bluuebunny/crossref_metadata_2025 huggingface dataset:
Tailoring Privacy-Aware Trustworthy Cooperating Smart Spaces for University Environments
Authors: Liampotis Nicolas , Papadopoulou Eliza , Kalatzis Nikos , Roussaki Ioanna G. , Kosmides Pavlos , Sykas Efstathios D. , Bental Diana , Taylor Nicholas Kenelm
Published: May 2019

The more information users disclose to pervasive systems or social media, the better quality and enhanced experience they enjoy for a wider variety of personalised services. However, the privacy concerns of individuals that use such systems have dramatically risen the last years, especially after several events of massive security breaches in various computing or communication systems that have reached the news. This chapter presents the approach being employed by the SOCIETIES project to protect the privacy of sensitive user data and ensure the trustworthiness of delivered services via social and pervasive computing systems. This framework has already been designed, implemented and evaluated via real user trials engaging wide and heterogeneous user populations. In addition to the respective requirements, architecture and features discussed herewith, this chapter elaborates on the user trial that has been conducted in university settings to validate this system focusing on the privacy and trust evaluation results obtained.
A New View of Privacy in Social Networks
Authors: Chang Wei , Wu Jie
Published: May 2019

Many smartphone-based applications need microdata, but publishing a microdata table may leak respondents' privacy. Conventional researches on privacy-preserving data publishing focus on providing identical privacy protection to all data requesters. Considering that, instead of trapping in a small coterie, information usually propagates from friend to friend. The authors study the privacy-preserving data publishing problem on a mobile social network. Along a propagation path, a series of tables will be locally created at each participant, and the tables' privacy-levels should be gradually enhanced. However, the tradeoff between these tables' overall utility and their individual privacy requirements are not trivial: any inappropriate sanitization operation under a lower privacy requirement may cause dramatic utility loss on the subsequent tables. For solving the problem, the authors propose an approximation algorithm by previewing the future privacy requirements. Extensive results show that this approach successfully increases the overall data utility, and meet the strengthening privacy requirements.
Hybrid Privacy Preservation Technique Using Neural Networks
Authors: VidyaBanu R. , Nagaveni N.
Published: May 2019

A novel Artificial Neural Network (ANN) dimension expansion-based framework that addresses the demand for privacy preservation of low dimensional data in clustering analysis is discussed. A hybrid approach that combines ANN with Linear Discriminant Analysis (LDA) is proposed to preserve the privacy of data in mining. This chapter describes a feasible technique for privacy preserving clustering with the objective of providing superior level of privacy protection without compromising the data utility and mining outcome. The suitability of these techniques for mining has been evaluated by performing clustering on transformed data and the performance of the proposed method is measured in terms of misclassification and privacy level percentage. The methods are further validated by comparing the results with traditional Geometrical Data Transformation Methods (GDTMs). The results arrived at are significant and promising.
Mobile Security in Low-Income Households' Businesses
Authors: Chummun Bibi Zaheenah
Published: May 2019

A wide range of technologies impinges on all disciplines including financial services in this era of the Fourth Industrial Revolution. The deployment and security of mobile phones have considerably increased financial services access such as mobile money to the low-income households in developing African markets recently. The financial services that were once randomly accessible to those financially excluded have now become a potential pathway to enhance financial inclusion in allowing the low-income households to transact through mobile financial services in a more speedy, reliable, and secure manner. However, many security challenges remain to be addressed to promote a more inclusive mobile financial system. This chapter focuses on mobile devices security landscape and unprecedented security breaches by cyber criminals and how those threats can be mitigated in a view to promote financial inclusion in the mobile financial services sector of emerging African markets in the midst of the Fourth Industrial Revolution.
Genetic Privacy
Authors: Supiot Elsa , Bernelin Margo
Published: May 2019

This chapter analyzes the European Union framing of the protection of genetic privacy in the context of the European Commission's 2012 proposal to amend the 95/46/EC Data Protection Directive. This market-driven proposal, fitting a wider European movement with regard to health-related legal framework, takes into account the challenges to privacy protection brought by rapid technological development. Although the proposal is an attempt to clarify the 1995 Data Protection Directive, including the question of genetic data, it also creates some controversial grey areas, especially concerning the extensive regulatory role to be played by the European Commission. With regard to genetic privacy, this chapter takes the opportunity to develop on this paradox, and gives an analysis of the European design on the matter.
Information Disclosure on Social Networking Sites
Authors: Doherty Clare , Lang Michael , Deane James , Connor Regina
Published: May 2019

