• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.128-133
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• 2006

This paper compares domain combination based protein-protein interaction prediction method with domain based protein-protein interaction method. The prediction accuracy and reliability of the methods are compared using the same prediction technique and interaction data. According to the comparison, domain combination based prediction method has showed superior prediction accuracy to domain based prediction method for protein pairs with fully overlapped domains with protein pairs in learning sets. When we consider that domain combination based method has the effects of assigning a weight to each domain interaction, it implies that we can improve the prediction accuracies of currently available domain or domain combination based protein interaction prediction methods further by developing more advanced weight assignment techniques. Several significant facts revealed from the comparative studies are also described in this paper.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.136-143
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• 2016

KiSS1-derived peptide receptor, a GPCR protein, binds with the hormone kiss peptin. They are important in the neuroendocrine regulation of reproduction and in the secretion of gonadotrophin-releasing hormone. Thus, analysing the structural features of the receptor becomes important. However, the three dimensional structure of the protein is unavailable. Hence in this study, we have performed the homology modelling of KiSS1-derived peptide receptor with 5 different templates. 30 models were constructed using two platforms - Easymodeller and ITasser. The optimal models were chosen based on the model validation. Two models were selected after validation. The developed models could provide useful for analysing the structural features of KiSS1-derived peptide receptor and their pathophysiological role in various disorders related to them.

• Genomics & Informatics
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• v.8 no.4
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• pp.170-176
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• 2010

The Ribonucleotide reductases (RNR) are essential enzymes that catalyze the conversion of nucleotides to deoxynucleotides in DNA replication and repair in all living organisms. The RNRs operate by a free radical mechanism but differ in the composition of subunit, cofactor required and regulation by allostery. Based on these differences the RNRs are classified into three classesclass I, class II and class III which depend on oxygen, adenosylcobalamin and S-adenosylmethionine with an iron sulfur cluster respectively for radical generation. In this article thirty seven sequences belonging to each of the three classes of RNR were analyzed by using various tools of bioinformatics. Phylogenetic analysis, dot-plot comparisons and motif analysis was done to identify a number of differences in the three classes of RNRs. In this research article, we have attempted to decipher evolutionary relationship between the three classes of RNR by using bioinformatics approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

• BMB Reports
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• v.37 no.1
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• pp.75-82
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• 2004

Recent years saw a dramatic increase in genomic and proteomic data in public archives. Now with the complete genome sequences of human and other species in hand, detailed analyses of the genome sequences will undoubtedly improve our understanding of biological systems and at the same time require sophisticated bioinformatic tools. Here we review what computational challenges are ahead and what are the new exciting developments in this exciting field.

• Journal of Integrative Natural Science
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• v.8 no.3
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• pp.176-183
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• 2015

Corticotropin-releasing actor receptors (CRFRs) activates the hypothalamic pituitary adrenal axis, one of the 2 parts of the fight or flight response to stress. Increased CRH production has is associated with Alzheimer's disease and major depression and hypoglycemia. In this study, we report the important structural and chemical parameters for CRFR inhibitors using the derivatives of 8-substituted-2-aryl-5-alkylaminoquinolines. A 3D QSAR study, Comparative molecular field analysis (CoMFA) was performed. The best predictions were obtained for the best CoMFA model with a $q^2$ of 0.607 with 6 components and $r^2$ of 0.991. The statistical parameters from the generated CoMFA models indicated that the data are well fitted and have high predictive ability. The contour map resulted from the CoMFA models might be helpful in the future designing of novel and more potent CRFR derivatives.

• Journal of Integrative Natural Science
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• v.9 no.4
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• pp.234-240
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• 2016

Bradykinin receptor B2, a GPCR protein, binds with the inflammatory mediator hormone bradkynin. It plays an important role in cross-talk between the renin-angiotensin system (RAS) and the kinin-kallikrein system (KKS). Also, it is involved in many processes including vasodilation, edema, smooth muscle spasm and pain fiber stimulation. Hence, studuying the structural features of the receptor becomes important. But the unavailability of the three dimensional structure of the protein makes the analysis difficult. Hence we have performed the homology modelling of Bradykinin receptor B2 with 5 different templates. 25 different homology models were constructed. Two best models were selected based on the model validation. The developed models could be helpful in analysing the structural features of Bradykinin receptor B2 and in pathophysiology of various disorders related to them.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2006.02a
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• pp.125-126
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• 2006

