Search results for: Sense-antisense gene pair

Authors: A. R. Nezamabadi, M. Karami Khorramabadi

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This paper presents the elastic buckling of homogeneous beams with a pair of piezoelectric layers surface bonded on both sides of the beams. The displacement field of beam is assumed based on the Engesser-Timoshenko beam theory. Applying the Hamilton's principle, the equilibrium equation is established. The influences of applied voltage, dimensionless geometrical parameter and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: Mechanical Buckling, Engesser-Timoshenko beam theory - Piezoelectric layer.

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Authors: Seo Young Kim, Jae Won Lee, Jong Sung Bae

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Microarray experiments are information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. For biologists, a key aim when analyzing microarray data is to group genes based on the temporal patterns of their expression levels. In this paper, we used an iterative clustering method to find temporal patterns of gene expression. We evaluated the performance of this method by applying it to real sporulation data and simulated data. The patterns obtained using the iterative clustering were found to be superior to those obtained using existing clustering algorithms.

Keywords: Clustering, microarray experiment, temporal pattern of gene expression data.

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Authors: Frank Emmert-Streib, Matthias Dehmer

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Inferring the network structure from time series data is a hard problem, especially if the time series is short and noisy. DNA microarray is a technology allowing to monitor the mRNA concentration of thousands of genes simultaneously that produces data of these characteristics. In this study we try to investigate the influence of the experimental design on the quality of the result. More precisely, we investigate the influence of two different types of random single gene perturbations on the inference of genetic networks from time series data. To obtain an objective quality measure for this influence we simulate gene expression values with a biologically plausible model of a known network structure. Within this framework we study the influence of single gene knock-outs in opposite to linearly controlled expression for single genes on the quality of the infered network structure.

Keywords: Dynamic Bayesian networks, microarray data, structure learning, Markov chain Monte Carlo.

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Authors: Yingchun Jiang, Yan Tang

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In view of the good properties of nonstationary wavelet frames and the better flexibility of wavelets in Sobolev spaces, the nonstationary dual wavelet frames in a pair of dual Sobolev spaces are studied in this paper. We mainly give the oblique extension principle and the mixed extension principle for nonstationary dual wavelet frames in a pair of dual Sobolev spaces Hs(Rd) and H-s(Rd).

Keywords: Nonstationary, dual frames, dual Sobolev spaces, extension principle.

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Authors: U. Kairov, T. Karpenyuk, E. Ramanculov, A. Zinovyev

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The most common result of analysis of highthroughput data in molecular biology represents a global list of genes, ranked accordingly to a certain score. The score can be a measure of differential expression. Recent work proposed a new method for selecting a number of genes in a ranked gene list from microarray gene expression data such that this set forms the Optimally Functionally Enriched Network (OFTEN), formed by known physical interactions between genes or their products. Here we present calculation results of relative connectivity of genes from META-OFTEN network and tentative biological interpretation of the most reproducible signal. The relative connectivity and inbetweenness values of genes from META-OFTEN network were estimated.

Keywords: Microarray, META-OFTEN, gene network.

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Authors: N. Reehana, A. Parveez Ahamed, D. Mubarak Ali, A. Suresh, R. Arvind Kumar, N. Thajuddin

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Cyanobacteria play a vital role in the production of phycobiliproteins that includes phycocyanin and phycoerythrin pigments. Phycocyanin and related phycobiliproteins have wide variety of application that is used in the food, biotechnology and cosmetic industry because of their color, fluorescent and antioxidant properties. The present study is focused to understand the pigment at molecular level in the Cyanobacteria Oscillatoria terebriformis NTRI05 and Oscillatoria foreaui NTRI06. After extraction of genomic DNA, the amplification of C-Phycocyanin gene was done with the suitable primer PCβF and PCαR and the sequencing was performed. Structural and Phylogenetic analysis was attained using the sequence to develop a molecular model.

Keywords: Cyanobacteria, C-Phycocyanin gene, Phylogenetic analysis, Structural analysis.

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Authors: C. Gunavathi, K. Premalatha

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Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the genes that directly involve in the classification and to eliminate irrelevant genes. In this paper statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR) and F-Statistics are used to rank the genes. The ranked genes are used for further classification. Particle Swarm Optimization (PSO) algorithm and Shuffled Frog Leaping (SFL) algorithm are used to find the significant genes from the top-m ranked genes. The Naïve Bayes Classifier (NBC) is used to classify the samples based on the significant genes. The proposed work is applied on Lung and Ovarian datasets. The experimental results show that the proposed method achieves 100% accuracy in all the three datasets and the results are compared with previous works.

