Yuehui Chen

• Ph.D, Professor
• University of Jinan

The Golgi apparatus is a crucial component of the inner membrane system in eukaryotic cells, playing a central role in protein biosynthesis. Dysfunction of the Golgi apparatus has been linked to neurodegenerative diseases. Accurate identification of sub-Golgi protein types is therefore essential for developing effective treatments for such diseases...

Deep multiview clustering provides an efficient way to analyze the data consisting of multiple modalities and features. Recently, the autoencoder (AE)-based deep multiview clustering algorithms have attracted intensive attention by virtue of their rewarding capabilities of extracting inherent features. Nevertheless, most existing methods are still...

Background Protein–protein interactions (PPIs) are crucial in various biological functions and cellular processes. Thus, many computational approaches have been proposed to predict PPI sites. Although significant progress has been made, these methods still have limitations in encoding the characteristics of each amino acid in sequences. Many featur...

Background: Peroxisomes are membrane-bound organelles that contain one or more types of oxidative enzymes. Aberrant localization of peroxisomal proteins can contribute to the development of various diseases. To more accurately identify and locate peroxisomal proteins, we developed the ProSE-Pero model. Methods: We employed three methods based on...

Contrastive-based clustering models usually rely on a large number of negative pairs to capture uniform representations, which requires a large batch size and high computational complexity. In contrast, some self-supervised methods perform non-contrastive learning to capture discriminative representations only with positive pairs, but suffer from t...

Plant vacuoles are essential organelles in the growth and development of plants, and accurate identification of their proteins is crucial for understanding their biological properties. In this study, we developed a novel model called GraphIdn for the identification of plant vacuole proteins. The model uses SeqVec, a deep representation learning mod...

Membrane protein amphiphilic helices play an important role in many biological processes. Based on the graph convolution network and the horizontal visibility graph the prediction method of membrane protein amphiphilic helix structure is proposed in this paper. The new dataset of amphiphilic helix is constructed. In this paper, we propose the novel...

Video captioning aims to generate natural language sentences that describe the visual content of given videos, which requires long-range temporal modeling and consumes significant computational resources. Existing methods typically operate on frames uniformly sampled from videos, leading to time scale inconsistency and redundancy in contiguous fram...

Pretrained language models such as BERT, ELMO, and GPT have proven to be effective for natural language processing tasks. However, deploying them on computationally constrained devices poses a challenge. Moreover, the practical application of these models is affected by the training and deployment of large-scale pretrained language models. While kn...

Peroxisomes, organelles containing one or more oxidases within a single lipid bilayer, play a crucial role in various metabolic pathways. Incorrect localization of peroxisomal proteins can lead to severe diseases. In this study, we introduced the TAPE-Pero model to improve the accuracy of peroxisomal protein identification and localization. This mo...

Mitochondria, comprising two layers of membranes, are indispensable organelles present in most cells. They perform a vital function in generating cellular energy and facilitating aerobic respiration. Experimentally determining the sub-mitochondrial location of proteins is both time-consuming and costly. Therefore, the development of a reliable meth...

Paeonia lactiflora is a commonly used herb in clinical work of traditional Chinese medicine. Total glucosides of paeony shows its superiority in the treatment of recurrent oral ulcer. Long-term use of total glucosides of paeony has fewer side effects for patients, and is an ideal drug for the treatment of recurrent oral ulcer. In order to further s...

The Chinese character transfer task must meet two requirements: the transfer image should retain the content structure information of the original Chinese character as much as possible, and present different reference styles. Some of the earlier methods required training with large amounts of paired data, which was a time-consuming task. The existi...

In recent years, scene text detection technologies have received more and more attention and have made rapid progress. However, they also face some challenges, such as fracture detection in text instances and the problem of poor robustness of detection models. To address these issues, we propose a scene text detector called CC-DBNet. This detector...

In recent years, benefiting from the abilities in implementation of the smooth operation on noises and preservation of the original gradient information on the texture edges, the guided filter (GF)-based fuzzy clustering has achieved inspiring performance in the task of image segmentation. However, different to image pixels, the general data sample...

Acute lung injury (ALI) is a serious respiratory disease, which can lead to acute respiratory failure or death. It is closely related to the pathogenesis of New Coronavirus pneumonia (COVID-19). Many researches showed that traditional Chinese medicine (TCM) had a good effect on its intervention, and network pharmacology could play a very important...

