Search results for: gene selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3728

Search results for: gene selection

3398 Multi-Objective Evolutionary Computation Based Feature Selection Applied to Behaviour Assessment of Children

Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

Abstract:

Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

Procedia PDF Downloads 364
3397 An Empirical Investigation of Factors Influencing Construction Project Selection Processes within the Nigeria Public Sector

Authors: Emmanuel U. Unuafe, Oyegoke T. Bukoye, Sandhya Sastry, Yanqing Duan

Abstract:

Globally, there is increasing interest in project management due to a shortage in infrastructure services supply capability. Hence, it is of utmost importance that organisations understand that choosing a particular project over another is an opportunity cost – tying up the organisations resources. In order to devise constructive ways to bring direction, structure, and oversight to the process of project selection has led to the development of tools and techniques by researchers and practitioners. However, despite the development of various frameworks to assist in the appraisal and selection of government projects, failures are still being recorded with government projects. In developing countries, where frameworks are rarely used, the problems are compounded. To improve the situation, this study will investigate the current practice of construction project selection processes within the Nigeria public sector in order to inform theories of decision making from the perspective of developing nations and project management practice. Unlike other research around construction projects in Nigeria this research concentrate on factors influencing the selection process within the Nigeria public sector, which has received limited study. The authors report the findings of semi-structured interviews of top management in the Nigerian public sector and draw conclusions in terms of decision making extant theory and current practice. Preliminary results from the data analysis show that groups make project selection decisions and this forces sub-optimal decisions due to pressure on time, clashes of interest, lack of standardised framework for selecting projects, lack of accountability and poor leadership. Consequently, because decision maker is usually drawn from different fields, religious beliefs, ethnic group and with different languages. The choice of a project by an individual will be greatly influence by experience, political precedence than by realistic investigation as well as his understanding of the desired outcome of the project, in other words, the individual’s ideology and their level of fairness.

Keywords: factors influencing project selection, public sector construction project selection, projects portfolio selection, strategic decision-making

Procedia PDF Downloads 325
3396 Characterization of an Isopropanol-Butanol Clostridium

Authors: Chen Zhang, Fengxue Xin, Jianzhong He

Abstract:

A unique Clostridium beijerinckii species strain BGS1 was obtained from grass land samples, which is capable of producing 8.43g/L butanol and 3.21 isopropanol from 60g/L glucose while generating 4.68g/L volatile fatty acids (VFAs) from 30g/L xylan. The concentration of isopropanol produced by culture BGS1 is ~15% higher than previously reported wild-type Clostridium beijerinckii under similar conditions. Compared to traditional Acetone-Butanol-Ethanol (ABE) fermentation species, culture BGS1 only generates negligible amount of ethanol and acetone, but produces butanol and isopropanol as biosolvent end-products which are pure alcohols and more economical than ABE. More importantly, culture BGS1 can consume acetone to produce isopropanol, e.g., 1.84g/L isopropanol from 0.81g/L acetone in 60g/L glucose medium containing 6.15g/L acetone. The analysis of BGS1 draft genome annotated by RAST server demonstrates that no ethanol production is caused by the lack of pyruvate decarboxylase gene – related to ethanol production. In addition, an alcohol dehydrogenase (adhe gene) was found in BGS1 which could be a potential gene responsible for isopropanol-generation. This is the first report on Isopropanol-Butanol (IB) fermentation by wild-type Clostridium strain and its application for isopropanol and butanol production.

Keywords: acetone conversion, butanol, clostridium, isopropanol

Procedia PDF Downloads 286
3395 The Interplay between Autophagy and Macrophages' Polarization in Wound Healing: A Genetic Regulatory Network Analysis

Authors: Mayada Mazher, Ahmed Moustafa, Ahmed Abdellatif

Abstract:

Background: Autophagy is a eukaryotic, highly conserved catabolic process implicated in many pathophysiologies such as wound healing. Autophagy-associated genes serve as a scaffolding platform for signal transduction of macrophage polarization during the inflammatory phase of wound healing and tissue repair process. In the current study, we report a model for the interplay between autophagy-associated genes and macrophages polarization associated genes. Methods: In silico analysis was performed on 249 autophagy-related genes retrieved from the public autophagy database and gene expression data retrieved from Gene Expression Omnibus (GEO); GSE81922 and GSE69607 microarray data macrophages polarization 199 DEGS. An integrated protein-protein interaction network was constructed for autophagy and macrophage gene sets. The gene sets were then used for GO terms pathway enrichment analysis. Common transcription factors for autophagy and macrophages' polarization were identified. Finally, microRNAs enriched in both autophagy and macrophages were predicated. Results: In silico prediction of common transcription factors in DEGs macrophages and autophagy gene sets revealed a new role for the transcription factors, HOMEZ, GABPA, ELK1 and REL, that commonly regulate macrophages associated genes: IL6,IL1M, IL1B, NOS1, SOC3 and autophagy-related genes: Atg12, Rictor, Rb1cc1, Gaparab1, Atg16l1. Conclusions: Autophagy and macrophages' polarization are interdependent cellular processes, and both autophagy-related proteins and macrophages' polarization related proteins coordinate in tissue remodelling via transcription factors and microRNAs regulatory network. The current work highlights a potential new role for transcription factors HOMEZ, GABPA, ELK1 and REL in wound healing.