Keywords: Microarray, T-Statistics, Signal-to-Noise Ratio, FStatistics, Particle Swarm Optimization, Shuffled Frog Leaping, Naïve Bayes Classifier.

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Authors: Huynh Quyet Thang, Le Hai Quan

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Interaction Model plays an important role in Modelbased Intelligent Interface Agent Architecture for developing Intelligent User Interface. In this paper we are presenting some improvements in the algorithms for development interaction model of interface agent including: the action segmentation algorithm, the action pair selection algorithm, the final action pair selection algorithm, the interaction graph construction algorithm and the probability calculation algorithm. The analysis of the algorithms also presented. At the end of this paper, we introduce an experimental program called “Personal Transfer System".

Keywords: interface agent, interaction model, user model.

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Authors: Cheng-Hong Yang, Tsung-Mu Shih, Li-Yeh Chuang

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Serial Analysis of Gene Expression is a powerful quantification technique for generating cell or tissue gene expression data. The profile of the gene expression of cell or tissue in several different states is difficult for biologists to analyze because of the large number of genes typically involved. However, feature selection in machine learning can successfully reduce this problem. The method allows reducing the features (genes) in specific SAGE data, and determines only relevant genes. In this study, we used a genetic algorithm to implement feature selection, and evaluate the classification accuracy of the selected features with the K-nearest neighbor method. In order to validate the proposed method, we used two SAGE data sets for testing. The results of this study conclusively prove that the number of features of the original SAGE data set can be significantly reduced and higher classification accuracy can be achieved.

Keywords: Serial Analysis of Gene Expression, Feature selection, Genetic Algorithm, K-nearest neighbor method.

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Authors: Raj Kumar Rajak, Bharat Mishra

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Bio-batteries represent an entirely new long-term, reasonable, reachable and ecofriendly approach to produce sustainable energy. In the present experimental work, we have studied the effect of generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow dung as an electrolyte. C-Mg electrode pair shows maximum voltage and SCC (Short Circuit Current) while C-Zn electrode pair shows less OCV (Open Circuit Voltage) and SCC. We have chosen C-Zn electrodes because Mg electrodes are not economical. By the studies of different electrodes and cow dung, it is found that C-Zn electrode battery is more suitable. This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: Bio-batteries, electricity, cow dung, electrodes, non-conventional.

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Authors: Mohamed Hafez, Georg Hausner

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The full length mitochondrial small subunit ribosomal (mt-rns) gene has been characterized for Ophiostoma novo-ulmi subspecies americana. The gene was also characterized for Ophiostoma ulmi and a group II intron was noted in the mt-rns gene of O. ulmi. The insertion in the mt-rns gene is at position S952 and it is a group IIB1 intron that encodes a double motif LAGLIDADG homing endonuclease from an open reading frame located within a loop of domain III. Secondary structure models for the mt-rns RNA of O. novo-ulmi subsp. americana and O. ulmi were generated to place the intron within the context of the ribosomal RNA. The in vivo splicing of the O.ul-mS952 group II intron was confirmed with reverse transcription-PCR. A survey of 182 strains of Dutch Elm Diseases causing agents showed that the mS952 intron was absent in what is considered to be the more aggressive species O. novo-ulmi but present in strains of the less aggressive O. ulmi. This observation suggests that the O.ul-mS952 intron can be used as a PCR-based molecular marker to discriminate between O. ulmi and O. novo-ulmi subsp. americana.

Keywords: Dutch Elm Disease, group II introns, mtDNA, species identification

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Authors: Congmin Z. Xie, Terry Healy, Peter Robinson, Kevin Stewart

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An HPLC-UV analytical method was developed to determine ethylenediaminetetraacetic acid (EDTA) in dairy wastewater and surface water. The optimizing separation was achieved by reversed–phase ion-pair liquid chromatography on a C18 column using methanol as mobile phase solvent, tetrabutylammonium bromide as the ion-pair reagent in pH 3.3 formate buffer solution at a flow rate of 0.9 mL min-1 with a UV detector at 265 nm. No interference of Ca, Mg or NO3 - was detected. Method performance was evaluated in terms of linearity, repeatability and reproducibility. The method detection limit was 5 μg L-1. The contents of EDTA in dairy effluents were 72 ~ 261 μg L-1 at a large dairy site. A change of EDTA concentration was observed downstream of the dairy effluent discharge, but this was well under the predicted no effect concentration for aquatic ecosystem.