Obtaining accurate segmentation of central serous chorioretinopathy in spectral‐domain optical coherence tomography (SD‐OCT) is critical for the determination of the disease severity. Although existing methods achieve considerable segmentation results, they heavily depend on large‐scale data with high‐quality annotations. Also, the lesions bear a l...

The amphiphilic helix structure in membrane proteins is involved in membrane-related biological processes and has important research significance. In this paper, we constructed a new amphiphilic helix dataset containing 70 membrane proteins with a total of 18,458 amino acid residues. We extracted three commonly used protein features and predicted t...

Golgi apparatus is also known as Golgi complex and Golgi apparatus. It is one of the components of the endosomal system in eukaryotic cells. The main function of the Golgi apparatus is to process, sort, and transport proteins synthesized by the endoplasmic reticulum, and then sort them into specific parts of the cell or secrete them outside the cel...

S-succinylation of proteins is a significant and common post-translational modification (PTM) that takes place on Cysteine. And in many biological processes, PTM plays an important role, which is also closely related to many diseases in humans. Hence, identifying the s-succinylation sites of Cysteine is very pivotal in biology and disease research....

The study of Protein-DNA binding sites is one of the fundamental problems in genome biology research. It plays an important role in understanding gene expression and transcription, biological research, and drug development. In recent years, language representation models have had remarkable results in the field of Natural Language Processing (NLP)...

Protein is the basis of life activities and plays an irreplaceable role. Proteins usually have a specific biochemical environment that is closely related to protein function, so understanding the subcellular localization information of proteins can provide powerful help for the research of drugs for the treatment of diseases. The prediction of prot...

Kernel clustering has the ability to get the inherent non-linear structure of the data. But the high computational complexity and the unknown representation of the kernel space make it unavailable for the data clustering in distributed peer-to-peer (P2P) networks. To solve this issue, we propose a new series of random feature based collaborative ke...

Distributed clustering based on the Gaussian mixture model (GMM) has exhibited excellent clustering capabilities in peer-to-peer (P2P) networks. However, more iterative numbers and communication overhead are required to achieve the consensus in existing distributed GMM clustering algorithms. In addition, the truth that it cannot find a closed form...

Transcription factors are important cellular components of the process of gene expression control. Transcription factor binding sites are locations where transcription factors specifically recognize DNA sequences, targeting gene-specific regions and recruiting transcription factors or chromatin regulators to fine-tune spatiotemporal gene regulation...

Structured pruning has received ever-increasing attention as a method for compressing convolutional neural networks. However, most existing methods directly prune the network structure according to the statistical information of the parameters. Besides, these methods differentiate the pruning rates only in each pruning stage or even use the same pr...

For high-dimensional data, the cluster structure often exists in a feature subset instead of the whole feature space. Soft subspace clustering can efficiently extract the important subspace by allocating a weight to each dimension on the basis of the contribution of this dimension to the cluster identification. However, this kind of method does not...

Background Nerve discharge is the carrier of information transmission, which can reveal the basic rules of various nerve activities. Recognition of the nerve discharge rhythm is the key to correctly understand the dynamic behavior of the nervous system. The previous methods for the nerve discharge recognition almost depended on the traditional stat...

Collaborative multi-view clustering methods can efficiently realize the view fusion by exploring complementary and consistent information among multiple views. However, these studies all ignore the differences between multiple views in fusion. In fact, in the multi-view clustering, the data is diverse from view to view. The larger the difference be...

The correct classification of cancer subtypes is of great significance for the in-depth study of cancer pathogenesis and the realization of accurate treatment for cancer patients. In recent years, the classification of cancer subtypes using deep neural networks and gene expression data has become a hot topic. However, most classifiers may face the...

Background Correctly classifying the subtypes of cancer is of great significance for the in-depth study of cancer pathogenesis and the realization of personalized treatment for cancer patients. In recent years, classification of cancer subtypes using deep neural networks and gene expression data has gradually become a research hotspot. However, mos...

Background The growing researches of molecular biology reveal that complex life phenomena have the ability to demonstrating various types of interactions in the level of genomics. To establish the interactions between genes or proteins and understand the intrinsic mechanisms of biological systems have become an urgent need and study hotspot. Resul...