This chapter explores how six constructs—control, trust, perceived risk, risk propensity, perceived legal protection, and privacy disposition—affect information disclosure on the Social Networking Site (SNS) Facebook. Building upon previous related work, an extended causal model of disclosure behaviour is proposed. The hypothesised relationships in this model were tested using survey data collected from 278 social networking site users in Ireland. The results of the analysis provide strong support for the proposed model.
Utilization Pattern and Privacy Issues in the Use of Health Records for Research Practice by Doctors
Authors: Omidoyin Eunice Olubunmi , Opeke Rosaline Oluremi , Osagbemi Gordon Kayode
Published: May 2019

Research is a fundamental activity in teaching hospitals, and medical doctors use information contained in health records for research. In this process, researchers are often confronted with privacy issues. It is however not clear the extent to which doctors paid attention to this privacy issues in their research. The purpose of this study was to establish the extent to which privacy principles were followed by medical doctors in federal teaching hospitals in Nigeria when using health records for research. Survey research design was adopted for this study with two-stage random sampling technique to select 60% of the federal teaching hospitals; and 60% of the medical doctors in the selected hospitals. Attention was paid to securing patients unused data; health records was used mostly to generate data to support application for grant. There was a joint positive significant relationship between the predictor variables (privacy and health records) and the criterion variable in research practice.
Students' Privacy Concerns on the Use of Social Media in Higher Education
Authors: Aymerich-Franch Laura , Fedele Maddalena
Published: May 2019

Social media is principally used by students in the private sphere. However, its implementation for educational purposes in higher education is rapidly expanding. This chapter looks into undergraduate students' perceptions of using social media in the university context. In particular, it examines students' privacy concerns regarding faculty use of social networks to support classroom work and video calling or online chats to meet for work discussion. Two-hundred-forty-four undergraduate students completed a survey and four focus groups were carried out. The results reveal that although students generally accept using social media in the instructional arena, privacy concerns can easily emerge. Educational institutions are encouraged to take these concerns seriously. Using applications specifically created for learning purposes and developing some guidelines for a correct implementation of these resources for the faculty to follow might contribute to alleviate these concerns.
Is It Privacy or Is It Access Control?
Authors: Osborn Sylvia L.
Published: May 2019

With the widespread use of online systems, there is an increasing focus on maintaining the privacy of individuals and information about them. This is often referred to as a need for privacy protection. The author briefly examines definitions of privacy in this context, roughly delineating between keeping facts private and statistical privacy that deals with what can be inferred from data sets. Many of the mechanisms used to implement what is commonly thought of as access control are the same ones used to protect privacy. This chapter explores when this is not the case and, in general, the interplay between privacy and access control on the one hand and, on the other hand, the separation of these models from mechanisms for their implementation.
Cloud Crime and Fraud
Authors: Singh Nimisha
Published: May 2019

Changing trends in IT industry are opening new avenues. With the scalability, flexibility, and economic advantage offered by cloud computing, more and more organizations are moving towards cloud for their applications. With all the benefits of cloud computing, it poses a danger of digital crime and security breaches. These challenges are compounded by the fact that cybercrime and the transgressors transcend geographical boundaries while the law enforcement does not. This paper tries to focus on how cloud computing is rising to the challenges thrown in from cyber space and recent developments to avoid and mitigate cloud fraud and abuse. Taking counter measures at organizational level, will alleviate and up to an extent eliminate security breaches. With current knowledge on policy and standards adopted by developed nations, the policy makers and law enforcement agencies in developing countries can work towards formulating standards and guidelines for awareness on threats, vulnerabilities and effectiveness of security controls to respond to risk.
Organizational Resilience Approaches to Cyber Security
Authors: Gould David
Published: May 2019

This article includes a perspective on cyber security through the lens of the World Economic Forum Resilience Framework. As cyber threats are a continual threat to organizations, it may be useful to consider resilience as a complementary approach to technological responses. The problem is that organizations cannot generate a sufficient number and types of responses to cyber security threats as the number of threats and associated costs continues to increase. The purpose of this article is to explore some possible practices and approaches to counter the ongoing and escalating cyber security threats, with the understanding and wisdom that not all threats will be possible to stop. Resilience is a complementary factor to directly countering threats by taking actions to backup information, having access to additional equipment as needed, by budgeting for failure, preparing for unexpected circumstances among other activities. Concepts from evolution and game theory are introduced within the resilience discussion.
Dimensions of Privacy Concerns Amongst Online Buyers in India
Authors: Jain Tinu , Mishra Prashant
Published: May 2019

