Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form basis biological mechanisms. Although large amount PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with methods cover only a fraction complete networks, further, identifying are both time-consuming expensive. Hence, it is urgent challenging to develop automated computational efficiently accurately predict...

Abstract Motivation: High-throughput protein interaction data, with ever-increasing volume, are becoming the foundation of many biological discoveries, and thus high-quality protein–protein (PPI) maps critical for a deeper understanding cellular processes. However, unreliability paucity current available PPI data key obstacles to subsequent quantitative studies. It is therefore highly desirable develop an approach deal these issues from computational perspective. Most previous works...

Proteins and their interactions lie at the heart of most underlying biological processes. Consequently, correct detection protein-protein (PPIs) is fundamental importance to understand molecular mechanisms in systems. Although convenience brought by high-throughput experiment technological advances makes it possible detect a large amount PPIs, data generated through these methods unreliable may not be completely inclusive all PPIs. Targeting this problem, study develops novel computational...

Abstract Background Protein-protein interactions (PPIs) play crucial roles in virtually every aspect of cellular function within an organism. Over the last decade, development novel high-throughput techniques has resulted enormous amounts data and provided valuable resources for studying protein interactions. However, these interaction are often associated with high false positive negative rates. It is therefore highly desirable to develop scalable methods identify errors from computational...

In recent years, wireless-based fingerprint positioning has attracted increasing research attention owing to its position-related features and applications in the Internet of Things (IoT). this paper, by leveraging long-term evolution (LTE) signals, a novel deep-learning-based approach is proposed solve problem outdoor positioning. Considering outstanding performance deep learning image classification, LTE signal measurements are converted into location grayscale images form database. order...

Protein-protein interactions (PPIs) are key components of most cellular processes, so identification PPIs is at the heart functional genomics. A number experimental techniques have been developed to discover PPI networks several organisms. However, accuracy and coverage these proven be limited. Therefore, it important develop computational methods assist in design validation studies for prediction interaction partners. Here, we provide a critical overview existing including genomic context...

Fingerprint-based positioning techniques are a hot research topic because of their satisfactory accuracy in complex environments. In this study, we adopted the deep-learning-based long-time-evolution (LTE) signal fingerprint method for outdoor environment positioning. Inspired by state-of-the-art image classification methods, novel hybrid location gray-scale utilizing LTE fingerprints is proposed paper. order to deal with fluctuations, several data enhancement methods adopted. A hierarchical...

Wi-Fi and magnetic field fingerprinting-based localization have gained increased attention owing to their satisfactory accuracy global availability. The common signal-based fingerprint deteriorates due well-known signal fluctuations. In this paper, we proposed a field-based system based on deep learning. Owing the low discernibility of strength (MFS) in large areas, unsupervised learning density peak clustering algorithm comparison distance (CDPC) is first used pick up several center points...

Due to the explosive development of location-based services (LBS), localization has attracted significant research attention over past decade. Among associated techniques, wireless fingerprint positioning garnered much interest due its compatibility with existing hardware. At present, widespread deployment long-term evolution (LTE) networks and uniqueness information fingerprints, based on LTE is mainstream method for outdoor positioning. However, in order improve accuracy, this needs...

In the complex and changeable war environment, how to intercept enemy's communication signals study source individual fingerprint identification obtain information of other party's equipment weapon system is an important basis for understanding enemy. Du e subtle differences in hardware between each device, there are characteristics that differ from devices. Fingerprint radiation source, by studying carried signal, can identify which coming from. Tracing equipment, provided determining...

For the goal of improving effectiveness and robustness identifying communicatioin radio individual under small sample prerequisite, we proposed a communication identification method based on stacked denoising auto-encoder, which can learn fingerprint feature from input unlabeled signal samples then extract low-dimension raio signals facing to high-dimension space. Finally, accurate phase will be accomplished in classifier. Experiments showed reliability three different data set.

Due to the small sample of communication station signals and weak fingerprint characteristics radio stations, accuracy individual identification stations is not high. This paper firstly proposes based on machine learning method, which can be used without training samples. Firstly, signal samples are subjected rectangular integral bispectral transformation, 1×L-dimensional bispectrum features extracted. Then these will sent clustering model finally classified into different groups. Compared...

Localization has attracted considerable attention in recent years because of the growth location-based services and computer-aided technology. In particular, wireless fingerprint-based positioning techniques have received due to their satisfactory performance with smartphones. this work, a two-level hierarchical structure system is proposed achieve accuracy. First, long-time-evolution (LTE) mobile networks are used provide information, collected measurements LTE signals converted into...