4.7 Article

DisSim: an online system for exploring significant similar diseases and exhibiting potential therapeutic drugs

期刊

SCIENTIFIC REPORTS
卷 6, 期 -, 页码 -

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/srep30024

关键词

-

资金

  1. National Natural Science Foundation of China [61502125]
  2. Heilongjiang Postdoctoral Fund [LBH-Z15179]
  3. China Postdoctoral Science Foundation [2016M590291]

向作者/读者索取更多资源

The similarity of pair-wise diseases reveals the molecular relationships between them. For example, similar diseases have the potential to be treated by common therapeutic chemicals (TCs). In this paper, we introduced DisSim, an online system for exploring similar diseases, and comparing corresponding TCs. Currently, DisSim implemented five state-of-the-art methods to measure the similarity between Disease Ontology (DO) terms and provide the significance of the similarity score. Furthermore, DisSim integrated TCs of diseases from the Comparative Toxicogenomics Database (CTD), which can help to identify potential relationships between TCs and similar diseases. The system can be accessed from http://123.59.132.21:8080/DisSim.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Letter Infectious Diseases

COVID-19 subgroups may slow down biological age acceleration

Yu Guo, Ying Zhang, Yang Hu

JOURNAL OF INFECTION (2023)

Article Biochemistry & Molecular Biology

gutMDisorder v2.0: a comprehensive database for dysbiosis of gut microbiota in phenotypes and interventions

Changlu Qi, Yiting Cai, Kai Qian, Xuefeng Li, Jialiang Ren, Ping Wang, Tongze Fu, Tianyi Zhao, Liang Cheng, Lei Shi, Xue Zhang

Summary: The gut microbiota plays a crucial role in maintaining health, and disruptions can lead to disorders. The gutMDisorder database provides a valuable resource for studying dysbiosis, and the latest version offers expanded data and improved features.

NUCLEIC ACIDS RESEARCH (2023)

Article Virology

An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2

Zijun Zhu, Xinyu Chen, Chao Wang, Sainan Zhang, Rui Yu, Yubin Xie, Shuofeng Yuan, Liang Cheng, Lei Shi, Xue Zhang

Summary: This study conducted a genome-wide association study (GWAS) to identify host genetic factors associated with COVID-19. The correlation between genetic variations and gene expression was assessed using expression quantitative trait locus (eQTL) analysis. The findings revealed 20 genes significantly associated with immunity and neurological disorders. Single-cell datasets were used to validate these findings and to explore the causal relationship between COVID-19 and neurological disorders. Cell experiments were conducted to investigate the effects of COVID-19-related protein-coding genes. This study provides important insights into the genetic architecture underlying the pathophysiology of COVID-19.

JOURNAL OF MEDICAL VIROLOGY (2023)

Article Medicine, Research & Experimental

Upregulation of SLC12A3 and SLC12A9 Mediated by the HCP5/miR-140-5p Axis Confers Aggressiveness and Unfavorable Prognosis in Uveal Melanoma

Congcong Yan, Xiaojuan Hu, Xiaoyan Liu, Jingting Zhao, Zhenmin Le, Jiayao Feng, Meng Zhou, Xiaoyin Ma, Qingxiang Zheng, Jie Sun

Summary: In this study, the role of solute carriers (SLCs) in uveal melanoma (UVM) was investigated using an integrative multiomics analysis. It was found that high expression of SLC12A3 and SLC12A9 was associated with unfavorable prognosis in UVM patients. The study also identified the HCP5-miR-140-5p axis as a potential noncoding RNA pathway upstream of SLC12A3 and SLC12A9, which may be involved in immunomodulation and serve as a novel predictor for clinical prognosis and immunotherapy responsiveness. These findings provide valuable insights for the development of SLC-targeted therapy and drug discovery for UVM.

LABORATORY INVESTIGATION (2023)

Article Biology

DeepDrRVO: A GAN-auxiliary two-step masked transformer framework benefits early recognition and differential diagnosis of retinal vascular occlusion from color fundus photographs

Zijian Yang, Yibo Zhang, Ke Xu, Jie Sun, Yue Wu, Meng Zhou

Summary: A deep learning model called DeepDrRVO was developed for early and differential diagnosis of retinal vascular occlusion (RVO). Trained on color fundus photographs, this model achieved high accuracy on different datasets and outperformed conventional classification models. These results highlight the potential benefits of the deep learning model in early RVO detection and differential diagnosis.