Internet is quickly becoming the public electronic marketplace. Though the internet has revolutionized retail and direct marketing, the full scale incorporation and acceptance of the internet marketplace with the modern business is limited. One major inhibition shown by the internet buyers is in the form of lack of confidence in the newly developed marketing machinery/technology and concern related fear and distrust regarding loss of personal privacy due to easy access of personal information to the marketers. This concern about personal information and privacy varies with consumers especially with countries. It is also suggested that importance provided to various privacy dimensions would vary. The research investigates different dimensions and their interrelationship to identify factors affecting privacy concern among Net buyers in India.
Digital Paranoia
Authors: McNeal Ramona Sue , Schmeida Mary
Published: May 2019

Participation in social networks, forums, and other discussion groups is a growing trend in the United States. Aside from the benefits of online social media, there is a growing concern about privacy and safety from the devolvement of personal information online. As a result of this unfriendly social media climate, Americans are taking measures to protect personal identity and to avoid surveillance by others. The purpose of this chapter is to analyze factors predicting which groups are most concerned about Internet privacy. In addition, this chapter explores how concerns regarding Information privacy are impacting usage of social network sites. We explore these questions using multivariate regression analysis and individual level data from the Pew Internet and American Life Project. Our findings suggest that those with the greatest fears regarding online privacy are not staying offline but are taking necessary precautions to address concerns.
Cyber Security Crime and Punishment
Authors: Abu-Taieh Evon , Alfaries Auhood , Al-Otaibi Shaha , Aldehim Ghadah
Published: May 2019

Cyberspace and the existence of the internet allows different types of crimes to appear. Hence, there is a need for new laws to be set with a collective, comprehensive, view of crime and a global understanding. This article studies 5 different countries' laws pertaining to cybercrimes namely: Jordan, Oman, Kuwait, Qatar, and Saudi Arabia. These different countries issued different laws at different times, some in 2007 others are as new as 2015. The article looks at the laws from an academic definition of different crimes, and also describes the laws from a perspective of each country.
Security, Privacy, and Ownership Issues With the Use of Wearable Health Technologies
Authors: Kerr Don , Butler-Henderson Kerryn , Sahama Tony
Published: May 2019

When considering the use of mobile or wearable health technologies to collect health data, a majority of users state security and privacy of their data is a primary concern. With users being connected 24/7, there is a higher risk today of data theft or the misappropriate use of health data. Furthermore, data ownership is often a misunderstood topic in wearable technology, with many users unaware who owns the data collected by a device, what that data can be used for and who can receive that data. Many countries are reviewing privacy governance in an attempt to clarify data privacy and ownership. But is it too late? This chapter explores the concepts of security and privacy of data from mobile and wearable technology, with specific examples, and the implications for the future.
The Future of National and International Security on the Internet
Authors: Dawson Maurice , Omar Marwan , Abramson Jonathan , Bessette Dustin
Published: May 2019

Hyperconnectivity is a growing trend that is driving cyber security experts to develop new security architectures for multiple platforms such as mobile devices, laptops, and even wearable displays. The futures of national and international security rely on complex countermeasures to ensure that a proper security posture is maintained during this state of hyperconnectivity. To protect these systems from exploitation of vulnerabilities it is essential to understand current and future threats to include the laws that drive their need to be secured. Examined within this chapter are the potential security-related threats with the use of social media, mobile devices, virtual worlds, augmented reality, and mixed reality. Further reviewed are some examples of the complex attacks that could interrupt human-robot interaction, children-computer interaction, mobile computing, social networks, and human-centered issues in security design.
Cloud Computing and Cybersecurity Issues Facing Local Enterprises
Authors: Erturk Emre
Published: May 2019

This chapter sets out to explore new trends in cyber and cloud security, and their implications for businesses. First, the terminology and assumptions related to cloud computing are stated. Next, the chapter reports on contemporary research around the awareness of security issues, and the security processes within the cloud computing realm. Cyber security poses a different challenge to local small and medium sized organizations, which may seem to have less at stake financially. However, they are more vulnerable, due to fewer resources dedicated toward prevention. A series of serious security incidents may even keep them out of business. Furthermore, security needs to be understood and handled differently in a cloud based environment. Therefore, the chapter identifies unique security practices and recommendations for these businesses to run their IT resources safely in the cloud.
Cyberbullying, Sexting, and Online Sharing
Authors: Nguyên Thanh Trúc T. , Mark Lauren K.
Published: May 2019

