A5073711572- Machine Learning in Bioinformatics
- Advanced Image Processing Techniques
- Advanced Image and Video Retrieval Techniques
- Genomics and Phylogenetic Studies
- Advanced Vision and Imaging
- Image Processing Techniques and Applications
- RNA and protein synthesis mechanisms
- Image Retrieval and Classification Techniques
- Infrared Target Detection Methodologies
- Image and Signal Denoising Methods
- Multiple Myeloma Research and Treatments
- Advanced Image Fusion Techniques
- Image Enhancement Techniques
- Vehicle License Plate Recognition
- vaccines and immunoinformatics approaches
- Video Surveillance and Tracking Methods
- Advanced Sensor and Control Systems
- Handwritten Text Recognition Techniques
- RNA modifications and cancer
- Algorithms and Data Compression
- Advanced Measurement and Detection Methods
- Computational Drug Discovery Methods
- Advanced Decision-Making Techniques
- MicroRNA in disease regulation
- Artificial Intelligence in Healthcare
Xiamen University of Technology
2010-2025
Xi'an Technological University
2011-2025
China Medical University
2020-2021
Shangqiu Institute of Technology
2016
Xi'an University of Technology
2016
Hebei University of Technology
2012
Xiamen University
2009-2011
Hebei University of Engineering
2010
Dalian Jiaotong University
2010
Xihua University
2009
MicroRNAs constitute an important class of noncoding, single-stranded, ~22 nucleotide long RNA molecules encoded by endogenous genes. They play role in regulating gene transcription and the regulation normal development. can be associated with disease; however, only a few microRNA-disease associations have been confirmed traditional experimental approaches. We introduce two methods to predict association. The first method, KATZ, focuses on integrating social network analysis method machine...
Abstract Motivation 5-Methylcytosine (5mC), a fundamental element of DNA methylation in eukaryotes, plays vital role gene expression regulation, embryonic development, and other biological processes. Although several computational methods have been proposed for detecting the base modifications like 5mC sites from Nanopore sequencing data, they face challenges including sensitivity to noise, ignoring imbalanced distribution real-world scenarios. Results Here, we develop NanoCon, deep hybrid...
Visually sensitive regions in the scene are thought to be important for categorization. In this paper, we propose utilize visually information represented by deep features Specifically, context relationship between objects and surroundings is fully utilized as main basis judging content of scene, combining with convolution neural networks (CNNs), a categorization model based on constructed. First, saliency images marked according context-based detection algorithm. Then, original...
Protein-peptide interactions are essential to cellular processes and disease mechanisms. Identifying protein-peptide binding residues is critical for understanding peptide function advancing drug discovery. However, experimental methods costly time-intensive, while existing computational approaches often predict or separately, lack effective feature integration, rely heavily on limited high-quality structural data. To address these challenges, we propose UMPPI (Unveiling Multilevel...
This paper introduces a handwritten text detection model for examination papers, termed YOLO-Handwritten, which mitigates the limitations of current models, such as difficulties arising from varied writing styles, uneven handwriting forms, and disproportionate distributions positive negative samples. The YOLO-Handwritten integrates deformable convolution (DCNv3) enhanced aggregate feature fusion (iAFF) into Backbone network to establish improvement mechanism, based on attributes images in...
Neuropeptides are key signaling molecules that regulate fundamental physiological processes ranging from metabolism to cognitive function. However, accurate identification is a huge challenge due sequence heterogeneity, obscured functional motifs and limited experimentally validated data. Accurate of neuropeptides critical for advancing neurological disease therapeutics peptide-based drug design. Existing neuropeptide methods rely on manual features combined with traditional machine learning...
Outdoor images captured during sand–dust weather condition typically yield poor contrast and colour shift. A novel method for single restoration is introduced in this paper, which relies on the atmospheric scattering model information loss constraint. To compensate shift achieve proper luminance, proposed light changing with content of local scenes, initially estimated basis general grey-world assumption. Then, initial updated coarse transmission under Next, fast guide filter exploited...
