Sentiment Classification of Customer Reviews about Automobiles in Roman Urdu

Text mining is a broad field having sentiment mining as its important constituent in which we try to deduce the behavior of people towards a specific item, merchandise, politics, sports, social media comments, review sites etc. Out of many issues in sentiment mining, analysis and classification, one major issue is that the reviews and comments can be in different languages like English, Arabic, Urdu etc. Handling each language according to its rules is a difficult task. A lot of research work has been done in English Language for sentiment analysis and classification but limited sentiment analysis work is being carried out on other regional languages like Arabic, Urdu and Hindi. In this paper, Waikato Environment for Knowledge Analysis (WEKA) is used as a platform to execute different classification models for text classification of Roman Urdu text. Reviews dataset has been scrapped from different automobiles sites. These extracted Roman Urdu reviews, containing 1000 positive and 1000 negative reviews, are then saved in WEKA attribute-relation file format (arff) as labeled examples. Training is done on 80% of this data and rest of it is used for testing purpose which is done using different models and results are analyzed in each case. The results show that Multinomial Naive Bayes outperformed Bagging, Deep Neural Network, Decision Tree, Random Forest, AdaBoost, k-NN and SVM Classifiers in terms of more accuracy, precision, recall and F-measure.Comment: This is a pre-print of a contribution published in Advances in Intelligent Systems and Computing (editors: Kohei Arai, Supriya Kapoor and Rahul Bhatia) published by Springer, Cham. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-03405-4_4

Promoter hypermethylation and histone hypoacetylation contribute to pancreatic-duodenal homeobox 1 silencing in gastric cancer

Background and Aims: The expression of pancreatic-duodenal homeobox 1 (PDX1) in gastric cancer is aberrantly reduced. The aim of this study was to elucidate the regulation of DNA methylation and histone acetylation at the promoter for PDX1 silencing in gastric cancer. Methods: PDX1 expression in response to demethylation and acetylation was detected in human gastric cancer cell lines by reverse transcription-polymerase chain reaction (PCR) and western blot. Four CpG islands within the 5#-flanking region of PDX1 gene were analyzed with their transcription activities being detected by dual luciferase assay. Promoter hypermethylation was identified in gastric cancer cell lines and cancer tissues by methylation-specific PCR or bisulfite DNA sequencing PCR analysis. Histone acetylation was determined by chromatin immunoprecipitation (ChIP) assay. Results: Demethylation by 5′-aza-2′-deoxycytidine (5′-aza-dC) and/or acetylation by trichostatin A (TSA) restored PDX1 expression in gastric cancer cells. Hypermethylation was found in four CpG islands in six of seven cancer cell lines. However, only the distal CpG island located in the promoter fragment of PDX1, F383 (c.22063 to 21681 nt upstream of the ATG start codon) displayed significant transcriptional activity that could be suppressed by SssI methylase and increased by 5′-aza-dC and TSA. More than 70% of the single CpG sites in F383 were methylated with hypermethylation of F383 fragment more common in gastric cancerous tissues compared with the paired normal tissues (P < 0.05). ChIP assay showed F383 was also associated with low hypoacetylation level of the histones. Conclusion: Promoter hypermethylation and histone hypoacetylation contribute to PDX1 silencing in gastric cancer. © The Author 2010. Published by Oxford University Press. All rights reserved.postprin

A synthetic gene network for tuning protein degradation in Saccharomyces cerevisiae

Protein decay rates are regulated by degradation machinery that clears unnecessary housekeeping proteins and maintains appropriate dynamic resolution for transcriptional regulators. Turnover rates are also crucial for fluorescence reporters that must strike a balance between sufficient fluorescence for signal detection and temporal resolution for tracking dynamic responses. Here, we use components of the Escherichia coli degradation machinery to construct a Saccharomyces cerevisiae strain that allows for tunable degradation of a tagged protein. Using a microfluidic platform tailored for single-cell fluorescence measurements, we monitor protein decay rates after repression using an ssrA-tagged fluorescent reporter. We observe a half-life ranging from 91 to 22 min, depending on the level of activation of the degradation genes. Computational modeling of the underlying set of enzymatic reactions leads to GFP decay curves that are in excellent agreement with the observations, implying that degradation is governed by Michaelis–Menten-type interactions. In addition to providing a reporter with tunable dynamic resolution, our findings set the stage for explorations of the effect of protein degradation on gene regulatory and signalling pathways