Keywords: autophagy related proteins, integrated network analysis, macrophages polarization M1 and M2, tissue remodelling

Procedia PDF Downloads 143
3394 Portfolio Selection with Constraints on Trading Frequency

Authors: Min Dai, Hong Liu, Shuaijie Qian

Abstract:

We study a portfolio selection problem of an investor who faces constraints on rebalancing frequency, which is common in pension fund investment. We formulate it as a multiple optimal stopping problem and utilize the dynamic programming principle. By numerically solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation, we find a series of free boundaries characterizing optimal strategy, and the constraints significantly impact the optimal strategy. Even in the absence of transaction costs, there is a no-trading region, depending on the number of the remaining trading chances. We also find that the equivalent wealth loss caused by the constraints is large. In conclusion, our model clarifies the impact of the constraints on transaction frequency on the optimal strategy.

Keywords: portfolio selection, rebalancing frequency, optimal strategy, free boundary, optimal stopping

Procedia PDF Downloads 74
3393 Gene Expression and Staining Agents: Exploring the Factors That Influence the Electrophoretic Properties of Fluorescent Proteins

Authors: Elif Tugce Aksun Tumerkan, Chris Lowe, Hannah Krupa

Abstract:

Fluorescent proteins are self-sufficient in forming chromophores with a visible wavelength from 3 amino acids sequence within their own polypeptide structure. This chromophore – a molecule that absorbs a photon of light and exhibits an energy transition equal to the energy of the absorbed photon. Fluorescent proteins (FPs) consisted of a chain of 238 amino acid residues and composed of 11 beta strands shaped in a cylinder surrounding an alpha helix structure. A better understanding of the system of the chromospheres and the increasing advance in protein engineering in recent years, the properties of FPs offers the potential for new applications. They have used sensors and probes in molecular biology and cell-based research that giving a chance to observe these FPs tagged cell localization, structural variation and movement. For clarifying functional uses of fluorescent proteins, electrophoretic properties of these proteins are one of the most important parameters. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) analysis is used for determining electrophoretic properties commonly. While there are many techniques are used for determining the functionality of protein-based research, SDS-PAGE analysis can only provide a molecular level assessment of the proteolytic fragments. Before SDS-PAGE analysis, fluorescent proteins need to successfully purified. Due to directly purification of the target, FPs is difficult from the animal, gene expression is commonly used which must be done by transformation with the plasmid. Furthermore, used gel within electrophoresis and staining agents properties have a key role. In this review, the different factors that have the impact on the electrophoretic properties of fluorescent proteins explored. Fluorescent protein separation and purification are the essential steps before electrophoresis that should be done very carefully. For protein purification, gene expression process and following steps have a significant function. For successful gene expression, the properties of selected bacteria for expression, used plasmid are essential. Each bacteria has own characteristics which are very sensitive to gene expression, also used procedure is the important factor for fluorescent protein expression. Another important factors are gel formula and used staining agents. Gel formula has an effect on the specific proteins mobilization and staining with correct agents is a key step for visualization of electrophoretic bands of protein. Visuality of proteins can be changed depending on staining reagents. Apparently, this review has emphasized that gene expression and purification have a stronger effect than electrophoresis protocol and staining agents.

Keywords: cell biology, gene expression, staining agents, SDS-page

Procedia PDF Downloads 188
3392 Real-Time Multi-Vehicle Tracking Application at Intersections Based on Feature Selection in Combination with Color Attribution

Authors: Qiang Zhang, Xiaojian Hu

Abstract:

In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 157
3391 The Construction of a Probiotic Lactic Acid Bacterium Expressing Acid-Resistant Phytase Enzyme

Authors: R. Majidzadeh Heravi, M. Sankian, H. Kermanshahi, M. R. Nassiri, A. Heravi Moussavi, S. A. Lari, A. R. Varasteh

Abstract:

The use of probiotics engineered to express specific enzymes has been the subject of considerable attention in poultry industry because of increased nutrient availability and reduced cost of enzyme supplementation. Phytase enzyme is commonly added to poultry feed to improve digestibility and availability of phosphorus from plant sources. To construct a probiotic with potential of phytate degradation, phytase gene (appA) from E. coli was cloned and transformed into two probiotic bacteria Lactobacillus salivarius and Lactococcus lactis. L. salivarous showed plasmid instability, unable to express the gene. The expression of appA gene in L. lactis was analyzed by detecting specific RNA and zymography assay. Phytase enzyme was isolated from cellular extracts of recombinant L. lactis, showing a 46 kDa band upon the SDS-PAGE analysis. Zymogram also confirmed the phytase activity of the 46 kDa band corresponding to the enzyme. An enzyme activity of 4.9U/ml was obtained in cell extracts of L. lactis. The growth of native and recombinant L. lactis was similar in the presence of two concentrations of ox bile.

Keywords: Lactobacillus salivarus, Lactococcuslactis, recombinant, phytase, poultry

Procedia PDF Downloads 481
3390 Habitat-Specific Divergences in the Gene Repertoire among the Reference Prevotella Genomes of the Human Microbiome

Authors: Vinod Kumar Gupta, Narendrakumar M. Chaudhari, Suchismitha Iskepalli, Chitra Dutta

Abstract:

Background-The community composition of the human microbiome is known to vary at distinct anatomical niches. But little is known about the nature of variations if any, at the genome/sub-genome levels of a specific microbial community across different niches. The present report aims to explore, as a case study, the variations in gene repertoire of 28 Prevotella reference draft genomes derived from different body-sites of human, as reported earlier by the Human Microbiome Consortium. Results-The analysis reveals the exclusive presence of 11798, 3673, 3348 and 934 gene families and exclusive absence of 17, 221, 115 and 645 gene families in Prevotella genomes derived from the human oral cavity, gastro-intestinal tracts (GIT), urogenital tract (UGT) and skin, respectively. The pan-genome for Prevotella remains “open”. Distribution of various functional COG categories differs appreciably among the habitat-specific genes, within Prevotella pan-genome and between the GIT-derived Bacteroides and Prevotella. The skin and GIT isolates of Prevotella are enriched in singletons involved in Signal transduction mechanisms, while the UGT and oral isolates show higher representation of the Defense mechanisms category. No niche-specific variations could be observed in the distribution of KEGG pathways. Conclusion-Prevotella may have developed distinct genetic strategies for adaptation to different anatomical habitats through selective, niche-specific acquisition and elimination of suitable gene-families. In addition, individual microorganisms tend to develop their own distinctive adaptive stratagems through large repertoires of singletons. Such in situ, habitat-driven refurbishment of the genetic makeup can impart substantial intra-lineage genome diversity within the microbes without perturbing their general taxonomic heritage.

Keywords: body niche adaptation, human microbiome, pangenome, Prevotella

Procedia PDF Downloads 245
3389 Phenotypical and Genotypical Diagnosis of Cystic Fibrosis in 26 Cases from East and South Algeria

Authors: Yahia Massinissa, Yahia Mouloud

Abstract:

Cystic fibrosis (CF), the most common lethal genetic disease in the Europe population, is caused by mutations in the transmembrane conductance regulator gene (CFTR). It affects most organs including an epithelial tissue, base of hydroelectrolytic transepithelial transport, notably that aerial ways, the pancreas, the biliary ways, the intestine, sweat glands and the genital tractus. The gene whose anomalies are responsible of the cystic fibrosis codes for a protein Cl channel named CFTR (cystic fibrosis transmembrane conductance regulator) that exercises multiple functions in the cell, one of the most important in control of sodium and chlorine through epithelia. The deficient function translates itself notably by an abnormal production of viscous secretion that obstructs the execrator channels of this target organ: one observes then a dilatation, an inflammation and an atrophy of these organs. It also translates itself by an increase of the concentration in sodium and in chloride in sweat, to the basis of the sweat test. In order to do a phenotypical and genotypical diagnosis at a part of the Algerian population, our survey has been carried on 16 patients with evocative symptoms of the cystic fibrosis at that the clinical context has been confirmed by a sweat test. However, anomalies of the CFTR gene have been determined by electrophoresis in gel of polyacrylamide of the PCR products (polymerase chain reaction), after enzymatic digestion, then visualized to the ultraviolet (UV) after action of the ethidium bromide. All mutations detected at the time of our survey have already been identified at patients attained by this pathology in other populations of the world. However, the important number of found mutation with regard to the one of the studied patients testifies that the origin of this big clinical variability that characterizes the illness in the consequences of an enormous diversity of molecular defects of the CFTR gene.