Schools are pushing to implement more technology use to promote student learning. Yet, adults may not be completely aware of the non-academic online activities students engage in, like cyberbullying, sexting, and online sharing. In this study, parents (N = 663) and educators (N = 548) from four US states were surveyed on their understanding and awareness of their children's/students' online activities. Adult awareness levels and perspectives were compared. Parents and educators were found to be similarly supportive of computer use adding value to student education, but significantly differed in their trust levels of students' computer usage, preparedness to talk to students about Internet safety issues, and comfort regarding students using online social media. Additionally, parents and educators differed significantly in their understanding of how sharing of explicit material occurs online.
Growing From Childhood Into Adolescence
Authors: Yan Zheng , Zheng Robert Z.
Published: May 2019

In this theoretical review paper, the authors discuss five important issues about the science of cyber behavior as a field of scientific research. First, they argue that the science of cyber behavior as a field of research is entering its adolescence after growing from its childhood, but before spearheading into its adulthood. The paper reviews the current understanding of human behavior in general and state that behavior sciences have generated extensive knowledge about human behavior theoretically, empirically, and methodologically across multiple disciplines. Next, the authors focus on cyber communication as an example to illustrate current knowledge about various types of cyber behaviors. They showcase exemplary research programs on cyber behavior in four disciplines of behavioral sciences, social psychology, cognitive psychology, communication studies, and sociology. Finally, the paper outlines future research programs in five major directions for further development of the field. Taking the opportunity to commemorate the inaugural issue of the International Journal of Cyber Behavior, Psychology and Learning, the authors attempt to draw the first sketch of the science of cyber behavior from the perspective of history of science.
“Hey, Look at My Body!”
Authors: Chan Lik Sam , Tsang Hing Weng Eric
Published: May 2019

This article considers the phenomenon of online body display by users of social networking sites in Hong Kong. A survey of 392 young adults was conducted to investigate the relationships between narcissism, grandiose exhibitionism, body image satisfaction, perceived privacy risks, and online body display. A Body Display Index was developed to measure the perceived level of sexual explicitness of photographs shared by Facebook users. Grandiose exhibitionism, a sub-trait of narcissism, was found to be a stronger predictor of online body display than narcissism. The relationship between body image satisfaction and online body display was not significant, and no relationship was found between such displays and perceived privacy risks, thus implying a lack of social media-related privacy concerns among the respondents.
Social Contributors and Consequences of Habitual and Compulsive Game Play
Authors: Wohn Donghee Yvette , Lee Yu-Hao , Ozkaya Elif Yilmaz
Published: May 2019

This study examines the relationship between social motivations, pro-social relationship outcomes, and two types of game play—habitual and compulsive—in the context of simulation games on Facebook. Social motivations were significantly associated with compulsive game play, but not habitual game play. Compulsive play was a positive predictor of pro-social outcomes whereas habitual use was not. By differentiating two different types of media use that are both associated with problematic use, the authors see that social factors contribute to people's inability to control their gaming behavior, but that the so-called “addictive” behavior can also yield positive relationship outcomes.
Loneliness and Internet Addiction Among University Students
Authors: Boylu Ayfer Aydiner , Günay Gülay
Published: May 2019

The present study was designed to determine the relationship between loneliness and Internet addiction, based on a sample of young generation from Turkey. Participants in this study were students of the Hacettepe University in Ankara, Turkey (n = 440). Findings show that there is a statistically significant relationship (p <0.05) between students' Internet addiction and only the grade they are studying. According to the correlation analysis, it was found that there is a negative relationship between the loneliness of students and the time they spend on the internet, and a positive relationship between internet addiction and age of students. Moreover, it was found that the age, time spent on the Internet and loneliness of university students were important determinants of Internet addiction.
The Changing Face of Electronic Aggression
Authors: Virkar Shefali
Published: May 2019

Over the last two decades, public confidence and trust in Government has declined visibly in several liberal democracies, giving way instead to disillusionment with current political institutions, actors, and practices; rendering obsolete or inappropriate much of traditional democratic politics. Simultaneously, digital technologies have created huge opportunities for public bodies and agencies. In analysing the No. 10 Downing Street ePetitions Initiative based in the United Kingdom, this chapter engages with issues related to the innovative use of digital network technology by Government to involve citizens in policy processes and to buffer national security within existing democratic frameworks. The work examines whether the application of new digital platforms to participatory democracy in the Government 2.0 era leads eventually to radical transformations in government functioning and the body politic, or merely to modest, unspectacular political reform and to the emergence of technology-based obsessive-compulsive pathologies and trolling behaviours amongst individuals in society.
I'm Always Online
Authors: Brkljačić Tihana , Majetić Filip , Wertag Anja
Published: May 2019

