RDscan: Extracting RNA-disease relationship from literature Using pre-training model DOI Creative Commons
Yang Zhang, Yu Yang, Liping Ren

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Фев. 9, 2024

Abstract With the rapid advancements in molecular biology and genomics, a multitude of connections between RNA diseases has been unveiled, making efficient accurate extraction RNA-disease relationships (RD relationships) from extensive biomedical literature crucial for advancing research this field. This study introduces RDscan, novel text mining method developed based on pre-training fine-tuning strategy, aimed at automatically extracting RD-related information vast corpus using pre-trained large language models. Initially, we constructed dedicated RD corpus, comprising 2,082 positive 2,000 negative statements, alongside an independent test dataset training evaluating RDscan. Subsequently, by Bioformer BioBERT models, RDscan demonstrated exceptional performance classification named entity recognition (NER) tasks. In 5-fold cross-validation, significantly outperformed traditional machine learning methods. summary, represents first tool specifically designed relationship extraction, is freely available https://github.com/ZhangCellab/RDScaning.

Язык: Английский

A First Computational Frame for Recognizing Heparin-Binding Protein DOI Creative Commons
Wen Zhu, Shi-Shi Yuan, Jian Li

и другие.

Diagnostics, Год журнала: 2023, Номер 13(14), С. 2465 - 2465

Опубликована: Июль 24, 2023

Heparin-binding protein (HBP) is a cationic antibacterial derived from multinuclear neutrophils and an important biomarker of infectious diseases. The correct identification HBP great significance to the study This work provides first recognition framework based on machine learning accurately identify HBP. By using four sequence descriptors, non-HBP samples were represented by discrete numbers. inputting these features into support vector (SVM) random forest (RF) algorithm comparing prediction performances methods training data independent test data, it found that SVM-based classifier has greatest potential model could produce auROC 0.981 ± 0.028 10-fold cross-validation overall accuracy 95.0% data. As for recognition, will provide some help diseases stimulate further research in related fields.

Язык: Английский

Процитировано

71

Cm-siRPred: Predicting chemically modified siRNA efficiency based on multi-view learning strategy DOI
Tianyuan Liu, Junyang Huang, Hongmei Luo

и другие.

International Journal of Biological Macromolecules, Год журнала: 2024, Номер 264, С. 130638 - 130638

Опубликована: Март 7, 2024

Язык: Английский

Процитировано

18

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review) DOI Open Access
Liping Ren,

Danni Huang,

Hongjiang Liu

и другие.

Oncology Letters, Год журнала: 2024, Номер 27(4)

Опубликована: Фев. 14, 2024

Gastric cancer (GC) is a prominent contributor to global cancer‑related mortalities, and deeper understanding of its molecular characteristics tumor heterogeneity required. Single‑cell omics spatial transcriptomics (ST) technologies have revolutionized research by enabling the exploration cellular landscapes at single‑cell level. In present review, an overview advancements in ST their applications GC provided. Firstly, multiple methods are discussed, highlighting ability offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns location tissues. Furthermore, summary provided key findings from previous on used GC, which valuable diagnosis prognosis, microenvironment analysis, treatment response. summary, application has revealed levels holds promise for improving diagnostics, personalized treatments patient outcomes GC.

Язык: Английский

Процитировано

11

TCM2COVID: A resource of anti‐COVID‐19 traditional Chinese medicine with effects and mechanisms DOI
Liping Ren, Yi Xu, Lin Ning

и другие.

iMeta, Год журнала: 2022, Номер 1(4)

Опубликована: Авг. 5, 2022

In China, traditional Chinese medicine (TCM) has been widely used for coronavirus infectious disease 2019 (COVID-19) prevention, treatment, and recovery played a part in the battle against disease. A variety of TCM treatments have recommended different stages COVID-19. But, to best our knowledge, comprehensive database storing organizing anti-COVID is still lacking. Herein, we developed TCM2COVID, manually curated resource formulas, natural products (NPs), herbs. The current version TCM2COVID (1) documents over 280 formulas (including 300 herbs) with detailed clinical evidence therapeutic mechanism information; (2) records 80 NPs potential mechanisms; (3) launches useful web server querying, analyzing visualizing documented similar those supplied by user (formula similarity analysis). summary, TCM2COVD provides user-friendly practical platform documenting, browsing treatments, will help development elucidation mechanisms action new therapies support fight COVID-19 epidemic. freely available at http://zhangy-lab.cn/tcm2covid/.

Язык: Английский

Процитировано

29

ACVPred: Enhanced prediction of anti-coronavirus peptides by transfer learning combined with data augmentation DOI

Yi Xu,

Tianyuan Liu, Yu Yang

и другие.