Keywords: cystic fibrosis, CFTR gene, polymorphism, algerian population, sweat test, genotypical diagnosis

Procedia PDF Downloads 302
3388 Integrating Dynamic Brain Connectivity and Transcriptomic Imaging in Major Depressive Disorder

Authors: Qingjin Liu, Jinpeng Niu, Kangjia Chen, Jiao Li, Huafu Chen, Wei Liao

Abstract:

Functional connectomics is essential in cognitive science and neuropsychiatry, offering insights into the brain's complex network structures and dynamic interactions. Although neuroimaging has uncovered functional connectivity issues in Major Depressive Disorder (MDD) patients, the dynamic shifts in connectome topology and their link to gene expression are yet to be fully understood. To explore the differences in dynamic connectome topology between MDD patients and healthy individuals, we conducted an extensive analysis of resting-state functional magnetic resonance imaging (fMRI) data from 434 participants (226 MDD patients and 208 controls). We used multilayer network models to evaluate brain module dynamics and examined the association between whole-brain gene expression and dynamic module variability in MDD using publicly available transcriptomic data. Our findings revealed that compared to healthy individuals, MDD patients showed lower global mean values and higher standard deviations, indicating unstable patterns and increased regional differentiation. Notably, MDD patients exhibited more frequent module switching, primarily within the executive control network (ECN), particularly in the left dorsolateral prefrontal cortex and right fronto-insular regions, whereas the default mode network (DMN), including the superior frontal gyrus, temporal lobe, and right medial prefrontal cortex, displayed lower variability. These brain dynamics predicted the severity of depressive symptoms. Analyzing human brain gene expression data, we found that the spatial distribution of MDD-related gene expression correlated with dynamic module differences. Cell type-specific gene analyses identified oligodendrocytes (OPCs) as major contributors to the transcriptional relationships underlying module variability in MDD. To the best of our knowledge, this is the first comprehensive description of altered brain module dynamics in MDD patients linked to depressive symptom severity and changes in whole-brain gene expression profiles.

Keywords: major depressive disorder, module dynamics, magnetic resonance imaging, transcriptomic

Procedia PDF Downloads 9
3387 Detecting Memory-Related Gene Modules in sc/snRNA-seq Data by Deep-Learning

Authors: Yong Chen

Abstract:

To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

Procedia PDF Downloads 116
3386 Cost Sensitive Feature Selection in Decision-Theoretic Rough Set Models for Customer Churn Prediction: The Case of Telecommunication Sector Customers

Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

Abstract:

In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

Procedia PDF Downloads 440
3385 Microarray Data Visualization and Preprocessing Using R and Bioconductor

Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

Abstract:

Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

Procedia PDF Downloads 472
3384 Cotton Fiber Quality Improvement by Introducing Sucrose Synthase (SuS) Gene into Gossypium hirsutum L.

Authors: Ahmad Ali Shahid, Mukhtar Ahmed

Abstract:

The demand for long staple fiber having better strength and length is increasing with the introduction of modern spinning and weaving industry in Pakistan. Work on gene discovery from developing cotton fibers has helped to identify dozens of genes that take part in cotton fiber development and several genes have been characterized for their role in fiber development. Sucrose synthase (SuS) is a key enzyme in the metabolism of sucrose in a plant cell, in cotton fiber it catalyzes a reversible reaction, but preferentially converts sucrose and UDP into fructose and UDP-glucose. UDP-glucose (UDPG) is a nucleotide sugar act as a donor for glucose residue in many glycosylation reactions and is essential for the cytosolic formation of sucrose and involved in the synthesis of cell wall cellulose. The study was focused on successful Agrobacterium-mediated stable transformation of SuS gene in pCAMBIA 1301 into cotton under a CaMV35S promoter. Integration and expression of the gene were confirmed by PCR, GUS assay, and real-time PCR. Young leaves of SuS overexpressing lines showed increased total soluble sugars and plant biomass as compared to non-transgenic control plants. Cellulose contents from fiber were significantly increased. SEM analysis revealed that fibers from transgenic cotton were highly spiral and fiber twist number increased per unit length when compared with control. Morphological data from field plants showed that transgenic plants performed better in field conditions. Incorporation of genes related to cotton fiber length and quality can provide new avenues for fiber improvement. The utilization of this technology would provide an efficient import substitution and sustained production of long-staple fiber in Pakistan to fulfill the industrial requirements.