Internet use has become an integral part of our lives. It provides a lot of benefits; however, excessive use can have serious consequences for one's well-being. Therefore, the aim of this chapter is to explore well-being of heavy Internet users. Empirical research was conducted on 500 students of engineering, who were divided into groups based on the total time per day reported spending in various online activities. The comparison of subjective well-being and sources of life satisfaction and dissatisfaction showed that heavy Internet users were less happy compared to light users. Heavy Internet users found more satisfaction in various entertainment activities, while light users found more satisfaction in love life and family. Findings of this research provide some important theoretical findings, but also point out that the continuing research is needed to further explore the relation between Internet addiction, time spent online, and well-being.
Treatment of Internet Addiction
Authors: Shen Libi
Published: May 2019

The birth of the Internet in 1969 has changed people's lives immensely in the past 48 years. Over the years, this invention has brought people connection, information, communication, business, entertainment, and so forth; however, researchers have found the impact of the Internet's byproduct, namely Internet addiction, in the past two decades as well. It was argued that Internet addiction might be detrimental to people's mental and physical health. The problem is that Internet addiction is not clearly defined, nor has it been included in Diagnostic and Statistical Manual for Mental Disorders (DSM-5) by American Psychiatric Association. If the definition is not clear and the symptoms are varied, the treatment for Internet addiction would become an issue. In this chapter, the researcher will focus on different approaches to the treatment of Internet addiction based on research after reviewing the definitions, theories, causes, consequences, and symptoms of Internet addiction.
Bioinformatics Database Resources
Authors: Khandelwal Icxa , Sharma Aditi , Agrawal Pavan Kumar , Shrivastava Rahul
Published: May 2019

Various biological databases are available online, which are classified based on various criteria for ease of access and use. All such bioinformatics database resources have been discussed in brief in this book chapter. The major focus is on most commonly used biological/bioinformatics databases. The authors provide an overview of the information provided and analysis done by each database, information retrieval system and formats available, along with utility of the database to its users. Most widely used databases have been covered in detail so as to enhance readers' understanding. This chapter will serve as a guide to those who are new to the field of bioinformatics database resources, or wish to have consolidated information on various bioinformatics databases available.
Subspace Clustering of DNA Microarray Data
Authors: Tchagang Alain B. , Famili Fazel , Pan Youlian
Published: May 2019

Identification of biological significant subspace clusters (biclusters and triclusters) of genes from microarray experimental data is a very daunting task that emerged, especially with the development of high throughput technologies. Several methods and applications of subspace clustering (biclustering and triclustering) in DNA microarray data analysis have been developed in recent years. Various computational and evaluation methods based on diverse principles were introduced to identify new similarities among genes. This review discusses and compares these methods, highlights their mathematical principles, and provides insight into the applications to solve biological problems.
Cloud-Based Computing Architectures for Solving Hot Issues in Structural Bioinformatics
Authors: Mrozek Dariusz
Published: May 2019

Bioinformatics as a scientific domain develops tools that enable understanding the wealth of information hidden in huge volumes of biological data. However, there are several problems in bioinformatics that, although already solved or at least equipped with promising algorithms, still require huge computing power in order to be completed in a reasonable time. Cloud computing responds to these demands. This chapter shows several cloud-based computing architectures for solving hot issues in structural bioinformatics, such as protein structure similarity searching or 3D protein structure prediction. Presented architectures have been implemented in Microsoft Azure public cloud and tested in several projects developed by Cloud4Proteins research group.
Enzyme Function Classification
Authors: Sharif Mahir M. , Tharwat Alaa , Hassanien Aboul Ella , Hefny Hesham A.
Published: May 2019

Enzymes are important in our life and it plays a vital role in the most biological processes in the living organisms and such as metabolic pathways. The classification of enzyme functionality from a sequence, structure data or the extracted features remains a challenging task. Traditional experiments consume more time, efforts, and cost. On the other hand, an automated classification of the enzymes saves efforts, money and time. The aim of this chapter is to cover and reviews the different approaches, which developed and conducted to classify and predict the functions of the enzyme proteins in addition to the new trends and challenges that could be considered now and in the future. The chapter addresses the main three approaches which are used in the classification the function of enzymatic proteins and illustrated the mechanism, pros, cons, and examples for each one.
Intelligent Biomedical Engineering Operations by Cloud Computing Technologies
Authors: Armutlu Hasan
Published: May 2019