Keywords: Dairy wastewater, EDTA, HPLC, surface water.

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Authors: Huong M. T. Nguyen, Hoa A. P. Nguyen, Mai P. T. Nguyen, Ngoc D. Ngo, Van T. Ta, Hai T. Le, Chi V. Phan

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Wilson’s disease (WD) is an autosomal recessive disorder of the copper metabolism, which is caused by a mutation in the copper-transporting P-type ATPase (ATP7B). The mechanism of this disease is the failure of hepatic excretion of copper to bile, and leads to copper deposits in the liver and other organs. The ATP7B gene is located on the long arm of chromosome 13 (13q14.3). This study aimed to investigate the gene mutation in the Vietnamese patients with WD, and make a presymptomatic diagnosis for their familial members. Forty-three WD patients and their 65 siblings were identified as having ATP7B gene mutations. Genomic DNA was extracted from peripheral blood samples; 21 exons and exon-intron boundaries of the ATP7B gene were analyzed by direct sequencing. We recognized four mutations ([R723=; H724Tfs*34], V1042Cfs*79, D1027H, and IVS6+3A>G) in the sum of 20 detectable mutations, accounting for 87.2% of the total. Mutation S105* was determined to have a high rate (32.6%) in this study. The hotspot regions of ATP7B were found at exons 2, 16, and 8, and intron 14, in 39.6 %, 11.6 %, 9.3%, and 7 % of patients, respectively. Among nine homozygote/compound heterozygote siblings of the patients with WD, three individuals were determined as asymptomatic by screening mutations of the probands. They would begin treatment after diagnosis. In conclusion, 20 different mutations were detected in 43 WD patients. Of this number, four novel mutations were explored, including [R723=; H724Tfs*34], V1042Cfs*79, D1027H, and IVS6+3A>G. The mutation S105* is the most prevalent and has been considered as a biomarker that can be used in a rapid detection assay for diagnosis of WD patients. Exons 2, 8, and 16, and intron 14 should be screened initially for WD patients in Vietnam. Based on risk profile for WD, genetic testing for presymptomatic patients is also useful in diagnosis and treatment.

Keywords: ATP7B gene, mutation detection, presymptomatic diagnosis, Vietnamese Wilson’s disease.

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Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

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The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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Authors: Raj Kumar Rajak, Bharat Mishra

Abstract:

Bio-batteries represent an entirely new long-term, reasonable, reachable, and eco-friendly approach to generation of sustainable energy. In the present experimental work, we have studied the effect of the generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow’s urine as an electrolyte. C-Mg electrode pair shows maximum Voltage and Short Circuit Current (SCC), while C-Zn electrode pair shows less Open Circuit Voltage (OCV) and SCC. By the studies of cow urine and different electrodes, it is found that C-Zn electrode battery is more economical. The cow urine battery with C-Zn electrode provides maximum power (707.4 mW) and durability (up to 145 h). This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: Bio-batteries, cow’s urine, electrodes, non-conventional.

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Authors: Zilya R. Vershinina, Andrei K. Baymiev, Aleksei K. Baymiev, Aleksei V. Chemeris

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This paper reports optimization of characteristics of bioballistic transformation of spring soft wheat (Triticum aestivum L. cultivar Raduga) and getting of transgenic plants, carrying pea lectin gene. This gene will let to create new associative wheat symbiosis with nodule bacteria of field pea, which has growth encouraging, fungistatic and other useful characteristics.

Keywords: transgenic wheat, pea lectin, rhizobia root colonization, symbiosis

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than Optical Character Recognition (OCR) results.

Keywords: Biological pathway, image understanding, gene name recognition, object detection, Siamese network, Visual Geometry Group.

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Authors: Reena Murali, David Peter S.

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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies show that upregulation of mRNA because serious diseases like cancer. So designing effective siRNA with good knockdown effects plays an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (%G), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: Artificial Neural Network, Double Stranded RNA, RNA Interference, Short Interfering RNA.