Keywords: agrobacterium-mediated transformation, cotton fiber, sucrose synthase gene, staple length

Procedia PDF Downloads 227
3383 Investigation of FoxM1 Gene Expression in Breast Cancer and Its Relationship with miR-216b-5p Expression Level

Authors: Neda Menbari, Ramin Mehdiabadi

Abstract:

Background: breast cancer remains a critical global health issue, constituting a leading cause of cancer-related mortality in women. MicroRNAs (miRs) are natural RNA molecules that play an important role in cellular processes and regulate post-transcriptional gene expression. MiR-216b-5p is a miR that acts as a tumor suppressor. The expression levels of FoxM1 and miR-216b-5p in malignant and control cells have been evaluated by quantitative polymerase chain reaction (qPCR) technique and flow cytometry. Results: the results of this study revealed a significant downregulation of miR-216b-5p in cancerous cells compared to the control MCF-10A cells (P=0.0004). Interestingly, the expression of miR-216b-5p exhibited an inverse relationship with key clinical indicators such as tumor size, grade, and lymph node invasion. Conclusion: The study's findings showed the prognostic value of miR-216b-5p levels in breast cancer, and its reduced expression correlates with unfavorable tumor characteristics. This research recommends performing more studies on the role of FoxM1 and miR-216b-5p in breast cancer pathology which potentially paving the way for targeted therapeutic interventions.

Keywords: breast cancer, gene expression, FOXM1, microRNA

Procedia PDF Downloads 41
3382 Correlation between Polysaccharides Molecular Weight Changes and Pectinases Gene Expression during Papaya Ripening

Authors: Samira B. R. Prado, Paulo R. Melfi, Beatriz T. Minguzzi, João P. Fabi

Abstract:

Fruit softening is the main change that occurs during papaya (Carica papaya L.) ripening. It is characterized by the depolymerization of cell wall polysaccharides, especially the pectic fractions, which causes cell wall disassembling. However, it is uncertain how the modification of the two main pectin polysaccharides fractions (water-soluble – WSF, and oxalate-soluble fractions - OSF) accounts for fruit softening. The aim of this work was to correlate molecular weight changes of WSF and OSF with the gene expression of pectin-solubilizing enzymes (pectinases) during papaya ripening. Papaya fruits obtained from a producer were harvest and storage under specific conditions. The fruits were divided in five groups according to days after harvesting. Cell walls from all groups of papaya pulp were isolated and fractionated (WSF and OSF). Expression profiles of pectinase genes were achieved according to the MIQE guidelines (Minimum Information for publication of Quantitative real-time PCR Experiments). The results showed an increased yield and a decreased molecular weight throughout ripening for WSF and OSF. Gene expression data support that papaya softening is achieved by polygalacturonases (PGs) up-regulation, in which their actions might have been facilitated by the constant action of pectinesterases (PMEs). Moreover, BGAL1 gene was up-regulated during ripening with a simultaneous galactose release, suggesting that galactosidases (GALs) could also account for pulp softening. The data suggest that a solubilization of galacturonans and a depolymerization of cell wall components were caused mainly by the action of PGs and GALs.

Keywords: carica papaya, fruit ripening, galactosidases, plant cell wall, polygalacturonases

Procedia PDF Downloads 416
3381 Genome-Wide Analysis of BES1/BZR1 Gene Family in Five Plant Species

Authors: Jafar Ahmadi, Zhohreh Asiaban, Sedigheh Fabriki Ourang

Abstract:

Brassinosteroids (BRs) regulate cell elongation, vascular differentiation, senescence and stress responses. BRs signal through the BES1/BZR1 family of transcription factors, which regulate hundreds of target genes involved in this pathway. In this research a comprehensive genome-wide analysis was carried out in BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus, Vitis vinifera, Glycin max, and Brachypodium distachyon. Specifications of the desired sequences, dot plot and hydropathy plot were analyzed in the protein and genome sequences of five plant species. The maximum amino acid length was attributed to protein sequence Brdic3g with 374aa and the minimum amino acid length was attributed to protein sequence Gm7g with 163aa. The maximum Instability index was attributed to protein sequence AT1G19350 equal with 79.99 and the minimum Instability index was attributed to protein sequence Gm5g equal with 33.22. Aliphatic index of these protein sequences ranged from 47.82 to 78.79 in Arabidopsis thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in Cucumis sativus. Overall, data obtained from our investigation contributes a better understanding of the complexity of the BES1/BZR1 gene family and provides the first step towards directing future experimental designs to perform systematic analysis of the functions of the BES1/BZR1 gene family.