Cloud computing is an effective way of using hardware- and software-oriented resources at optimum levels. Thanks to this technology, it is possible to share large amounts of resources effectively and accurately among target users. Because it is a rapidly growing technology, one cannot deny that it has remarkable relations with alternative research fields having great potential and application scope. It is clear that artificial intelligence is one of these fields. As associated with both these research fields, the purpose of this chapter is to examine artificial-intelligence-based biomedical engineering works supported/connected with cloud computing. Because it has a vital importance with applications regarding the medical/health problems, biomedical engineering needs support from the most recent technologies and research fields in this manner. So, the chapter provides a view over the intersection of these three research fields as trying to improve awareness among interested readers.
Applications of Supercomputers in Population Genetics
Authors: Dumancas Gerard G.
Published: May 2019

Population genetics is the study of the frequency and interaction of alleles and genes in population and how this allele frequency distribution changes over time as a result of evolutionary processes such as natural selection, genetic drift, and mutation. This field has become essential in the foundation of modern evolutionary synthesis. Traditionally regarded as a highly mathematical discipline, its modern approach comprises more than the theoretical, lab, and fieldwork. Supercomputers play a critical role in the success of this field and are discussed in this chapter.
Sensor Based Smart Real Time Monitoring of Patients Conditions Using Wireless Protocol
Authors: R. Jegan , S. Nimi W.
Published: May 2019

This article describes how physiological signal monitoring plays an important role in identifying the health condition of heart. In recent years, online monitoring and processing of biomedical signals play a major role in accurate clinical diagnosis. Therefore, there is a requirement for the developing of online monitoring systems that will be helpful for physicians to avoid mistakes. This article focuses on the method for real time acquisition of an ECG and PPG signal and it's processing and monitoring for tele-health applications. This article also presents the real time peak detection of ECG and PPG for vital parameters measurement. The implementation and design of the proposed wireless monitoring system can be done using a graphical programming environment that utilizes less power and a minimized area with reasonable speed. The advantages of the proposed work are very simple, low cost, easy integration with programming environment and continuous monitoring of physiological signals.
Informatics and Data Analytics to Support Exposome-Based Discovery
Authors: Sarigiannis Dimosthenis A. , Gotti Alberto , Handakas Evangelos , Karakitsios Spyros P.
Published: May 2019

This chapter aims at outlining the current state of science in the field of computational exposure biology and in particular at demonstrating how the bioinformatics techniques and algorithms can be used to support the association between environmental exposures and human health and the deciphering of the molecular and metabolic pathways of induced toxicity related to environmental chemical stressors. Examples of the integrated bioinformatics analyses outlined herein are given concerning exposure to airborne chemical mixtures, to organic compounds frequently found in consumer goods, and to mixtures of organic chemicals and metals through multiple exposure pathways. Advanced bioinformatics are coupled with big data analytics to perform studies of exposome-wide associations with putative adverse health outcomes. In conclusion, the chapter gives the reader an outline of the available computational tools and paves the way towards the development of future comprehensive applications that are expected to support efficiently exposome research in the 21st century.
Protein Docking and Drug Design
Authors: Gangopadhyay Aditi , Chakraborty Hirak Jyoti , Datta Abhijit
Published: May 2019

Protein docking is integral to structure-based drug design and molecular biology. The recent surge of big data in biology, the demand for personalised medicines, evolving pathogens and increasing lifestyle-associated risks, asks for smart, robust, low-cost and high-throughput drug design. Computer-aided drug design techniques allow rapid screening of ultra-large chemical libraries within minutes. This is immensely necessary to the drug discovery pipeline, which is presently burdened with high attrition rates, failures, huge capital and time investment. With increasing drug resistance and difficult druggable targets, there is a growing need for novel drug scaffolds which is partly satisfied by fragment based drug design and de novo methods. The chapter discusses various aspects of protein docking and emphasises on its application in drug design.
Identification of Candidate Genes Responsible for Age-Related Macular Degeneration Using Microarray Data
Authors: Hao Yuhan , Weiss Gary M. , Brown Stuart M
Published: May 2019

A DNA microarray can measure the expression of thousands of genes simultaneously, and this enables us to study the molecular pathways underlying Age-related Macular Degeneration. Previous studies have not determined which genes are responsible for the process of AMD. The authors address this deficiency by applying modern data mining and machine learning feature selection algorithms to the AMD microarray dataset. In this paper four methods are utilized to perform feature selection: Naïve Bayes, Random Forest, Random Lasso, and Ensemble Feature Selection. Functional Annotation of 20 final selected genes suggests that most of them are responsible for signal transduction in an individual cell or between cells. The top seven genes, five protein-coding genes and two non-coding RNAs, are explored from their signaling pathways, functional interactions and associations with retinal pigment epithelium cells. The authors conclude that Pten/PI3K/Akt pathway, NF-kappaB pathway, JNK cascade, Non-canonical Wnt Pathway, and two biological processes of cilia are likely to play important roles in AMD pathogenesis.
De Novo Motif Prediction Using the Fireworks Algorithm
Authors: Lihu Andrei , Holban Ștefan
Published: May 2019

