Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Polygenic Traits01:18

Polygenic Traits

65.7K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
65.7K
Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.2K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

308
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
308
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

66
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
66
Improving Translational Accuracy02:07

Improving Translational Accuracy

9.8K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
9.8K
Pleiotropy01:33

Pleiotropy

40.4K
Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
40.4K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Association of Genetic Liability to Psychiatric Disorders with Peripheral Metabolic Dysregulation.

medRxiv : the preprint server for health sciences·2026
Same author

Rare Coding Variants Reveal Distinct Genetic Architectures Across Multidimensional Sleep Phenotypes.

medRxiv : the preprint server for health sciences·2026
Same author

A New Finite Element Simulation Methodology for Analyzing the Mechano-Electrochemical Effects of Al Alloys.

Materials (Basel, Switzerland)·2026
Same author

Genome-wide association study and polygenic risk score analysis for bipolar disorder in the Korean population.

Asian journal of psychiatry·2026
Same author

Exome sequencing directly implicates 68 genes in inflammatory bowel disease.

medRxiv : the preprint server for health sciences·2026
Same author

Traditional Chinese medicine therapies for chronic nonspecific low back pain: A systematic review and network meta-analysis.

Journal of back and musculoskeletal rehabilitation·2026
Same journal

Comparative Evaluation of Pretrained Large Language Models for Suicide Risk Prediction from Clinical Notes in U.S. Veterans.

medRxiv : the preprint server for health sciences·2026
Same journal

Nocturnal Respiratory Rate and Variability Predict Long-term Mortality in Stable Outpatients with Cardiovascular Disease.

medRxiv : the preprint server for health sciences·2026
Same journal

MOSAIC: Methylation-Oriented Site Analysis and Information Classifier for Robust Epigenomic Classification of Acute Leukemia in Clinical Cohorts with Variable Tumor Purity.

medRxiv : the preprint server for health sciences·2026
Same journal

Risk beliefs, intensive digital information and demand for a new preventative health product in public clinics: Evidence from an experiment in Zimbabwe.

medRxiv : the preprint server for health sciences·2026
Same journal

Development of an automated, imaging-based preoperative screening model for early identification of malnutrition in an abdominal surgery cohort.

medRxiv : the preprint server for health sciences·2026
Same journal

A Pilot Project Leveraging Large Language Models for Automated Screening and Variable Extraction in Observational Studies.

medRxiv : the preprint server for health sciences·2026
查看所有相关文章

相关实验视频

Updated: Jun 20, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

683

实时动态多基因预测,用于数据流.

Justin D Tubbs1,2,3, Yu Chen3,4,5, Rui Duan6

  • 1Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.

medRxiv : the preprint server for health sciences
|July 23, 2024
PubMed
概括
此摘要是机器生成的。

实时多基因风险评分 (PRS) 动态更新新数据,提高预测准确度,无需重新培训. 这种实时方法通过不断改进患者的遗传风险评估来提高精准医学.

更多相关视频

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

12.9K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.1K

相关实验视频

Last Updated: Jun 20, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

683
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

12.9K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.1K

科学领域:

  • 遗传学 是一个遗传学.
  • 生物信息学是一种生物信息学.
  • 精准医学是一门精准的医学.

背景情况:

  • 多基因风险评分 (PRS) 对精准医学至关重要,但依赖于过时的全基因组关联研究 (GWAS) 数据.
  • 目前的PRS方法对于快速增长的遗传和健康数据集是不理想的,这限制了新患者的预测准确性.

研究的目的:

  • 引入实时PRS-CS (rtPRS-CS),这是一种用于动态PRS改进和校准的新方法.
  • 为了使PRS随着新样本的采集而持续更新,避免需要中间GWAS.

主要方法:

  • 开发了rtPRS-CS用于在线,动态的PRS计算.
  • 进行了广泛的模拟,以评估不同基因架构和样本大小的rtPRS-CS性能.
  • 将rtPRS-CS应用于来自Mass General Brigham Biobank和UK Biobank的定量特征,以及亚洲地区的精神分裂症队列.

主要成果:

  • rtPRS-CS有效地集成了大量的流数据,以随着时间的推移提高PRS预测的准确性.
  • 证明了rtPRS-CS在大规模生物库中增强PRS预测的能力.
  • 验证了rtPRS-CS在精神分裂症队伍中在不同祖先之间动态预测和分层疾病风险的临床实用性.

结论:

  • rtPRS-CS通过实时适应新数据,为PRS方法提供了重大进步.
  • rtPRS-CS的动态性质最大限度地提高了入院患者的预测准确性,进步了精准医学.
  • rtPRS-CS显示了广泛的适用性和临床实用性,用于在不同人群中预测疾病风险.