intCC:一种高效的加权整合性共识聚类多式联运数据
1Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 31, 2023
概括
本研究介绍了intCC,这是一种高效的加权整合集群方法,用于从多组数据中发现癌症亚型. intCC准确地识别了复杂的生物模式,有助于更好地了解人类疾病.
科学领域:
- 计算生物学是一种计算生物学.
- 生物信息学是一种生物信息学.
- 机器学习用于omics数据分析数据分析.
背景情况:
- 高通量多态数据为癌症等复杂疾病提供了洞察力.
- 识别不同的癌症亚型对于有针对性的治疗和改善患者治疗结果至关重要.
- 综合集群是发现子类型的关键无监督学习方法.
研究的目的:
- 开发一种高效的加权整合集群方法,命名为intCC.
- 为了提高从多组学数据中发现亚型的准确性.
- 为癌症研究提供强大的计算工具.
主要方法:
- 结合合体方法,共识聚类和内核学习以实现整合性聚类.
- 开发用于高效准确的集群分析的intCC算法.
- 使用广泛的模拟研究和现实癌症数据集 (TCGA).
主要成果:
- intCC有效地揭示了多态数据中的潜在集群结构.
- 该方法在识别潜在的癌症亚型方面具有很高的准确性.
- 一个关于TCGA泛癌数据集的案例研究验证了intCC的性能.
结论:
- intCC是一个强大而有效的工具,用于整合性聚类和癌症亚型的发现.
- 拟议的方法有助于通过多组学数据分析来理解人类疾病的复杂性.
- 对intCC的R包是公开可用的,用于更广泛的研究应用.
相关概念视频
Weighted Mean
5.2K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.2K
Cluster Sampling Method
11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
515
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
515
Central Tendency: Analysis
154
Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
154
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
70
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...
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...
70
Multicompartment Models: Overview
145
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
145