De novo motif discovery is essential in understanding the cis-regulatory processes that play a role in gene expression. Finding unknown patterns of unknown lengths in massive amounts of data has long been a major challenge in computational biology. Because algorithms for motif prediction have always suffered of low performance issues, there is a constant effort to find better techniques. Evolutionary methods, including swarm intelligence algorithms, have been applied with limited success for motif prediction. However, recently developed methods, such as the Fireworks Algorithm (FWA) which simulates the explosion process of fireworks, may show better prospects. This paper describes a motif finding algorithm based on FWA that maximizes the Kullback-Leibler divergence between candidate solutions and the background noise. Following the terminology of FWA's framework, the candidate motifs are fireworks that generate additional sparks (i.e. derived motifs) in their neighborhood. During the iterations, better sparks can replace the fireworks, as the Fireworks Motif Finder (FW-MF) assumes a one occurrence per sequence mode. The results obtained on a standard benchmark for promoter analysis show that our proof of concept is promising.
CytoNet, a Versatile Web-Based System for Accessing Advisory Cytology Services
Authors: Perroti Rallou , Pouliakis Abraham , Margari Niki , Panopoulou Eleni , Karakitsou Efrossyni , Iliopoulou Dimitra , Panayiotides Ioannis , Koutsouris Dimitrios Dionysios
Published: May 2019

This article describes how the use of artificial intelligence applications as a consultation tool on a cytological laboratory's daily routine has been suggested for several decades. In addition to the use of high-resolution thyroid ultrasonography and fine-needle aspiration cytology, a further reduction of the number of unnecessary thyroidectomies can be achieved through the access to such techniques. Despite the evident advantages, artificial intelligence applications hardly ever find their way to end-users due to the specialized knowledge necessary for designing and using them, as well as the users' unfamiliarity with the required technology. The authors aimed to design an easy-to-use online platform (CytoNet) that gives access to a learning vector quantizer neural network (LVQ NN) that discriminates benign from malignant thyroid lesions to users (medical doctors) with no specialized technical background on artificial intelligence.
A Web Database IR-PDB for Sequence Repeats of Proteins in the Protein Data Bank
Authors: Samuel Selvaraj , Rajathei Mary
Published: May 2019

Amino acid repeats play significant roles in the evolution of structure and function of many large proteins. Analysis of internal repeats of protein with known structure helps to understand the importance of repeats of the protein. A database IR-PDB for repeats in sequence of the proteins in the PDB has been developed for the analysis of impact of repeats in proteins. Using the state of the art repeat detection method RADAR, internal repeats in 148202 sequences out of 285714 sequences belonging to 115031 PDB structures were detected. The identified sequence repeats were annotated with secondary structural information with a view to analyze the structural consequence and conservation of the repeats. The tertiary structure of the repeats and their functional involvements can be found out through web links to PDB, PDBsum and Pfam. IR-PDB is systematically annotated for the proteins in the PDB with sequence repeats and their structure with the possibility to access the dataset interactively through web services.
Opportunities and Challenges in Socially Inclusive Innovation
Authors: Peñalba Linda M. , Elazegui Dulce D.
Published: May 2019

This chapter analyzes the opportunities and challenges for modern biotechnology, particularly Genetically Modified (GM) corn, in addressing social inclusion to ensure its equitable outcomes or impacts. It examines the policy environment in which GM corn was introduced and the related socioeconomic concerns. The study reveals that in the Philippines there is no institutionalized mechanism yet to determine if GM corn promotion policies and strategies conform to the social inclusion context of biotechnology. Governance of the GM technology and the interplay of the innovation system intermediaries hindered the full realization and application of social inclusion principles. Interventions to monitor socio-economic impact, knowledge transfer and interaction, and credit support delivery are needed for a more socially inclusive innovation. There should be a continuous interactive learning among various stakeholders to have evidence-based information on the technology.
Genetically Engineered Microorganisms for Bioremediation Processes
Authors: Benjamin Stephen Rathinaraj , de Lima Fabio , Rathoure Ashok K.
Published: May 2019