NimbleGen has developed strategies to use its high-density oligonucleotide microarray platform (385,000 probes per array) to map both promoter binding sites and copy number variation at very high-resolution in the human genome. Here we describe a genome-wide map of active promoters determined by experimentally locating the sites of transcription imitation complex binding throughout the human genome using microarrays combined with chromatin immunoprecipitation. This map defines 10,567 active promoters corresponding to 6,763 known genes and at least 1,196 un-annotated transcriptional units. Microarray-based comparative genomic hybridisation (CGH) is animportant research tool for investigating chromosomal aberrations frequently associated with complex diseases such as cancer, neuropsychiatric disorders, and congenital developmental disorders. NimbleGen array CGH is an ultra-high resolution (0.5-50 Kb) oligo array platform that can be used to detect amplifications and deletions and map the associated breakpoints on the whole-genome level or with custom fine-tiling arrays. For whole-genome array CGH, probes are tiled through genic and intergenic regions with a median probe spacing of 6 Kb, which provides a comprehensive, unbiased analysis of the genome.

• Genomics & Informatics
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• v.13 no.1
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• pp.15-24
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• 2015

Fatty acid synthase (FASN, EC 2.3.1.85), is a multi-enzyme dimer complex that plays a critical role in lipogenesis. This lipogenic enzyme has gained importance beyond its physiological role due to its implications in several clinical conditions-cancers, obesity, and diabetes. This has made FASN an attractive pharmacological target. Here, we have attempted to predict the theoretical models for the human enoyl reductase (ER) and ${\beta}$-ketoacyl reductase (KR) domains based on the porcine FASN crystal structure, which was the structurally closest template available at the time of this study. Comparative modeling methods were used for studying the structure-function relationships. Different validation studies revealed the predicted structures to be highly plausible. The respective substrates of ER and KR domains-namely, trans-butenoyl and ${\beta}$-ketobutyryl-were computationally docked into active sites using Glide in order to understand the probable binding mode. The molecular dynamics simulations of the apo and holo states of ER and KR showed stable backbone root mean square deviation trajectories with minimal deviation. Ramachandran plot analysis showed 96.0% of residues in the most favorable region for ER and 90.3% for the KR domain, respectively. Thus, the predicted models yielded significant insights into the substrate binding modes of the ER and KR catalytic domains and will aid in identifying novel chemical inhibitors of human FASN that target these domains.

• Journal of Life Science
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• v.29 no.1
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• pp.1-8
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• 2019

In Hanwoo cattle (Korean native cattle), there is a scarcity of comparative analysis papers using highdepth sequencing and haplotype phasing, particularly a comparative analysis of the Truseq Synthetic Long-Read Haplotyping sequencing platform serviced by Illumina (TSLRH) versus the Chromium Genome Sequencing platform serviced by 10X Genomics (10XG). DNA was extracted from the sperm of a Hanwoo breeding bull (ID: TN1505D2184/27214) provided by Hanwoo research canter and used for the generation of sequence data from both the sequencing platforms. We then identified SNVs using an appropriate analysis pipeline tailored for each platform. The TSLRH and 10XG platforms generated a total of 355,208,304 and 1,632,772,004 reads, respectively, corresponding to a Q30 (%) of 89.04% and 88.60%, respectively, of which 351,992,768(99.09%) and 1,526,641,824(93.50%) were successfully mapped. For the TSLRH and 10XG platforms, the mean depth of the sequencing was 13.04X and 74.3X, the longest phase block was 1,982,706 bp and 1,480,081 bp, the N50 phase block was 57,637 bp and 114,394 bp, the total number of SNVs identified was 4,534,989 and 8,496,813, and the total phased rate was 72.29% and 87.67%, respectively. Moreover, for each chromosome, we identified unique and common SNVs using both sequencing platforms. The number of SNVs was directly proportional to the length of the chromosome. Based on our results, we recommend the use of the 10XG platform for haplotype phasing and SNV identification, as it generated a longer N50 phase block, in addition to a higher mean depth, total number of reads, total number of SNVs, and phase rate, than the TSLRH platform.