Keywords: BES1/BZR1, brassinosteroids, phylogenetic analysis, transcription factor

Procedia PDF Downloads 331
3380 Ring FingerPortein 2 (RNF2) Targeting by miRNAs in Breast Cancer Cell Lines

Authors: Ceyda Okudu, Secil Eroglu, Khandakar A. S. M. Saadat, Sibel O. Balci

Abstract:

Ring Finger Protein 2 (RNF2) is a member of polycomb repressive complex 1 (PRC1), which is one of the epigenetic regulators in the genome. When RNF2 combines with other PRC1 members, it mediates the mono-ubiquitination of Histon2A (H2A). In breast cancer, RNF2 is commonly overexpressed, and also it promotes metastasis and invasion in other aggressive tumors like melanoma, prostate, and hepatocarcinoma. The role of RNF2 in the metastasis and invasion of breast cancer has not yet been elucidated. Our aim is to observe the role of RNF2 in metastasis and invasion in this study by miRNA mediated RNF2 gene silencing in breast cancer cell lines. We selected miRNAs, targeting to RNF2 by searching online databases. miR-17-5p, miR20a-5p, and miR-106b-5p were transfected to breast cancer cell lines (MCF-7, MDA-MB-231, SK-BR-3, and ZR-75-1), and also we used normal breast epithelial cell line (hTERT-HME1) to compare RNF2 gene expression level. After 48-72 hours post-transfection, mRNAs were isolated from the cells, and gene expressions were measured by RT-qPCR after from cDNA syntheses. We observed that RNF2 was highly expressed in SK-BR-3 and MDA-MB-231 cell lines opposite to MCF-7 and ZR-75-1 cell lines. RNF2 was downregulated 5, 5 and 7 fold by miR17-5p, miR20a-5p and miR106b-5p respectively in MCF-7. However, in SK-BR-3 and ZR-75-1 cell lines, miRNAs did not affect significantly RNF2 gene expression level. miR20a-5p decreased RNF2 3 fold and miR17-5p and miR106b-5p did not affect MDA-MB-231. After gene expression analysis, we performed metastasis and invasion assay in MCF-7 cells. For metastasis, we used both wound healing assay and Transwell Cell Migration Assay, and we used Transwell Cell Invasion Assay for invasion. The data of this assay showed that miR17-5p and miR20a-5p decreased both invasion and metastasis level, but miR106b-5p has no effect. We would like to conclude that RNF2 can be targeted by miR17-5p, miR20a-5p and miR106b-5p in MCF-7 cells and also RNF2, which is one of the upregulated genes in aggressive tumor, can be decreased by using these miRNAs. In future, we would like to confirm these results at the protein level and also whether these miRNAs are direct target of RNF2 or not.

Keywords: breast cancer, epigenetic, microRNAs, RNF2

Procedia PDF Downloads 171
3379 Usability Evaluation in Practice: Selecting the Appropriate Method

Authors: Hanan Hayat, Russell Lock

Abstract:

The importance of usability in ensuring software quality has been well established in literature and widely accepted by software development practitioners. Consequently, numerous usability evaluation methods have been developed. However, the availability of large variety of evaluation methods alongside insufficient studies that critically analyse them resulted in an ambiguous process of selection amongst non-usability-expert practitioners. This study investigates the factors affecting the selection of usability evaluation methods within a project by interviewing a software development team. The results of the data gathered are then analysed and integrated in developing a framework. The framework developed poses a solution to the selection processes of usability evaluation methods by adjusting to individual projects resources and goals. It has the potential to be further evaluated to verify its applicability and usability within the domain of this study.

Keywords: usability evaluation, evaluating usability in non-user entered designs, usability evaluation methods (UEM), usability evaluation in projects

Procedia PDF Downloads 148
3378 An Adjusted Network Information Criterion for Model Selection in Statistical Neural Network Models

Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

Abstract:

In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

Procedia PDF Downloads 559
3377 CMT4G: Rare Form of Charcot-Marie-Tooth Disease in Slovak Roma Patient

Authors: Dana Gabriková, Martin Mistrík, Jarmila Bernasovská, Iveta Tóthová, Jana Kisková

Abstract:

The Roma (Gypsies) is a transnational minority with a high degree of consanguineous marriages. Similar to other genetically isolated founder populations, the Roma harbor a number of unique or rare genetic disorders. This paper discusses about a rare form of Charcot-Marie-Tooth disease – type 4G (CMT4G), also called Hereditary Motor and Sensory Neuropathy type Russe, an autosomal recessive disease caused by mutation private to Roma characterized by abnormally increased density of non-myelinated axons. CMT4G was originally found in Bulgarian Roma and in 2009 two putative causative mutations in the HK1 gene were identified. Since then, several cases were reported in Roma families mainly from Bulgaria and Spain. Here we present a Slovak Roma family in which CMT4G was diagnosed on the basis of clinical examination and genetic testing. This case is a further proof of the role of the HK1 gene in pathogenesis of the disease. It confirms that mutation in the HK1 gene is a common cause of autosomal recessive CMT disease in Roma and should be considered as a common part of a diagnostic procedure.

Keywords: gypsies, HK1, HSMN-Russe, rare disease

Procedia PDF Downloads 381
3376 lncRNA Gene Expression Profiling Analysis by TCGA RNA-Seq Data of Breast Cancer

Authors: Xiaoping Su, Gabriel G. Malouf

Abstract:

Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor.