In the past few decades, environmental pollution is a major issue which affects biodiversity public health and eco systems present in worldwide, nowadays, microbial potential are connected to effect the clean-up of environmental pollutants. Conventional methods are focus on the separation, rather than the destruction of contaminants, the use of genetically engineered microorganisms for bioremediation would be an alternative, environmentally friendly, more effectiveness and economical clean-up technique for the remediation of pollutants in present in contaminated sites. A combined strategies relationship between genetic engineered microbes and bioremediation can enhance the effectiveness of contaminants sites. Here, we have elaborated recent work on the investigation and improvement of these microbes using genetic tools and given an outlook of what may be possible in the near future.
Information Needs and Assessment of Bioinformatics Students at the University of Swaziland
Authors: Sorokhaibam Satyabati Devi , Mathabela Ntombikayise Nomsa
Published: May 2019

A survey was carried out of the information landscape within the students of Computer Science, Biology and Mathematics in the University of Swaziland which examined the research problems, important sources of information, the methods of access, information needs and seeking behavior of the users their assessment and the role of the Libraries since Librarian have to identify the information needs, uses and problems faced to meet the needs and requirement of the user. A total of 200 questionnaire were distributed. The survey indicated that majority of the students believe that the online resources play a very important role for their research and show positive attitude toward future bioinformatics usage and training. The study concluded that the training preferences of students need to be further explored.
Bacterial Remediation of Phenolic Compounds
Authors: Krishnaswamy Veena Gayathri
Published: May 2019

Environmental pollution has been an irrefutable fact of life for many centuries; but it has become a real problem, since the start of the industrial revolution. Discharge of these toxic compounds without treatment results in serious health risks to humans and the marine ecosystem. Several physical, chemical and biological methods have been employed for the remediation of the phenolics. Bioremediation is identified as the most efficient, cost effective and eco-friendly ways for treatment of phenolic compounds. This article is a comprehensive review on the sources of phenolic compounds, their hazards, and their fate once released into the environment; the treatment technologies employed and bioremediation of these compounds using both non-extremophlic and extremophilic organisms. The review, throws light on the enzymes involved in the remediation of phenolic compounds, highlights the importance of extremophilic organisms and biological treatment of phenol containing industrial wastewaters. Such comprehensive information on the research work performed for the remediation of phenolic compounds provide ways to explore the role played by micro organisms in the remediation of phenolic compounds, which could be applied in the remediation of phenol /contaminated sites even under extreme conditions.
Cancer Pathway Network Analysis Using Cellular Automata
Authors: Mahata Kalyan , Sarkar Anasua
Published: May 2019

Identification of cancer pathways is the central goal in the cancer gene expression data analysis. Data mining refers to the process analyzing huge data in order to find useful pattern. Data classification is the process of identifying common properties among a set of objects and grouping them into different classes. A cellular automaton is a discrete, dynamical system with simple uniformly interconnected cells. Cellular automata are used in data mining for reasons such as all decisions are made locally depend on the state of the cell and the states of neighboring cells. A high-speed, low-cost pattern-classifier, built around a sparse network referred to as cellular automata (ca) is implemented. Lif-stimulated gene regulatory network involved in breast cancer has been simulated using cellular automata to obtain biomarker genes. Our model outputs the desired genes among inputs with highest priority, which are analysed for their functional involvement in relevant oncological functional enrichment analysis. This approach is a novel one to discover cancer biomarkers in cellular spaces.
Bioremediation of Oil Contaminated Soil and Water
Authors: Nanayakkara Chandrika Malkanthi , Witharana Ayoma
Published: May 2019

Pollution from petroleum, plant and animal origin oils, which are released via oil production and shipping operations, refineries, accidental spills, effluents of different industries such as hotels, restaurants, food processing, etc. is ubiquitous in the environment. This necessitates the need for cost effective and efficient remediation technologies. Dealing with the problem chemically and physically is known to generate secondary pollutants and incurs high cost. Expediting natural attenuation via stimulating pollutant degradation activity of residential microbial community and/or introducing competent microflora in to polluted sites has been identified as the most successful and cost effective technology and is termed bioremediation. Phytoremediation, an emerging branch of bioremediation, has also been recognized as a promising treatment technology. Chapter examines the extent of work carried out in in situ and ex situ bioremediation strategies to mitigate oil pollution, the validity of such practices in terms of efficiency of the process and the future research directives.
Einstein–Maxwell Equations on Four-dimensional Lie Algebras
Authors: Koca Caner , Lejmi Mehdi
Published: May 2019

We classify up to automorphisms all left-invariant non-Einstein solutions to the Einstein–Maxwell equations on four-dimensional Lie algebras.