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Authors: ByungHoon Kang, Jeawook Shin, Ju-man Song, Hyun-Taek Choi, PooGyeon Park

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In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing straightly and the moving distance for each unit time is measured continuously. However, the accuracy of the localization using the trigonometry is highly dependent to the accuracy of DOAs and measured moving distances. Therefore, we proposed another method based on the extended Kalman filter that gives more robust and accurate localization result.

Keywords: Localization, acoustic, underwater, extended Kalman filter.

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Authors: N. Tuncbag, T. Haliloglu, O. Keskin

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Understanding the cell's large-scale organization is an interesting task in computational biology. Thus, protein-protein interactions can reveal important organization and function of the cell. Here, we investigated the correspondence between protein interactions and function for the yeast. We obtained the correlations among the set of proteins. Then these correlations are clustered using both the hierarchical and biclustering methods. The detailed analyses of proteins in each cluster were carried out by making use of their functional annotations. As a result, we found that some functional classes appear together in almost all biclusters. On the other hand, in hierarchical clustering, the dominancy of one functional class is observed. In brief, from interaction data to function, some correlated results are noticed about the relationship between interaction and function which might give clues about the organization of the proteins.

Keywords: Pair-wise protein interactions, DIP database, functional correlations, biclustering.

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Authors: Esmaeil Hassannejad

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Some of the students' problems in writing skill stem from inadequate preparation for the writing assignment. Students should be taught how to write well when they arrive in language classes. Having selected a topic, the students examine and explore the theme from as large a variety of viewpoints as their background and imagination make possible. Another strategy is that the students prepare an Outline before writing the paper. The comparison between the two mentioned thought provoking techniques was carried out between the two class groups –students of Islamic Azad University of Dezful who were studying “Writing 2" as their main course. Each class group was assigned to write five compositions separately in different periods of time. Then a t-test for each pair of exams between the two class groups showed that the t-observed in each pair was more than the t-critical. Consequently, the first hypothesis which states those who utilize Brainstorming as a thought provoking technique in prewriting phase are more successful than those who outline the papers before writing was verified.

Keywords: Brainstorming, Outlining, Prewriting, Thought provoking techniques

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Authors: Roya Bakhtiar, Alireza Abdolmohammadi, Hadi Hajarian, Zahra Nikousefat, Davood, Kalantar-Neyestanaki

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The objective of the present study was to determine the polymorphism in the leptin (332G>A) and its association with biometric traits in Sanjabi sheep. For this purpose, blood samples from 96 rams were taken, and tail length, width tail, circumference tail, body length, body width, and height were simultaneously recorded. PCR was performed using specific primer to amplify 463 bp fragment including exon 3 of leptin gene, and PCR products were digested by Cail restriction enzymes. The 332G>A (at 332th nucleotide of exon 3 leptin gene) that caused an amino acid change from Arg to Gln was detected by Cail (CAGNNNCTG) endonuclease, as the endonuclease cannot cut this region if G nucleotide is located in this position. Three genotypes including GG (463), GA (463, 360and 103 bp) and GG (360 bp and 103 bp) were identified after digestion by enzyme. The estimated frequencies of three genotypes including GG, GA, and AA for 332G>A locus were 0.68, 0.29 and 0.03 and those were 0.18 and 0.82 for A and G alleles, respectively. In the current study, chi-square test indicated that 332G>A positions did not deviate from the Hardy–Weinberg (HW) equilibrium. The most important reason to show HW equation was that samples used in this study belong to three large local herds with a traditional breeding system having random mating and without selection. Shannon index amount was calculated which represent an average genetic variation in Sanjabi rams. Also, heterozygosity estimated by Nei index indicated that genetic diversity of mutation in the leptin gene is moderate. Leptin gene polymorphism in the 332G>A had significant effect on body length (P<0.05) trait, and individuals with GA genotype had significantly the higher body length compared to other individuals. Although animals with GA genotype had higher body width, this difference was not statistically significant (P>0.05). This non-synonymous SNP resulted in different amino acid changes at codon positions111(R/Q). As leptin activity is localized, at least in part, in domains between amino acid residues 106-1406, it is speculated that the detected SNP at position 332 may affect the activity of leptin and may lead to different biological functions. Based to our results, due to significant effect of leptin gene polymorphism on body size traits, this gene may be used a candidate gene for improving these traits.