Keywords: lncRNA profiling, breast cancer, HOTAIRM1, tumor suppressor

Procedia PDF Downloads 100
3375 Bioinformatic Prediction of Hub Genes by Analysis of Signaling Pathways, Transcriptional Regulatory Networks and DNA Methylation Pattern in Colon Cancer

Authors: Ankan Roy, Niharika, Samir Kumar Patra

Abstract:

Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.

Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions

Procedia PDF Downloads 124
3374 Construction of Genetic Recombinant Yeasts with High Environmental Tolerance by Accumulation of Trehalose and Detoxication of Aldehyde

Authors: Yun-Chin Chung, Nileema Divate, Gen-Hung Chen, Pei-Ru Huang, Rupesh Divate

Abstract:

Many environmental factors, such as glucose concentration, ethanol, temperature, osmotic pressure and pH, decrease the production rate of ethanol using yeast as a starter. Fermentation starters with high tolerance to various stresses are always demanded for brewing industry. Trehalose, a storage carbohydrate in cell wall of yeast, plays an important role in tolerance of environmental stress by preserving integrity of plasma membrane and stabilizing proteins. Furan aldehydes are toxic to yeast and the growth rate of yeast is significantly reduced if furan aldehydes were present in the fermentation medium. In yeast, aldehyde reductase is involved in the detoxification of reactive aldehydes and consequently the growth of yeast is improved. The aims of this study were to construct a genetic recombinant Saccharomyces cerevisiae or Pichia pastoris with furfural and HMF degrading and high ethanol tolerance capacities. Yeast strains were engineered by genetic recombination for overexpression of trehalose-6-phosphate synthase gene (tps1) and aldehyde reductase gene (ari1). TPS1 gene was cloned from S. cerevisiae by reverse transcription-polymerase chain reaction (RT-PCR) and then ligated with pGAPZαC vector. The constructed vector, pGAPZC-tps1, was transformed to recombinant yeasts strain with overexpression of ari1. The transformants with pGAPZC-tps1-ari1 were generated called STA (S. cerevisiae) and PTA (P. pastoris) with overexpression of tps1, ari1. PCR with tps1-specific primers and western blot with his-tag confirmed the gene insertion and protein expression of tps1 in the transformants, respectively. The neutral trehalase gene (nth1) of STA was successfully deleted and the novel strain STAΔN will be used for further study, including the measurement of trehalose concentration and ethanol, furfural tolerance assay.

Keywords: genetic recombinant, yeast, ethanol tolerance, trehalase, aldehyde reductase

Procedia PDF Downloads 414
3373 Expression of ULK-1 mRNA in Human Peripheral Blood Mononuclear Cells from Patients with Alzheimer's Disease

Authors: Ali Bayram, Remzi Yiğiter

Abstract:

Objective: Alzheimer's disease (AD), the most common cause of dementia, is a progressive neurodegenerative disease. At present, diagnosis of AD is rather late in the disease. Therefore, we attempted to find peripheral biomarkers for the early diagnosis of AD. Herein, we conducted a study to investigate the unc-51 like autophagy activating kinase-1 (ULK1) mRNA expression levels in human peripheral blood mononuclear cells from patients with Alzheimer's disease. Method: To determine whether ULK1 gene expression are altered in AD patients, we measured their gene expression in human peripheral blood cell in 50 patients with AD and 50 age and gender matched healthy controls by quantitative real-time PCR technique. Results: We found that both ULK1 gene expression in peripheral blood cell were significantly decreased in patients with AD as compared with controls (p <0.05). Lower levels of ULK1 gene expression were significantly associated with the increased risk for AD. Conclusions: Serine/threonine-protein kinase involved in autophagy in response to starvation. Acts upstream of phosphatidylinositol 3-kinase PIK3C3 to regulate the formation of autophagophores, the precursors of autophagosomes. Part of regulatory feedback loops in autophagy: acts both as a downstream effector and negative regulator of mammalian target of rapamycin complex 1 (mTORC1) via interaction with RPTOR. Activated via phosphorylation by AMPK and also acts as a regulator of AMPK by mediating phosphorylation of AMPK subunits PRKAA1, PRKAB2, and PRKAG1, leading to negatively regulate AMPK activity. May phosphorylate ATG13/KIAA0652 and RPTOR; however such data need additional evidences. Plays a role early in neuronal differentiation and is required for granule cell axon formation. Alzheimer is the most common neurodegenerative disease. Our results provide useful information that the ULK1 gene expression is decreased in the neurodegeneration and AD patients with, indicating their possible systemic involvement in AD.

