Jijun Tang
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View article: HyperPhS: a pharmacophore-guided multimodal representation framework for metabolic stability prediction through contrastive hypergraph learning
HyperPhS: a pharmacophore-guided multimodal representation framework for metabolic stability prediction through contrastive hypergraph learning Open
Motivation Metabolic stability is crucial in the early stage of drug discovery and development. Drug candidate screening and optimization can be streamlined through the accurate prediction of stability. Functional groups within drug molecu…
View article: Genome-Wide Tissue-Specific RNA Editability Estimation Through Convolution Neural Networks
Genome-Wide Tissue-Specific RNA Editability Estimation Through Convolution Neural Networks Open
View article: ST-deconv: an accurate deconvolution approach for spatial transcriptome data utilizing self-encoding and contrastive learning
ST-deconv: an accurate deconvolution approach for spatial transcriptome data utilizing self-encoding and contrastive learning Open
Single-cell RNA sequencing (scRNA-seq) has significantly deepened our understanding of cellular heterogeneity and cell type interactions, providing insights into how cell populations adapt to environmental variability. However, its lack of…
View article: Advancing osteoarthritis research: the role of AI in clinical, imaging and omics fields
Advancing osteoarthritis research: the role of AI in clinical, imaging and omics fields Open
View article: SVEA: an accurate model for structural variation detection using multi-channel image encoding and enhanced AlexNet architecture
SVEA: an accurate model for structural variation detection using multi-channel image encoding and enhanced AlexNet architecture Open
This study presents SVEA, a deep learning model incorporating advanced encoding and feature extraction techniques to enhance structural variation prediction. The model demonstrates high accuracy, outperforming existing methods by approxima…
View article: Análisis unicelular de alta dimensión que evalúa los efectos de diferentes estrategias de manejo de las vías respiratorias en las células inmunitarias perioperatorias en la cirugía de cáncer de pulmón de células no pequeñas High-Dimensional Single-Cell Analysis Evaluating Effects of Different Airway Management Strategies on Perioperative Immune Cells in Non-Small Cell Lung Cancer Surgery
Análisis unicelular de alta dimensión que evalúa los efectos de diferentes estrategias de manejo de las vías respiratorias en las células inmunitarias perioperatorias en la cirugía de cáncer de pulmón de células no pequeñas High-Dimensional Single-Cell Analysis Evaluating Effects of Different Airway Management Strategies on Perioperative Immune Cells in Non-Small Cell Lung Cancer Surgery Open
View article: GFDet: Multi-Level Feature Fusion Network for Caries Detection Using Dental Endoscope Images
GFDet: Multi-Level Feature Fusion Network for Caries Detection Using Dental Endoscope Images Open
Early dental caries detection by endoscope can prevent complications, such as pulpitis and apical infection. However, automatically identifying dental caries remains challenging due to the uncertainty in size, contrast, low saliency, and h…
View article: A generalizable framework for unlocking missing reactions in genome-scale metabolic networks using deep learning
A generalizable framework for unlocking missing reactions in genome-scale metabolic networks using deep learning Open
Incomplete knowledge of metabolic processes hinders the accuracy of GEnome-scale Metabolic models (GEMs), which in turn impedes advancements in systems biology and metabolic engineering. Existing gap-filling methods typically rely on pheno…
View article: RetroCaptioner: beyond attention in end-to-end retrosynthesis transformer via contrastively captioned learnable graph representation
RetroCaptioner: beyond attention in end-to-end retrosynthesis transformer via contrastively captioned learnable graph representation Open
Motivation Retrosynthesis identifies available precursor molecules for various and novel compounds. With the advancements and practicality of language models, Transformer-based models have increasingly been used to automate this process. H…
View article: EPIMR: Prediction of Enhancer-Promoter Interactions by Multi-Scale ResNet on Image Representation
EPIMR: Prediction of Enhancer-Promoter Interactions by Multi-Scale ResNet on Image Representation Open
Prediction of enhancer-promoter interactions (EPIs) is key to regulating gene expression and diagnosing genetic diseases. Due to limited resolution, biological experiments perform not as well as expected while precisely identifying specifi…
View article: A gene regulatory network–aware graph learning method for cell identity annotation in single-cell RNA-seq data
A gene regulatory network–aware graph learning method for cell identity annotation in single-cell RNA-seq data Open
Cell identity annotation for single-cell transcriptome data is a crucial process for constructing cell atlases, unraveling pathogenesis, and inspiring therapeutic approaches. Currently, the efficacy of existing methodologies is contingent …
View article: Comprehensive cross cancer analyses reveal mutational signature cancer specificity
Comprehensive cross cancer analyses reveal mutational signature cancer specificity Open
Mutational signatures refer to distinct patterns of DNA mutations that occur in a specific context or under certain conditions. It is a powerful tool to describe cancer etiology. We conducted a study to show cancer heterogeneity and cancer…
View article: Drug–Drug Interaction Relation Extraction Based on Deep Learning: A Review
Drug–Drug Interaction Relation Extraction Based on Deep Learning: A Review Open
Drug–drug interaction (DDI) is an important part of drug development and pharmacovigilance. At the same time, DDI is an important factor in treatment planning, monitoring effects of medicine and patient safety, and has a significant impact…
View article: Species identification through deep learning and geometrical morphology in oaks (<i>Quercus</i> spp.): Pros and cons
