of Naval Architects of Korea
• /
• v.31 no.4
• /
• pp.147-156
• /
• 1994

Though optimization method had been used for long time for the optimal design of ship structure, design variables in the most cases were assumed to be continuous real values or it was not easy to solve the mixed integer optimum design problems using the conventional optimization methods. Thus, it was often tried to use various initial starting points to locate the best optimum paint and to use special method such as branch and bound method to handle the discrete design variables in the optimization problems. Sometimes it had succeed, but the essential problems for dealing with the local optimum and discrete design variables was left unsolved. Hence, in this paper, Genetic Algorithms adopting the biological evolution process is applied to the ship structural design problem where the integer values for the number of stiffen design variables or the discrete values for the plate thickness variables would be more preferable in order to find out their effects on the final optimum design. Through the numerical result comparisons, it was found that Genetic Algorithm could always yield the global optimum for the discrete and mixed integer structural optimization problem cases even though it takes more time than other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.1765-1794
• /
• 2019

Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a "population" of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a "fitness function" and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a "correct" program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.