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Soybean tissue-specific network helps identify and visualize the gene-gene relationships in various tissues [1]. We have built SoyTSN, a web-based tool for tissue-specific network prediction in soybean using 14 tissues RNA-Seq datasets including flower, root, nodule, leaf, stem, seed, etc. SoyTSN first combines multiple tissue specific RNA-Seq studies, and later Cross-Conditions Cluster Detection...
A central goal of systems biology is to uncover the underlying functional architecture of the cell and study its mechanisms. To this end, large amounts of omics data are being rapidly generated, and a focus of bioinformatics research has been towards integrating these data to identify active pathways or modules under certain conditions. Many bioinformatics algorithms include optimization methods,...
In eukaryotes, protein ubiquitylation is an important type of post-translation modification, in which the ubiquitin conjugates to a substrate protein. To have a better insight of the mechanisms underlying ubiquitylation, a key step is to identify protein ubiquitylation sites. Many existing computational methods are based on feature engineering, which may lead to biased and incomplete features. Deep...
Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. Existing computational methods for predicting amidation sites are based on feature extraction, which may result in incomplete or biased features...
With the advent of next-generation sequencing technologies, a considerable effort has been put into sequencing the epigenomes of different species. The efforts such as “Encode” and “Roadmap” epigenomics projects provide an opportunity to compare epigenomes across species (especially between human and mouse). This study is an effort to understand how different histone modifications vary/co-appear between...
Prioritizing genes according to their association with a disease allows researchers to explore genes in more informed ways. Although some useful algorithms have been developed, they are based on single gene importance, gene interaction networks, or gene modules with little consideration of relative gene importance in the context of modules. In this paper, we propose to prioritize genes considering...
Ubiquitination, as a post-translational modification, is a crucial biological process presented in cell signaling, death and localization. Identification of ubiquitination protein is of fundamental importance for understanding molecular mechanisms in biological systems and diseases. Although high-throughput experimental studies using mass spectrometry have identified many ubiquitination proteins and...
The goal of complex event detection is to automatically detect whether an event of interest happens in temporally untrimmed long videos which usually consist of multiple video shots. Observing some video shots in positive (resp. negative) videos are irrelevant (resp. relevant) to the given event class, we formulate this task as a multi-instance learning (MIL) problem by taking each video as a bag...
A mutual coupling theory is used to analyze the frequency splitting phenomena in magnetic resonance wireless power transfer (WPT) systems, along with a derivation of the critical coupling point (maximum operating distance at which maximum power-transfer efficiency is still achievable). Theoretical analysis and simulation results show the clearly visible frequency splitting phenomena, and reveal that...
This paper presents a self-tuning proportional-integral-derivative (PID) leader-follower control method of autonomous robots. Simulation result demonstrates the effectiveness and merit of the proposed methods.
Oil and gas pipelines are likely to be damaged due to various reasons such as external force, corrosion, and pipeline material in the process of operation. The pipeline accident will cause serious economic loss and environmental pollution. Therefore, it is significant to assess the risk of oil and gas pipeline. Considering the difficulty of fully perceiving and quantifying all risk information of...
Object segmentation in weakly labelled videos is an interesting yet challenging task, which aims at learning to perform category-specific video object segmentation by only using video-level tags. Existing works in this research area might still have some limitations, e.g., lack of effective DNN-based learning frameworks, under-exploring the context information, and requiring to leverage the unstable...
With rapid development of medical information, more and more attention has been paid to the intelligent diagnosis based on electronic medical records. The results of intelligent diagnosis can provide doctors with advice in the course of diagnosis and treatment, and avoid unnecessary mistakes. In the field of intelligent text aided diagnosis, how to extract and express a large amount of text information...
There are numerous potential applications for the Internet of Things (IOT) at the present stage. In the topic of image processing, the gender recognition usually adopts face information to identify the gender of a person. Therefore, if the input image loses face information, it will result in the wrong identification result. In this paper, we proposed a multiple-attributes (MA) recognition method...
This paper investigates the potential resonance of the MMC-MTDC system excited by ac background harmonics. First, the impact of ac background harmonics on one MMC is explored by using phase-leg voltage analysis. Then, the frequency-impedance characteristics of the MMC-MTDC system is explored to illustrate the reason why the dc network resonance occurs. Finally appropriate selection of the smoothing...
With the improvement of people's living standards, there is no doubt that people are paying more and more attention to their health. However, shortage of medical resources is a critical global problem. As a result, an intelligent prognostics system has a great potential to play important roles in computer aided diagnosis. Numerous papers reported that tongue features have been closely related to a...
For the traditional way of Liver disease diagnosis, there exists a certain subjectivity, and easily missed diagnosis and misdiagnosis. The use of a single neural network can not eliminate the redundant information among various indicators, resulting in diagnostic accuracy is not high. In order to improve the correctness of the early diagnosis of liver lesions, This paper proposes a liver disease diagnosis...
Recently, pathological diagnosis plays a crucial role in many areas of medicine, and some researchers have proposed many models and algorithms for improving classification accuracy by extracting excellent feature or modifying the classifier. They have also achieved excellent results on pathological diagnosis using tongue images. However, pixel values can't express intuitive features of tongue images...
Singular rough sets or S-rough sets, which have dynamic characteristics, are proposed by improving rough sets of Z. Pawlak. Two structures of S-rough sets: one direction singular rough sets and dual of one direction singular sets, are used to work out data dynamic mining which satisfies the attribute disjunction characteristics. Then the authors further work out the concepts of inner-data, outer-data...
In this paper, a customized electricity retailing plan recommendation strategy is developed. Cost-effective retailing plans are recommended according to customer's electricity usage pattern. Usage pattern is recognized through classifying daily load profile (DLP) into a certain class, which is obtained in DLP clustering process. Two DLP clustering skills, plan rank-oriented and load feature-oriented...
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