使人类衍生数据公平:来自NCI数据共享工作坊办公室的反
Mousumi Ghosh1, Ying Huang1, Heather K Basehore1
1Office of Data Sharing, National Cancer Institute, National Institutes of Health, Rockville, MD, USA.
Journal of the National Cancer Institute
|December 26, 2025
概括
联邦政策促进负责任地分享生物医学研究数据. 研讨会确定了癌症研究必不可少的患者临床数据,旨在实现FAIR数据原则以最大限度地提高研究影响.
科学领域:
- 生物医学研究的研究.
- 数据科学是数据科学.
- 癌症研究 癌症研究
背景情况:
- 美国联邦政策,包括NIH数据管理和共享 (DMS) 和公共访问政策,要求对公共资助的研究成果进行负责任的共享.
- 确保科学数据是 FAIR (可查找,可访问,可互操作,可重复使用) 对于最大限度地提高其可用性和影响至关重要.
- 国家癌症研究所 (NCI) 数据共享办公室 (ODS) 召开了研讨会,以解决临床数据共享的挑战.
研究的目的:
- 确定高价值的临床数据特征,用于癌症研究中的收集和共享.
- 探索数据使用的挑战,并提出有效科学数据共享的解决方案.
- 为全面的癌症研究建立关于患者获得的最低临床信息的共识.
主要方法:
- 举办了一系列研讨会,让研究人员和利益相关者参与其中.
- 总结了关于数据使用挑战和潜在解决方案的研讨会讨论.
- 在癌症研究中,确定了关于患者获得的临床数据的基本共识.
主要成果:
- 强调需要对各种数据类型和方法进行结构化输出,以实现公平共享.
- 概述了与会者对各种癌症研究所需的最低患者衍生临床信息的共识.
- 确定了数据使用的挑战,并提出了有效的数据共享的潜在解决方案.
结论:
- 研讨会的成果为收集和共享有影响力的临床数据的最佳实践建议提供了基础.
- 为决策者和研究人员提出的关于对来自人类的临床数据进行一致和有效管理的初步指南.
- 强调了FAIR数据原则对于加强癌症研究中数据最终用户的共享过程和结果的重要性.
更多相关视频
04:07Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays
Published on: February 24, 2023
2.1K
06:32Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
Published on: July 14, 2023
1.8K
相关概念视频
02:46Chi-square Analysis
28.9K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
28.9K
02:54Evolutionary Relationships through Genome Comparisons
5.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.8K
02:26Comparing Copy Number Variations and SNPs
11.6K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
11.6K
02:34DNA Microarrays
16.8K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
16.8K
01:29Bias in Epidemiological Studies
1.7K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.7K
01:28Human Genetics
2.0K
Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
The complex relationship between genetics and psychology is observable through common biological components such...
2.0K