COMPUTERS IN BIOLOGY AND MEDICINE (2023)

Article Multidisciplinary Sciences

The transcriptional landscape and diagnostic potential of long non-coding RNAs in esophageal squamous cell carcinoma

Meng Zhou, Siqi Bao, Tongyang Gong, Qiang Wang, Jie Sun, Jiaqi Li, Minyi Lu, Wanyuan Sun, Jianzhong Su, Hongyan Chen, Zhihua Liu

Summary: This study developed a lncRNA signature predictive of ESCC and validated it across multiple external cohorts. It demonstrated the potential of lncRNAs as non-invasive biomarkers for the early detection of ESCC.

NATURE COMMUNICATIONS (2023)

Article Oncology

Deep learning identifies a T-cell exhaustion-dependent transcriptional signature for predicting clinical outcomes and response to immune checkpoint blockade

Zicheng Zhang, Hongyan Chen, Dongxue Yan, Lu Chen, Jie Sun, Meng Zhou

Summary: This study investigated the dynamic changes in molecular profiles of T-cell exhaustion (TEX) during immune checkpoint blockade (ICB) treatment, and identified an ICB-associated transcriptional signature consisting of 16 TEX-related genes. A machine-learning model called MLTIP incorporating 16 ITGs achieved reliable predictive power for clinical ICB response. The MLTIP consistently demonstrated superior predictive performance compared to other well-established markers and signatures.

ONCOGENESIS (2023)

Article Medicine, General & Internal

DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

Ning Zhao, Zicheng Zhang, Qiang Wang, Lin Li, Zichao Wei, Hongyan Chen, Meng Zhou, Zhihua Liu, Jianzhong Su

Summary: This study characterizes DNA damage repair (DDR) subtypes in esophageal squamous cell carcinoma (ESCC) and investigates their prognostic value. Two distinct DDR subtypes, DDRactive and DDRsilent, are identified, and their independent prognostic values are observed in locoregional ESCC. Additionally, a combination immunotherapy strategy is proposed and validated for high-risk locoregional ESCC tumors.

EBIOMEDICINE (2023)

Article Biology

Automatic detection and differential diagnosis of age-related macular degeneration from color fundus photographs using deep learning with hierarchical vision transformer

Ke Xu, Shenghai Huang, Zijian Yang, Yibo Zhang, Ye Fang, Gongwei Zheng, Bin Lin, Meng Zhou, Jie Sun

Summary: The study presents a deep learning model called DeepDrAMD for the detection and differentiation of AMD subtypes using color fundus photographs (CFPs). The model achieved high performance in AMD detection and classification, surpassing conventional methods and expert-level diagnosis. It offers significant cost savings and efficiency improvements compared to manual reading approaches.

COMPUTERS IN BIOLOGY AND MEDICINE (2023)

Article Medical Laboratory Technology

Noninvasive early differential diagnosis and progression monitoring of ovarian cancer using the copy number alterations of plasma cell-free DNA

Lu Chen, Rong Ma, Chang Luo, Qin Xie, Xin Ning, Kaidi Sun, Fanling Meng, Meng Zhou, Jie Sun

Summary: This study utilized LC-WGS to analyze genome-wide copy number variations (CNVs) in plasma cfDNA, identifying CNV markers associated with ovarian cancer and developing predictive models for tumor classification. Additionally, certain CNV features associated with survival outcomes and chemotherapy response were discovered.

TRANSLATIONAL RESEARCH (2023)

Article Biochemistry & Molecular Biology

Single-cell characterization of macrophages in uveal melanoma uncovers transcriptionally heterogeneous subsets conferring poor prognosis and aggressive behavior

Ke Li, Lanfang Sun, Yanan Wang, Yixin Cen, Jingting Zhao, Qianling Liao, Wencan Wu, Jie Sun, Meng Zhou

Summary: A recent study utilized single-cell transcriptome data to explore the cellular heterogeneity of macrophages within the uveal melanoma (UM) tumor microenvironment, revealing four distinct macrophage subsets. One subset, M phi-C4, was found to be associated with aggressive tumor behavior and poor survival outcomes. The study also developed a machine-learning-based subtyping system to classify UM subtypes and predict prognosis based on M phi-C4-specific core metagenes. This research deepens our understanding of cellular heterogeneity in UM and highlights the potential therapeutic benefits of targeting macrophages in UM treatment.

EXPERIMENTAL AND MOLECULAR MEDICINE (2023)

暂无数据