Conducting retrospective impact analysis to inform a medical research charity’s funding strategies: The case of Asthma UK

© 2013 Hanney et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.BACKGROUND: Debate is intensifying about how to assess the full range of impacts from medical research. Complexity increases when assessing the diverse funding streams of funders such as Asthma UK, a charitable patient organisation supporting medical research to benefit people with asthma. This paper aims to describe the various impacts identified from a range of Asthma UK research, and explore how Asthma UK utilised the characteristics of successful funding approaches to inform future research strategies. METHODS: We adapted the Payback Framework, using it both in a survey and to help structure interviews, documentary analysis, and case studies. We sent surveys to 153 lead researchers of projects, plus 10 past research fellows, and also conducted 14 detailed case studies. These covered nine projects and two fellowships, in addition to the innovative case studies on the professorial chairs (funded since 1988) and the MRC-Asthma UK Centre in Allergic Mechanisms of Asthma (the ‘Centre’) which together facilitated a comprehensive analysis of the whole funding portfolio. We organised each case study to capture whatever academic and wider societal impacts (or payback) might have arisen given the diverse timescales, size of funding involved, and extent to which Asthma UK funding contributed to the impacts. RESULTS: Projects recorded an average of four peer-reviewed journal articles. Together the chairs reported over 500 papers. All streams of funding attracted follow-on funding. Each of the various categories of societal impacts arose from only a minority of individual projects and fellowships. Some of the research portfolio is influencing asthma-related clinical guidelines, and some contributing to product development. The latter includes potentially major breakthroughs in asthma therapies (in immunotherapy, and new inhaled drugs) trialled by university spin-out companies. Such research-informed guidelines and medicines can, in turn, contribute to health improvements. The role of the chairs and the pioneering collaborative Centre is shown as being particularly important. CONCLUSIONS: We systematically demonstrate that all types of Asthma UK’s research funding assessed are making impacts at different levels, but the main societal impacts from projects and fellowships come from a minority of those funded. Asthma UK used the study’s findings, especially in relation to the Centre, to inform research funding strategies to promote the achievement of impact.This study was funded by Asthma UK

Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family

<p>Abstract</p> <p>Background</p> <p>Five DNA regions, namely, <it>rbcL</it>, <it>matK</it>, ITS, ITS2, and <it>psbA-trnH</it>, have been recommended as primary DNA barcodes for plants. Studies evaluating these regions for species identification in the large plant taxon, which includes a large number of closely related species, have rarely been reported.</p> <p>Results</p> <p>The feasibility of using the five proposed DNA regions was tested for discriminating plant species within Asteraceae, the largest family of flowering plants. Among these markers, ITS2 was the most useful in terms of universality, sequence variation, and identification capability in the Asteraceae family. The species discriminating power of ITS2 was also explored in a large pool of 3,490 Asteraceae sequences that represent 2,315 species belonging to 494 different genera. The result shows that ITS2 correctly identified 76.4% and 97.4% of plant samples at the species and genus levels, respectively. In addition, ITS2 displayed a variable ability to discriminate related species within different genera.</p> <p>Conclusions</p> <p>ITS2 is the best DNA barcode for the Asteraceae family. This approach significantly broadens the application of DNA barcoding to resolve classification problems in the family Asteraceae at the genera and species levels.</p