Keywords: Body size, Leptin gene, PCR-RFLP, Sanjabi sheep.

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Authors: T. Kerdchuen

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This paper proposes the stochastic tabu search (STS) for improving the measurement scheme for power system state estimation. If the original measured scheme is not observable, the additional measurements with minimum number of measurements are added into the system by STS so that there is no critical measurement pair. The random bit flipping and bit exchanging perturbations are used for generating the neighborhood solutions in STS. The Pδ observable concept is used to determine the network observability. Test results of 10 bus, IEEE 14 and 30 bus systems are shown that STS can improve the original measured scheme to be observable without critical measurement pair. Moreover, the results of STS are superior to deterministic tabu search (DTS) in terms of the best solution hit.

Keywords: Measurement Scheme, Power System StateEstimation, Network Observability, Stochastic Tabu Search (STS).

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Authors: Amer A. Hasan, Mehri Igci, Ersin Borazan, Rozhgar A. Khailany, Emine Bayraktar, Ahmet Arslan

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Gastric Cancer (GC) has high morbidity and fatality rate in various countries. It is still one of the most frequent and deadly diseases. Gastrokine1 (GKN1) and gastrokine2 (GKN2) genes are highly expressed in the normal stomach epithelium and play important roles in maintaining the integrity and homeostasis of stomach mucosal epithelial cells. In this study, 47 paired samples that were grouped according to the types of gastric cancer and the clinical characteristics of the patients, including gender and average of age. They were investigated with gene expression analysis and mutation screening by monitoring RT-PCR, SSCP and nucleotide sequencing techniques. Both GKN1 and GKN2 genes were observed significantly reduced found by (Wilcoxon signed rank test; p<0.05). As a result of gene screening, no mutation (no different genotype) was detected. It is considered that gene mutations are not the cause of gastrokines inactivation. In conclusion, the mRNA expression level of GKN1 and GKN2 genes statistically was decreased regardless the gender, age, or cancer type of patients. Reduced of gastrokine genes seem to occur at the initial steps of gastric cancer development.

Keywords: Diagnostic biomarker, gastric cancer, nucleotide sequencing, semi-quantitative RT-PCR.

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Authors: Rohayu Izanwati M. R., Muhamad Ridhwan M. R., Abbe Maleyki M. J., Ahmad Zubaidi A. L., Zahri M. K.

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PPARs function as regulators of lipid and lipoprotein metabolism. The aim of the study was to compare the lipid profile between two phases of fasting and to examine the frequency and relationship of peroxisome proliferator-activated receptor, PPARα gene polymorphisms to lipid profile in fasting respondents. We conducted a case-control study protocol, which included 21 healthy volunteers without gender discrimination at the age of 18 years old. 3 ml of blood sample was drawn before the fasting phase and during the fasting phase (in Ramadhan month). 1ml of serum for the lipid profile was analyzed by using the automated chemistry analyser (Olympus, AU 400) and the data were analysed using the Paired T-Test (SPSS ver.20). DNA was extracted and PCR was conducted utilising 6 sets of primer. Primers were designed within 6 exons of interest in PPARα gene. Genetic and metabolic characteristics of fasting respondents and controls were estimated and compared. Fasting respondents were significantly have lowered the LDL levels (p=0.03). There were no polymorphisms detected except in exon 1 with 5% of this population study respectively. The polymorphisms in exon 1 of the PPARα gene were found in low frequency. Regarding the 1375G/T and 1386G/T polymorphisms in the exon 1 of the PPARα gene, the T-allele in fasting phase had no association with the decreased LDL levels (Fisher Exact Test). However this association is more promising when the sample size is larger in order to elucidate the precise impact of the polymorphisms on lipid profile in the population. In conclusion, the PPARα gene polymorphisms do not appear to affect the LDL of fasting respondents.

Keywords: Fasting, LDL, Peroxisome proliferator activated receptor alpha (PPAR-α), Polymorphisms.