Not only is modeling in-vivo protein-DNA binding basic to a deeper comprehension of regulatory mechanisms, but a complicated job in computational biology. Although current deep-learning based methods have achieved some success in-vivo protein-DNA binding, on the one hand, they tend to ignore the weakly supervised information genome sequences, that...

As the basis and key of cell activities, protein plays an important role in many life activities. Protein usually does not work alone. Under normal circumstances, most proteins perform specific functions by interacting with other proteins, and play the greatest role in life activity. The prediction of protein-protein interaction (PPI) is a very bas...

Golgi is an important eukaryotic organelle. Golgi plays a key role in protein synthesis in eukaryotic cells, and its dysfunction will lead to various genetic and neurodegenerative diseases. In order to better develop drugs to treat diseases, one of the key problems is to identify the protein category of Golgi apparatus. In the past, the physical an...

Post-translational modification (PTM) is considered a significant biological process with a tremendous impact on the function of proteins in both eukaryotes, and prokaryotes cells. Malonylation of lysine is a newly discovered post-translational modification, which is associated with many diseases, such as type 2 diabetes and different types of canc...

Non-invasive whole-brain scans aid the diagnosis of neuropsychiatric disorder diseases such as autism, dementia, and brain cancer. The assessable analysis for autism spectrum disorders (ASD) is rationally challenging due to the limitations of publicly available datasets. For diagnostic or prognostic tools, functional Magnetic Resonance Imaging (fMR...

MicroRNAs are a group of noncoding RNAs that are about 20–24 nucleotides in length. They are involved in the physiological processes of many diseases and regulate transcriptional and post-transcriptional gene expression. Therefore, the prediction of microRNAs is of great significance for basic biological research and disease treatment. MicroRNA pre...

Writer identification is one of the research hotspots of computer vision and pattern recognition, and it is of great significance in the fields of judicial authentication, file security protection, historical document analysis, and so on. However, many problems are still challenging due to the different writing sources, the common features of learn...

Automated lesion segmentation is one of the important tasks for the quantitative assessment of retinal diseases in SD-OCT images. Recently, deep convolutional neural networks (CNN) have shown promising advancements in the field of automated image segmentation, whereas they always benefit from large-scale datasets with high-quality pixel-wise annota...

Gaussian mixture model (GMM) is a well-known model-based approach for data clustering. However, when the data samples are insufficient, the classical GMM-based clustering algorithms are not effective anymore. Referring to the idea of transfer clustering methods, this paper proposes a general transfer GMM-based clustering framework, which employs th...

Chinese characters are complex graphics with strokes as the basic unit. In order to analyze their structure, stroke extraction is the first step. This paper presents an automatic extraction method of Chinese character strokes, which regards the extraction of Chinese character strokes as finding the optimal path and merging. Based on the superpixel...

The fuzzy c-means clustering with guided image filter (GF) is a useful method for image segmentation. The single-channel GF can be efficiently applied to the gray-scale guidance image, but for the color guidance image, due to the high run-time overhead on the calculation of the inverse of the covariance matrix, it is a hard work to perform the mult...

The traditional collaborative fuzzy clustering can effectively perform data clustering in distributed peer-to-peer (P2P) networks, which is an impossible task to complete for the centralized clustering methods due to privacy and security requirements or network transmission technology constraints. But it will increase the number of clustering itera...

Most automated segmentation approaches for quantitative assessment of sub-retinal fluid regions rely heavily on retinal anatomy knowledge (e.g. layer segmentation) and pixel-level annotation, which requires excessive manual intervention and huge learning costs. In this paper, we propose a weakly supervised learning method for the quantitative analy...

Lysine malonylation is a newly discovered type of protein post-translational modification, which plays an essential role in many biological activities. A good knowledge of malonylation sites can serve as guidance in solving a large number of biological problems, such as disease diagnosis and drug discovery. There have already been several experimen...

Protein is a complex organic substance with a spatial structure, which exists widely in the body of living things. Almost all living things rely on protein to form an important part of the body, perform many physiological function adjustments, and obtain energy. Without protein, there is no life. Most of these functions of proteins are realized by...

The interactions between proteins play important roles in several organisms, and such issue can be involved in almost all activities in the cell. The research of protein-protein interactions (PPIs) can make a huge contribution to the prevention and treatment of diseases. Currently, many prediction methods based on machine learning have been propose...