A markov classification model for metabolic pathways

<p>Abstract</p> <p>Background</p> <p>This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first identifies frequently traversed network paths using a Markov mixture model. Then by employing a hierarchical mixture of experts, separate classifiers are built using information specific to each path and combined into an ensemble prediction for the response.</p> <p>Results</p> <p>We compared the performance of HME3M with logistic regression and support vector machines (SVM) for both simulated pathways and on two metabolic networks, glycolysis and the pentose phosphate pathway for <it>Arabidopsis thaliana</it>. We use AltGenExpress microarray data and focus on the pathway differences in the developmental stages and stress responses of <it>Arabidopsis</it>. The results clearly show that HME3M outperformed the comparison methods in the presence of increasing network complexity and pathway noise. Furthermore an analysis of the paths identified by HME3M for each metabolic network confirmed known biological responses of <it>Arabidopsis</it>.</p> <p>Conclusions</p> <p>This paper clearly shows HME3M to be an accurate and robust method for classifying metabolic pathways. HME3M is shown to outperform all comparison methods and further is capable of identifying known biologically active pathways within microarray data.</p

DNA Barcode Goes Two-Dimensions: DNA QR Code Web Server

The DNA barcoding technology uses a standard region of DNA sequence for species identification and discovery. At present, “DNA barcode” actually refers to DNA sequences, which are not amenable to information storage, recognition, and retrieval. Our aim is to identify the best symbology that can represent DNA barcode sequences in practical applications. A comprehensive set of sequences for five DNA barcode markers ITS2, rbcL, matK, psbA-trnH, and CO1 was used as the test data. Fifty-three different types of one-dimensional and ten two-dimensional barcode symbologies were compared based on different criteria, such as coding capacity, compression efficiency, and error detection ability. The quick response (QR) code was found to have the largest coding capacity and relatively high compression ratio. To facilitate the further usage of QR code-based DNA barcodes, a web server was developed and is accessible at http://qrfordna.dnsalias.org. The web server allows users to retrieve the QR code for a species of interests, convert a DNA sequence to and from a QR code, and perform species identification based on local and global sequence similarities. In summary, the first comprehensive evaluation of various barcode symbologies has been carried out. The QR code has been found to be the most appropriate symbology for DNA barcode sequences. A web server has also been constructed to allow biologists to utilize QR codes in practical DNA barcoding applications

Toolbox model of evolution of metabolic pathways on networks of arbitrary topology

In prokaryotic genomes the number of transcriptional regulators is known to quadratically scale with the total number of protein-coding genes. Toolbox model was recently proposed to explain this scaling for metabolic enzymes and their regulators. According to its rules the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger "universal" network formed by the union of all species-specific networks. It remained to be understood, however, how the topological properties of this universal network influence the scaling law of functional content of genomes. In this study we answer this question by first analyzing the scaling properties of the toolbox model on arbitrary tree-like universal networks. We mathematically prove that the critical branching topology, in which the average number of upstream neighbors of a node is equal to one, is both necessary and sufficient for the quadratic scaling. Conversely, the toolbox model on trees with exponentially expanding, supercritical topology is characterized by the linear scaling with logarithmic corrections. We further generalize our model to include reactions with multiple substrates/products as well as branched or cyclic metabolic pathways. Unlike the original model the new version employs evolutionary optimized pathways with the smallest number of reactions necessary to achieve their metabolic tasks. Numerical simulations of this most realistic model on the universal network from the KEGG database again produced approximately quadratic scaling. Our results demonstrate why, in spite of their "small-world" topology, real-life metabolic networks are characterized by a broad distribution of pathway lengths and sizes of metabolic regulons in regulatory networks.Comment: 34 pages, 9 figures, 2 table

A gap between rational annuitization price for producer and price for customer

The paper studies pricing of insurance products focusing on the pricing of annuities under uncertainty. This pricing problem is crucial for financial decision making and was studied intensively; however, many open questions still remain. In particular, there is a so-called ``annuity puzzle" related to certain inconsistency of existing financial theory with the empirical observations for the annuities market. The paper suggests a pricing method based on the risk minimization such that both producer and customer seek to minimize the mean square hedging error accepted as a measure of risk. This leads to two different versions of the pricing problem: the selection of the annuity price given the rate of regular payments, and the selection of the rate of payments given the annuity price. It appears that solutions of these two problems are different. This can contribute to explanation for the "annuity puzzle"