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Authors: Farahnaz Amini, Woo Yun Kin, Lazwani Kolandaiveloo

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Availability of different genetic tests after completion of Human Genome Project increases the physicians’ responsibility to keep themselves update on the potential implementation of these genetic tests in their daily practice. However, due to numbers of barriers, still many of physicians are not either aware of these tests or are not willing to offer or refer their patients for genetic tests. This study was conducted an anonymous, cross-sectional, mailed-based survey to develop a primary data of Malaysian physicians’ level of knowledge and perception of gene profiling. Questionnaire had 29 questions. Total scores on selected questions were used to assess the level of knowledge. The highest possible score was 11. Descriptive statistics, one way ANOVA and chi-squared test was used for statistical analysis. Sixty three completed questionnaires were returned by 27 general practitioners (GPs) and 36 medical specialists. Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4). About 40% of the participants rated themselves as having poor level of knowledge in genetics in general whilst 60% believed that they have fair level of knowledge; however, almost half (46%) of the respondents felt that they were not knowledgeable about available genetic tests. A majority (94%) of the responders were not aware of any lab or company which is offering gene profiling services in Malaysia. Only 4% of participants were aware of using gene profiling for detection of dosage of some drugs. Respondents perceived greater utility of gene profiling for breast cancer (38%) compared to the colorectal familial cancer (3%). The score of knowledge ranged from 2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score of knowledge of GPs and specialists were observed, with score of 4.19 and 4.58 respectively. There was no significant association between any demographic factors and level of knowledge. However, those who graduated between years 2001 to 2005 had higher level of knowledge. Overall, 83% of participants showed relatively high level of perception on value of gene profiling to detect patient’s risk of disease. However, low perception was observed for both statements of using gene profiling for general population in order to alter their lifestyle (25%) as well as having the full sequence of a patient genome for the purpose of determining a patient’s best match for treatment (18%). The lack of clinical guidelines, limited provider knowledge and awareness, lack of time and resources to educate patients, lack of evidence-based clinical information and cost of tests were the most barriers of ordering gene profiling mentioned by physicians. In conclusion Malaysian physicians who participate in this study had mediocre level of knowledge and awareness in gene profiling. The low exposure to the genetic questions and problems might be a key predictor of lack of awareness and knowledge on available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling into practice for eligible patients.

Keywords: Gene Profiling, Knowledge, Malaysia, Physician.

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Authors: Mohamed A. Mahfouz, M. A. Ismail

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Biclustering is a very useful data mining technique for identifying patterns where different genes are co-related based on a subset of conditions in gene expression analysis. Association rules mining is an efficient approach to achieve biclustering as in BIMODULE algorithm but it is sensitive to the value given to its input parameters and the discretization procedure used in the preprocessing step, also when noise is present, classical association rules miners discover multiple small fragments of the true bicluster, but miss the true bicluster itself. This paper formally presents a generalized noise tolerant bicluster model, termed as μBicluster. An iterative algorithm termed as BIDENS based on the proposed model is introduced that can discover a set of k possibly overlapping biclusters simultaneously. Our model uses a more flexible method to partition the dimensions to preserve meaningful and significant biclusters. The proposed algorithm allows discovering biclusters that hard to be discovered by BIMODULE. Experimental study on yeast, human gene expression data and several artificial datasets shows that our algorithm offers substantial improvements over several previously proposed biclustering algorithms.

Keywords: Machine learning, biclustering, bi-dimensional clustering, gene expression analysis, data mining.

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Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani

Abstract:

The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.

Keywords: Exon7, PCR-digestion, SMA, SMN gene.

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Authors: S.Touati, A.H. Meniai

Abstract:

The present work presents the extraction of copper(II) from sulphuric acid solutions with Sodium diethyldithiocarbamate (SDDT), and six different organic diluents: Dichloromethane, Chloroform, Carbon tetrachloride, Toluene, xylene and Cyclohexane, were tested. The pair SDDT/Chloroform showed to be the most selective in removing the copper cations, and hence was considered throughout the experimental study. The effects of operating parameters such as the initial concentration of the extracting agent, the agitation time, the agitation speed and the acid concentration were considered. For an initial concentration of Cu (II) of 63 ppm in a 0.5 M sulphuric acid solution, both with a mass of the extracting agent of 20 mg, an extraction percentage of about 97.8 % and a distribution coefficient of 44.42 were obtained, respectively, confirming the performance of the SDDT-Chloroform pair.

Keywords: Copper (II), Distribution coefficient, Extraction, SDDT, Sulphuric acid.

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Authors: M. Pandi, K. Premalatha

Abstract:

The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.

Keywords: Spread out, simplex, multi-minima, fitness function, optimization, search area, monocyte, solution, genomes.

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