Keywords: Alzheimer’s sisease, ULK1, mRNA expression, RT-PCR

Procedia PDF Downloads 394
3372 Clothing and Personnel Selection: An Experimental Study to Test the Effects of Dress Style on Hirability Perceptions

Authors: Janneke K. Oostrom, Richard Ronay

Abstract:

The so called “red sneakers effect” refers to people’s inclination to infer status and competence from signals of nonconformity. In the current research, we explore an untested possible boundary condition to the red sneakers effect within the context of personnel selection. In two experimental studies (total N = 156), we examined how (non)conforming dress style interacts with the quality of a job applicant’s resume to determine hirability perceptions. We found that dress style indeed impacts hirability perceptions, but that the exact impact depends on the quality of the applicant’s resume. Results revealed that applicants with a low quality resume were punished for behaving in a nonconforming way, whereas applicants with a high quality resume appeared to have the leeway to dress as they please. Importantly, the observed interaction effect was mediated by perceptions of power. These findings suggest that nonconforming dress acts as a power-signaling mechanism in the context of personnel selection. However, the signaling effects of non-conforming dress style can backfire when accompanied by evidence that such posturing is not matched by cues of actual competence.

Keywords: clothing, hirability, nonconformity, personnel selection, power

Procedia PDF Downloads 172
3371 Effects of Physical Activity on the Association of CETP Gene with HDL Cholesterol Levels in Korean Population

Authors: Jae Woong Sull, Sun Ha Jee

Abstract:

High-density lipoprotein (HDL) cholesterol levels are associated with decreased risk of coronary artery disease. Several genome-wide association studies (GWAS) for HDL cholesterol levels have implicated cholesterol ester transfer protein (CETP) as possibly causal. We tested for the association between single nucleotide polymorphisms (SNPs) in CETP gene and HDL cholesterol levels in Korean population. Subjects were selected from the Korean Metabolic Syndrome Research Initiative study in the Bundang-Gu area. A total of 2,304 individuals from Bundang-Gu were recruited in 2008. Other subjects were selected from the Severance Hospital (N=4,294). SNP rs6499861 in the CETP gene was associated with mean HDL cholesterol levels (effect per allele -2.044 mg/dL, p=7.23×10-7). Subjects with the CG/GG genotype had a 1.46 -fold (range 1.24–1.72-fold) higher risk of having abnormal HDL cholesterol levels (<40 mg/dL) than subjects with the CC genotype. When analyzed by gender, the association of CETP was stronger in women than in men. When analyzed by physical activity behavior, the association with CETP was much stronger in male subjects with low physical activity (OR=1.54, 95% CI: 1.23-1.92, P=0.0001) than in male subjects with high physical activity. This study clearly demonstrates that genetic variants in CETP influence HDL cholesterol levels in Korean adults.

Keywords: CETP, HDL cholesterol, physical activity, polymorphisms

Procedia PDF Downloads 281
3370 Nest-Site Selection of Crested Lark (Galerida cristata) in Yazd Province, Iran

Authors: Shirin Aghanajafizadeh

Abstract:

Nest site selection of Crested Lark was investigated in Boroyeh wildlife sanctuary of Harat during spring 2014. Habitat variables such as number of plant species, soil texture, distance to the nearest water resources, farms and roads were compared in the species presence plots with absence ones. Our analysis showed that the average number of Zygophyllum atriplicoidesand, Artemisia sieberi were higher while fine-textured soil percent cover (with very little and gravel) was lower in species presence plots than control plots. We resulted that the most affecting factor in the species nest site selection is the number of Z .atriplicoides and soil texture. Z. atriplicoides and A. sieberi can provide cover for nests and chickens against predators and environmental harsh events such as sunshine and wind. The stability of built nest forces the birds to select sites with not fine-textured soil. Some of the nests were detected in Alfalfa farms that can be related to its cover producing capability.

Keywords: habitat selection, Yazd Province, presence and absence plots, habitat variables

Procedia PDF Downloads 177
3369 Vendor Selection and Supply Quotas Determination by Using Revised Weighting Method and Multi-Objective Programming Methods

Authors: Tunjo Perič, Marin Fatović

Abstract:

In this paper a new methodology for vendor selection and supply quotas determination (VSSQD) is proposed. The problem of VSSQD is solved by the model that combines revised weighting method for determining the objective function coefficients, and a multiple objective linear programming (MOLP) method based on the cooperative game theory for VSSQD. The criteria used for VSSQD are: (1) purchase costs and (2) product quality supplied by individual vendors. The proposed methodology is tested on the example of flour purchase for a bakery with two decision makers.

Keywords: cooperative game theory, multiple objective linear programming, revised weighting method, vendor selection

Procedia PDF Downloads 351