Future Generation Computer Systems, Год журнала: 2024, Номер 160, С. 305 - 315

Опубликована: Июнь 7, 2024

Язык: Английский

Процитировано

8

Role of oxidative stress in the concurrent development of osteoporosis and tendinopathy: Emerging challenges and prospects for treatment modalities DOI Creative Commons

Xianting Xia,

Zhengyuan Fang,

Yinhua Qian

и другие.

Journal of Cellular and Molecular Medicine, Год журнала: 2024, Номер 28(13)

Опубликована: Июль 1, 2024

Both osteoporosis and tendinopathy are widely prevalent disorders, encountered in diverse medical contexts. Whilst each condition has distinct pathophysiological characteristics, they share several risk factors underlying causes. Notably, oxidative stress emerges as a crucial intersecting factor, playing pivotal role the onset progression of both diseases. This imbalance arises from dysregulation generating neutralising reactive oxygen species (ROS), leading to an abnormal environment. Elevated levels ROS can induce multiple cellular disruptions, such cytotoxicity, apoptosis activation reduced cell function, contributing tissue deterioration weakening structural integrity bones tendons. Antioxidants substances that prevent or slow down oxidation process, including Vitamin C, melatonin, resveratrol, anthocyanins so on, demonstrating potential treating these overlapping disorders. comprehensive review aims elucidate complex within interlinked pathways comorbid conditions. By integrating contemporary research empirical findings, our objective is outline new conceptual models innovative treatment strategies for effectively managing underscores importance further in-depth validate efficacy antioxidants traditional Chinese medicine plans, well explore targeted interventions focused on promising areas future advancements.

Язык: Английский

Процитировано

8

Policy research on role of traditional medicine in emergency health system construction based on the PMC index model: evidence from China DOI Creative Commons
Yujing Zhang, Tian Xia, Chen Zhao

и другие.

BMC Complementary Medicine and Therapies, Год журнала: 2025, Номер 25(1)

Опубликована: Янв. 8, 2025

Abstract Background The integration of traditional Chinese medicine (TCM) into emergency health systems in China serves as a model for global policy development and refining the inclusion emergencies. Methods This study investigated 13 public policies related to TCM released by central government from 2003–2023. A PMC(Policy Modeling Consistency) index was developed combining ROSTCM text mining analysis software. contents these documents were quantitatively assessed using 10 first- 40 s-level indicators. Results content results showed that current focus on treatment, State Administration Traditional Medicine is issuing authority main policies, most which are issued form notice. scoring two, five, three, three rated excellent, good, qualified, unqualified, respectively. indicates quality use response normally distributed generally although room further improvement exists; should follow principles science, reasonableness, operability, be updated timely manner with continuous governance period while focusing content, safeguards, role measures. Conclusion Effective backed state institutions vital. includes enforcing relevant laws regulations, establishing multidisciplinary medical teams, developing integrated strategies support clinical research maximize unique benefits medicine.

Язык: Английский

Процитировано

1

CFNCM: Collaborative filtering neighborhood-based model for predicting miRNA-disease associations DOI
Biffon Manyura Momanyi, Hasan Zulfiqar,

Bakanina Kissanga Grace-Mercure

и другие.

Computers in Biology and Medicine, Год журнала: 2023, Номер 163, С. 107165 - 107165

Опубликована: Июнь 9, 2023

Язык: Английский

Процитировано

9

E-MuLA: An Ensemble Multi-Localized Attention Feature Extraction Network for Viral Protein Subcellular Localization DOI Creative Commons

Grace-Mercure Bakanina Kissanga,

Hasan Zulfiqar,

Shenghan Gao

и другие.

Information, Год журнала: 2024, Номер 15(3), С. 163 - 163

Опубликована: Март 13, 2024

Accurate prediction of subcellular localization viral proteins is crucial for understanding their functions and developing effective antiviral drugs. However, this task poses a significant challenge, especially when relying on expensive time-consuming classical biological experiments. In study, we introduced computational model called E-MuLA, based deep learning network that combines multiple local attention modules to enhance feature extraction from protein sequences. The superior performance the E-MuLA has been demonstrated through extensive comparisons with LSTM, CNN, AdaBoost, decision trees, KNN, other state-of-the-art methods. It noteworthy achieved an accuracy 94.87%, specificity 98.81%, sensitivity 84.18%, indicating potential become tool predicting virus localization.

Язык: Английский

Процитировано

3

RDscan: Extracting RNA-disease relationship from the literature based on pre-training model DOI
Yang Zhang, Yu Yang, Liping Ren

и другие.

Methods, Год журнала: 2024, Номер 228, С. 48 - 54

Опубликована: Май 22, 2024

Язык: Английский

Процитировано

3