In the recent years, the subject of Golgi classification has been studied intensively. It has been scientifically proven that Golgi can synthesize many substances, such as polysaccharides, and it can also combine proteins with sugars or lipids with glycoproteins and lipoproteins. In some cells (such as liver cells), the Golgi apparatus is also invo...

Symbolic regression has been utilized to infer mathematical formulas in order to solve the complex prediction and classification problems. In this paper, complex-valued S-system model (CVSS) is proposed to predict real-valued time series data. In a CVSS model, input variables and rate constants are complex-valued. The time series data need to be tr...

Background: Apoptosis, also called programmed cell death, refers to the spontaneous and orderly death of cells controlled by genes in order to maintain a stable internal environment. Identifying the subcellular location of apoptosis proteins is very helpful in understanding the mechanism of apoptosis and designing drugs. Therefore, the subcellular...

Background: The nervous system senses and transmits information through the firing behavior of neurons, and this process is affected by various noises. However, in the previous study of the influence of noise on nerve discharge, the channel of some noise effects is not clear, and the difference from other noises was not examined. Objective: To c...

Quantitative assessment of retinal layer thickness in spectral domain-optical coherence tomography (SD-OCT) images is vital for clinicians to determine the degree of ophthalmic lesions. However, due to the complex retinal tissues, high-level speckle noises and low intensity constraint, how to accurately recognize the retinal layer structure still r...

Segmentation of retinal layers with central serious chorioretinopathy (CSC) in Spectral Domain Optical Coherence Tomography (SD-OCT) images is significant for quantitative analysis including the volume, location and shape of CSC region. In this paper, we present an automatic segmentation method to segment retinal layers based on graph theory and th...

Lysine Malonylation (Kmal) is a newly discovered protein post-translational modifications (PTMs) type, which plays an important role in many biological processes. Therefore, identifying and understanding Kmal sites is very critical in the studies of biology and diseases. The typical methods are time-wasting and expensive. Nowadays, many researchers...

Background: Cancer subtype classification attains the great importance for accurate diagnosis and personalized treatment of cancer. Latest developments in high-throughput sequencing technologies have rapidly produced multi-omics data of the same cancer sample. Many computational methods have been proposed to classify cancer subtypes, however most...

Kernel clustering methods are useful to discover the non-linear structures hidden in data, but they suffer from the difficulty of kernel selection and high computational complexity. In this paper, we propose a novel random feature map-based multiple kernel fuzzy clustering method with all feature weights, in which low-rank randomized features of mu...

Qualitative assessment of pathological changes is vital for clinicians to determine the degree of neurosensory retinal detachment (NRD). However, accurate segmentation is challenging due to the diversity of NRD size and location. Spectral domain-optical coherence tomography (SD-OCT) imaging technology can yield high-resolution, three-dimensional im...

In this study, the deterministic Chay model is improved considering the K⁺ channel opening probability during the generation of the generation mechanism of action potential. It can not only simulate the periodic firing, chaos and periodic-adding bifurcation that the original Chay model can simulate, but also simulate the rhythm that the original mo...

Lysine lipoylation is a special type of posttranslational modification in both prokaryotes’ and eukaryotes’ proteomics researches. Such a modification takes part in several significant biological processions and plays a key role in the cellular level. In order to construct and design an accurate classification algorithm for identifying lipoylation...

Complex-valued system identification has the ability to providing the basis for system analysis. So as to demonstrate the potential and internal mechanism of complex-value system, such system is more clearly and accurately, this work proposes a novel complex-valued hybrid evolutionary algorithm (CSE) to optimize complex-valued expression model (CEM...

In this paper, the deterministic Chay model was improved considering the generation mechanism of an action potential, with special relevance to the opening of potassium channel after depolarization. Then a chaos-like irregular non-periodic neural firing pattern, which was lying between period n and period (n + 1) bursting in a period-adding bifurca...

Data gravitation-based classification model, a new physic law inspired classification model, has been demonstrated to be an effective classification model for both standard and imbalanced tasks. However, due to its large scale of gravitational computation during the feature weighting process, DGC suffers from high computational complexity, especial...

Background: For a protein to execute its function, ensuring its correct subcellular localization is essential. In addition to biological experiments, bioinformatics is widely used to predict and determine the subcellular localization of proteins. However, single-feature extraction methods cannot effectively handle the huge amount of data and multi...