Species identification through deep learning and geometrical morphology in oaks (<i>Quercus</i> spp.): Pros and cons Open
Plant phenotypic characteristics, especially leaf morphology of leaves, are an important indicator for species identification. However, leaf shape can be extraordinarily complex in some species, such as oaks. The great variation in leaf mo…
View article: Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification
Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification Open
This paper focuses on the classification task of breast ultrasound images and researches on the reliability measurement of classification results. We proposed a dual-channel evaluation framework based on the proposed inference reliability …
View article: Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification
Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification Open
This paper focuses on the classification task of breast ultrasound images and researches on the reliability measurement of classification results. We proposed a dual-channel evaluation framework based on the proposed inference reliability …
View article: Tell Me More About Multi-Granularity Semantic Relationship Information from Images
Tell Me More About Multi-Granularity Semantic Relationship Information from Images Open
View article: Rfae: A High-Robust Feature Selector Based on Fractal Autoencoder
Rfae: A High-Robust Feature Selector Based on Fractal Autoencoder Open
View article: RecGOBD: accurate recognition of gene ontology related brain development protein functions through multi-feature fusion and attention mechanisms
RecGOBD: accurate recognition of gene ontology related brain development protein functions through multi-feature fusion and attention mechanisms Open
Motivation Protein function prediction is crucial in bioinformatics, driven by the growth of protein sequence data from high-throughput technologies. Traditional methods are costly and slow, underscoring the need for computational solution…
View article: Deep neural network based tissue deconvolution of circulating tumor cell RNA
Deep neural network based tissue deconvolution of circulating tumor cell RNA Open
View article: Additional file 1 of Deep neural network based tissue deconvolution of circulating tumor cell RNA
Additional file 1 of Deep neural network based tissue deconvolution of circulating tumor cell RNA Open
Additional file 1: RNA-seq data from normal tissues.
View article: Genotyping data and population location for <i>Quercus</i> <i>aliena</i> and <i>Q</i><i>uercus dent</i><i>ata</i>
Genotyping data and population location for <i>Quercus</i> <i>aliena</i> and <i>Q</i><i>uercus dent</i><i>ata</i> Open
"SSR_ALL.txt" is the genotyping data for all 538 samples of the Quercus aliena and Quercus dentata scored using Genemarker v. 2.2, then normalized the score by FlexiBinv2 in TXT format.
View article: Genotyping data for <i>Quercus</i> <i>aliena</i> and <i>Q</i><i>uercus dent</i><i>ata</i>
Genotyping data for <i>Quercus</i> <i>aliena</i> and <i>Q</i><i>uercus dent</i><i>ata</i> Open
"SSR_ALL.txt" is the genotyping data for all 538 samples of the Quercus aliena and Quercus dentata scored using Genemarker v. 2.2, then normalized the score by FlexiBinv2 in TXT format.
View article: Genotyping data for <i>Quercus</i> <i>aliena</i> and <i>Q</i><i>uercus dent</i><i>ata</i>
Genotyping data for <i>Quercus</i> <i>aliena</i> and <i>Q</i><i>uercus dent</i><i>ata</i> Open
"SSR_ALL.txt" is the genotyping data for all 538 samples of the Quercus aliena and Quercus dentata scored using Genemarker v. 2.2, then normalized the score by FlexiBinv2 in TXT format.
View article: CoMutDB: the landscape of somatic mutation co-occurrence in cancers
CoMutDB: the landscape of somatic mutation co-occurrence in cancers Open
Motivation Somatic mutation co-occurrence has been proven to have a profound effect on tumorigenesis. While some studies have been conducted on co-mutations, a centralized resource dedicated to co-mutations in cancer is still lacking. Resu…
View article: Sustainable Cotton Production through Increased Competitiveness: Analysis of Comparative Advantage and Influencing Factors of Cotton Production in Xinjiang, China
Sustainable Cotton Production through Increased Competitiveness: Analysis of Comparative Advantage and Influencing Factors of Cotton Production in Xinjiang, China Open
Cotton production makes an important contribution to the income of rural residents and the economy in Xinjiang province, which leads other provinces in terms of planted area, total production, and average yield of cotton in China. This stu…
View article: Robust data storage in DNA by de Bruijn graph-based de novo strand assembly
Robust data storage in DNA by de Bruijn graph-based de novo strand assembly Open
DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as strand breaks, rearrangements,…
View article: EAA-Net: Rethinking the Autoencoder Architecture with Intra-class Features for Medical Image Segmentation
EAA-Net: Rethinking the Autoencoder Architecture with Intra-class Features for Medical Image Segmentation Open
Automatic image segmentation technology is critical to the visual analysis. The autoencoder architecture has satisfying performance in various image segmentation tasks. However, autoencoders based on convolutional neural networks (CNN) see…
View article: Identification of DNA N4-methylcytosine Sites via Multiview Kernel Sparse Representation Model
Identification of DNA N4-methylcytosine Sites via Multiview Kernel Sparse Representation Model Open
| openaire: EC/H2020/101016775/EU//INTERVENE
View article: Prediction of Major Histocompatibility Complex Binding with Bilateral and Variable Long Short Term Memory Networks
Prediction of Major Histocompatibility Complex Binding with Bilateral and Variable Long Short Term Memory Networks Open
As an important part of immune surveillance, major histocompatibility complex (MHC) is a set of proteins that recognize foreign molecules. Computational prediction methods for MHC binding peptides have been developed. However, existing met…