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Co-evolution exists ubiquitously in biological systems. At the molecular level, interacting proteins, such as ligands and their receptors and components in protein complexes, co-evolve to maintain their structural and functional interactions. Many proteins contain multiple functional domains interacting with different partners, making co-evolution of interacting domains occur more prominently. Multiple...
Identifying the interactions between proteins and Long non-coding RNAs (lncRNAs) can provide valuable clues for understanding the mechanisms and physiological functions of lncRNAs. In this work, we propose a computational method, PLIPCOM, which can accurately detect protein-lncRNA interactions by integrating two groups of network features. Low dimensional diffusion characteristics and HeteSim features...
Possible drug side-effects (SEs) are usually verified by many years of repeated clinical trials. Despite the effort, some drugs are still expected to cause adverse reactions in some patients. To better predict drug SEs without having to go through the laborious processes of testing and re-testing, machine learning (ML) techniques are more and more used to uncovered patterns in drug data for such purpose...
Gastric cancer (GC) is one of the lethal cancer types as well as one of the heterogeneous cancer types. To elucidate GC molecular mechanisms, mutational co-occurrence analyses have been suggested. However, an association between mutational co-occurrences and known GC signaling contexts has yet to be identified. In this study, the known GC signaling contexts including cancer hallmarks (DNA repair,...
Parkinson's disease is a debilitating and chronic disease of the nervous system. Traditional Chinese Medicine (TCM) is a new way for diagnosing Parkinson, and the data of Chinese Medicine for diagnosing Parkinson is a multi-label data set. Considering that the symptoms as the labels in Parkinson data set always have correlations with each other, we can facilitate the multi-label learning process by...
Big data analysis has been pervasively adopted as a method to analyze the tremendous amount of daily generated high throughput data in an efficient and accurate manner. Among the series of tools available in the field of big biomedical data, correlation networks are one of the most powerful tools for modelling gene expression, which is important in the study of disease and ageing. With the help of...
The recent rise in the use of social networks has resulted in an abundance of information on different aspects of everyday social activities that is available online. In the process of analysis of identifying the information originating from social networks, and especially Twitter, an important aspect is that of the geographic coordinates, i.e., geolocalisation, of the relevant information. Geolocalized...
As average life expectancy continuously rises, assisting the elderly population with living independently is of great importance. Detecting abnormal behaviour of the elderly living at home is one way to assist the eldercare systems with the increase of the elderly population. In this study, we perform an initial investigation to identify abnormal behaviour of household residents using energy consumption...
Social media serves as a unified platform for users to express their thoughts on subjects ranging from their daily lives to their opinion on consumer brands and products. These users wield an enormous influence in shaping the opinions of other consumers and influence brand perception, brand loyalty and brand advocacy. In this paper, we analyze the opinion of 19M Twitter users towards 62 popular industries,...
Gene (microRNA) identification is a key step in understanding the cellular mechanisms. Compared with biological experiments, computational prediction of disease genes is cheaper and more effortless. In this study, we analyzed the properties of tumor-associated microRNA in mouse and found that tumor-associated genes display 8distinguishingfeatures when compared with genes not yet known to be involved...
In this paper, we study relations ranking and object classification for multi-relational data where objects are interconnected by multiple relations. The relations among objects should be exploited for achieving a good classification. While most existing approaches exploit either by directly counting the number of connections among objects or by learning the weight of each relation from labeled data...
Wind speed prediction has been used in various fields such as Satellite launch, Air traffic control, Weather forecasting etc. Wind speed can be calculated by various atmospheric variables such as temperature, humidity, pressure, wind direction, etc. A number of methods have been proposed by various researchers to predict the wind speed. During the last few years a lot of research has been carried...
We consider an infrastructure of networked systems with discrete components that can be reinforced at certain costs to guard against attacks. The communications network plays a critical, asymmetric role of providing the vital connectivity between the systems. We characterize the correlations within this infrastructure at two levels using (a) aggregate failure correlation function that specifies the...
Goal. To create a mathematical tool for assessing the quality of a complex system likely availability (or failure) in the presence of interrelation in the components operation. The tool is different from the Markov's chain and other analogs. Tasks. To introduce a binomial distribution as the sum of the probabilities of ordered subsets of the numbers of successful tests. Introduction to probability...
Recently, it has been shown that lexicographic orderings and time travel can be used to automate the play of Nintendo Entertainment System (NES) games. In this work, we present a method for optimizing solutions to NES games. Since many of these classic Nintendo games are NP-hard, we propose a metaheuristic algorithm that works by borrowing operators from evolutionary algorithms. By using a search...
We describe a “crowd measurement” project, referred to as PoQeMoN, whose main objective is to identify Quality of Service (QoS) indicators in order to predict the Quality of Experience (QoE) for HTTP YouTube content on mobile networks. Results are based on experiments on an operational network. The second contribution of this paper is to show that the proposed indicator is easy to implement in order...
Medical imaging is an important area in today's healthcare system. Diagnosis using medical images relies heavily on a clinician's ability and experience. However this reliance can offer a room for diagnosis inaccuracies when clinicians are faced with long hours and heavy workload. Therefore the role of Computer Aided Diagnosis (CADx) systems to aid clinicians to make faster and more accurate decisions...
Ballistocardiogram (BCG) has been revisited in the last years as an unobtrusive method to detect heart beats. New electromechanical film (EMFi) sensors are now able to detect minimal oscillations in its surface, allowing to detect the mechanical action of the heart as it beats. This has allowed to develop unobtrusive systems for heart rate monitoring to be used as Point-of-Care devices, and to deploy...
Visual tracking is a very challenging problem in computer vision as the performance of a tracking algorithm may be degraded due to many challenging issues in the scenes, such as illumination change, deformation, and background clutter. So far no algorithms can handle all these challenging issues. Recently, it has been shown that correlation filters can be implemented efficiently and, with suitable...
This paper describes an objective and subjective evaluation models of pencil still drawings for art education. In the subjective evaluation, the evaluation word is summarized. This is a point of view when an art educator evaluates a pencil still drawing. The objective evaluation model consists of factor Fi, which comprises the features value of a basic pencil still drawing. Fi is also defined by considering...
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