基于个体网络的IBD微生物相互作用特征预测数据表1

数据集获取（Figshare）

• 源站标题：Data Sheet 1_Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients.docx
• DOI：10.3389/fmolb.2024.1490533.s009
• 发布日期：2025-01-29
• 文件数：1 个
• 文件总体积：4.13 MB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Individual-network_based_predictions_of_microbial_interaction_signatures_for_response_to_biological_therapies_in_IBD_patients_docx/28301393

命令行下载

curl -L -o "Data Sheet 1_Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients.docx" "https://ndownloader.figshare.com/files/51992930"

文件清单

• Data Sheet 1_Individual-network based predictions of microbial interaction signatures for response to biological therapies in IBD patients.docx（4.13 MB）

文件总体积 4.13 MB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Inflammatory Bowel Disease (IBD), which includes Ulcerative Colitis (UC) and Crohn’s Disease (CD), is marked by dysbiosis of the gut microbiome. Despite therapeutic interventions with biological agents like Vedolizumab, Ustekinumab, and anti-TNF agents, the variability in clinical, histological, and molecular responses remains significant due to inter-individual and inter-population differences. This study introduces a novel approach using Individual Specific Networks (ISNs) derived from faecal microbial measurements of IBD patients across multiple cohorts. These ISNs, constructed from baseline and follow-up data post-treatment, successfully predict therapeutic outcomes based on endoscopic remission criteria. Our analysis revealed that ISNs characterised by core gut microbial families, including Lachnospiraceae and Ruminococcaceae, are predictive of treatment responses. We identified significant changes in abundance levels of specific bacterial genera in response to treatment, confirming the robustness of ISNs in capturing both linear and non-linear microbiota signals. Utilising network topological metrics, we further validated these findings, demonstrating that critical microbial features identified through ISNs can differentiate responders from non-responders with respect to various therapeutic outcomes. The study highlights the potential of ISNs to provide individualised insights into microbiota-driven therapeutic responses, emphasising the need for larger cohort studies to enhance the accuracy of molecular biomarkers. This innovative methodology paves the way for more personalised and effective treatment strategies in managing IBD.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fmolb.2024.1490533.s009（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Individual-network_based_predictions_of_microbial_interaction_signatures_for_response_to_biological_therapies_in_IBD_patients_docx/28301393）。