Background and objective: Quantitative assessment of subretinal fluid in spectral domain optical coherence tomography (SD-OCT) images is crucial for the diagnosis of central serous chorioretinopathy. For the subretinal fluid segmentation, the traditional methods need to segment retinal layers and then segment subretinal fluid. The layer segmentati...

Classification of cancer subtypes is of paramount importance for diagnosis and prognosis of cancer. In recent years, deep learning methods have gained considerable popularity for cancer subtype classification, however, the structure of the neural network is difficult to determine and the performance of the deep network depends largely on its struct...

Each part of internal structure of cells which is commonly mentioned as subcellular is highly ordered and interconnected has unique functions. The experiments show that deviated protein delivery to the corresponding subcellular causes of human disease. Studies of protein localization can clarify pathogenesis and find treatments. As protein subcellu...

Abstract Inference of gene regulatory network (GRN) is crucial to understand intracellular physiological activity and function of biology. The identification of large-scale GRN has been a difficult and hot topic of system biology in recent years. In order to reduce the computation load for large-scale GRN identification, a parallel algorithm based...

Automatic and reliable segmentation for geographic atrophy in spectral-domain optical coherence tomography (SD-OCT) images is a challenging task. To develop an effective segmentation method, a two-stage deep learning framework based on an auto-encoder is proposed. Firstly, the axial data of cross-section images were used as samples instead of the p...

Gene regulatory network (GRN) inference can understand the growth and development of animals and plants, and reveal the mystery of biology. Many computational approaches have been proposed to infer GRN. However, these inference approaches have hardly met the need of modeling, and the reducing redundancy methods based on individual information theor...

To automatically segment the geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images, we propose a novel segmentation method by designing a multi-path 3D convolution neural network (CNN) model in this paper. Firstly, the 3D patch was fed into the multi-path 3D CNN model as sample to preserve spatial features and over...

Forecasting exchange rate plays an important role in the financial market. It has become a hot research topic and many methods have been proposed. In this paper, a wide and deep flexible neural tree (FNT) is proposed to forecast the exchange rate. The wide component has the function to memorize the original input features, while the deep component...

An irregular on-off like spiking activity is observed in the rat neural pacemaker experiment with the changes of extracellular calcium concentration. The spiking activity is simulated using a minimal model, the stochastic INa,P + IK model. The nonlinear time series analysis on ISI series shows the similar stochastic dynamical features of both exper...

In the experimental neural pacemaker of a rat, a novel firing pattern has been discovered. This pattern was generated between the period 2 firing pattern and the period 3 firing pattern during the periodic adding bifurcation and inverse periodic adding bifurcation. The pattern was observed and analyzed in the present investigation. The composition...

Experimental methods play a crucial role in identifying the subcellular localization of proteins and building high-quality databases. However, more efficient, automated computational methods are required to predict the subcellular localization of proteins on a large scale. Various efficient feature extraction methods have been proposed to predict s...

As a kind of high-precision correlation measurement method, Part Mutual Information (PMI) was firstly introduced into Bayesian Networks (BNs) structure learning algorithm in the paper. Compared to the general search scoring algorithm which set the initial network as an empty network without edge, our training algorithm initialized the network struc...

Prediction of subcellular localization of Gram-negative bacterial proteins plays a vital role in the development of antibacterial drugs. Computational approaches have made remarkable progress in bacterial protein subcellular localization, but disadvantages still exist. Recently, deep learning has received significant attention in bioinformatics and...

At present, with continuously expanding of Chinese credit market, thus large amounts of P2P (person-to-person borrow or lend money in Internet Finance) platform were born and have been in development. Most of P2P platform in China carries out the credit risk evaluation of loan applicant by data mining method. As an emerging data mining tool, the ar...

Prediction of subcellular localization is critical for the analysis of mechanism and functions of proteins and biological research. A series of efficient methods have been proposed to identify subcellular localization, but challenges still exist. In this paper, a novel feature extraction method, denoted as F-Dipe, is proposed to identify subcellula...

In recent years, as China’s credit market continues to expand, a large number of P2P (person-to-person borrow or lend money in Internet Finance) platforms were born and developed. Most of the P2P platforms in China use data mining methods to evaluate the credit risk of loan applicants. Artificial neural network (ANN) is an emerging data mining tool...