In order to enhance the detection rate of multiple myeloma and execute an early more precise disease management, artificial intelligence assistant diagnosis system is developed.4,187 routine blood biochemical examination records were collected from Shengjing Hospital affiliated China Medical University January 2010 2020, which include 1,741 (MM) 2,446 non-myeloma (infectious diseases, rheumatic immune hepatic diseases renal diseases). The data set was split into training test subsets with...
MicroRNAs (miRNAs) comprise an important class of small single-stranded non-coding RNAs that regulate several biological processes, including cell differentiation, growth, and apoptosis. The dysregulations miRNAs are usually correlated with diseases because their regulatory functions in organisms. Over the past few years, often observed to be aberrantly expressed cancers, indicating potential correlations cancer pathogenesis. Recently, evidence has increased prove this assumption. Further...
Protein s-nitrosylation (SNO) is one of the most important post-translational modifications and formed by covalent modification nitric oxide cysteine residues. Extensive studies have shown that SNO plays a pivotal role in plant immune response treating various major human diseases. In recent years, sites become hot research topic. Traditional biochemical methods for site identification are time-consuming costly. this study, we developed an economical efficient prediction tool named Mul-SNO....
Enhancers are crucial for precise regulation of gene expression, while enhancer identification and strength prediction challenging because their free distribution tremendous number similar fractions in the genome. Although several bioinformatics tools have been developed, shortfalls these models remain, performances need further improvement. In present study, a two-layer predictor called Enhancer-FRL was proposed identifying enhancers (enhancers or nonenhancers) activities (strong weak)....
As to the problems of local stereo matching methods, such as window selection difficulty, fuzzy disparity edges and low accuracy in weak texture regions, this paper proposes an efficient algorithm improve these regions. First all, we segment images calculate adaptive support according area each segmentation region. Second, cost is computed based on feature fusion color gradient, then initial can be achieved. Finally, ultimate obtained through a series post-processing, including consistency...
Maintenance hemodialysis is the main method for treatment of end-stage renal disease in China. The <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>K</mi> <mi>t</mi> <mo>/</mo> <mi>V</mi> </math> value gold standard adequacy. However, id="M2"> requires repeated blood drawing and evaluation; it hard to monitor dialysis adequacy frequently. In order meet need clinical assessments adequacy, we want find a noninvasive way assess Therefore, collect some clinically relevant data...
Introduction: A diabetic protein marker is a type of that closely related to diabetes. This kind plays an important role in the prevention and diagnosis Therefore, it necessary identify effective method for predicting markers. In this study, we propose using ensemble methods predict Methodological issues: The consists two aspects. First, combine feature extraction obtain mixed features. Next, classify classifiers. We use three method, including composition physicochemical features...
Eight-puzzle Problem is a one of classic difficulty problem in Artificial Intelligence, to solve this most cases are adopted the search algorithm, and Search strategy main directions artificial intelligence research. Using different strategies process solving also may have differences. In paper, through analysis solution for Problem, Breadth-first Depth-first A*algorithm, which heuristic search, used implement it. These algorithms compared evaluate superiority between these three algorithms,...
In this paper, we investigate green supplier evaluation and selection problems within the interval 2-tuple linguistic environment. Based on operational laws comparison rule of variables, develop some new aggregation operators, such as hybrid averaging (ITHA) operator, ordered weighted averaging-weighted (ITOWAWA) operator geometric (ITHG) operator. Then, an approach for under context variables is proposed based developed operators. Finally, a practical application to problem automobile...
This paper mainly studies the principle and key technology of acoustic emission signal wavelet denoising method, conducted a comparative analysis on three kinds algorithm, while function, threshold method in types comparison experiment, make reconstruction lifting small wave using least square combining transform extract correct signal, determine leakage frequency characteristics application heater fault detection.