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According to the National Cancer Institute, there were 9.5 million cancer-related deaths in 2018. A challenge in improving treatment is resistance in genetically unstable cells. The purpose of this study is to evaluate unsupervised machine…

基因组学 · 定量生物学 2021-08-12 Anastasia Dunca , Frederick R. Adler

The exploration of cellular heterogeneity within the tumor microenvironment (TME) via single-cell RNA sequencing (scRNA-seq) is essential for understanding cancer progression and response to therapy. Current scRNA-seq approaches, however,…

基因组学 · 定量生物学 2025-02-06 Yu-An Huang , Yue-Chao Li , Hai-Ru You , Jie Pan , Xiyue Cao , Xinyuan Li , Zhi-An Huang , Zhu-Hong You

Single-cell RNA sequencing (scRNA-seq) enables dissecting cellular heterogeneity in tissues, resulting in numerous biological discoveries. Various computational methods have been devised to delineate cell types by clustering scRNA-seq data…

定量方法 · 定量生物学 2023-09-18 Tram Huynh , Zixuan Cang

High throughput genome sequencing technologies such as RNA-Seq and Microarray have the potential to transform clinical decision making and biomedical research by enabling high-throughput measurements of the genome at a granular level.…

The spatial distributions of different types of cells could reveal a cancer cell growth pattern, its relationships with the tumor microenvironment and the immune response of the body, all of which represent key hallmarks of cancer. However,…

计算机视觉与模式识别 · 计算机科学 2018-09-28 Shidan Wang , Tao Wang , Lin Yang , Faliu Yi , Xin Luo , Yikun Yang , Adi Gazdar , Junya Fujimoto , Ignacio I. Wistuba , Bo Yao , ShinYi Lin , Yang Xie , Yousheng Mao , Guanghua Xiao

Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various…

The cell cycle is one of the most fundamental biological processes important for understanding normal physiology and various pathologies such as cancer. Single cell RNA sequencing technologies give an opportunity to analyse the cell cycle…

定量方法 · 定量生物学 2022-08-11 Alexander Chervov , Andrei Zinovyev

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has…

分子网络 · 定量生物学 2014-09-09 Edwin Wang , Jinfeng Zou , Naif Zaman , Lenore K. Beitel , Mark Trifiro , Miltiadis Paliouras

Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently…

分子网络 · 定量生物学 2021-06-15 Michael A. Kochen , Steven S. Andrews , H. Steven Wiley , Song Feng , Herbert M. Sauro

Individual cancer cells carry a bewildering number of distinct genomic alterations i.e., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here we performed…

Cancer survival prediction is an active area of research that can help prevent unnecessary therapies and improve patient's quality of life. Gene expression profiling is being widely used in cancer studies to discover informative biomarkers…

机器学习 · 计算机科学 2016-11-18 Hamid Reza Hassanzadeh , John H. Phan , May D. Wang

High-dimensional point cloud data arise across many scientific domains, especially single-cell biology. The shapes or topologies of these datasets determine the types of information that can be extracted. For example, clustered data…

In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to…

组织与器官 · 定量生物学 2014-04-29 Philip Gerlee , Eunjung Kim , Alexander R. A. Anderson

Early detection of cancer plays a key role in improving survival rates, but identifying reliable biomarkers from RNA-seq data is still a major challenge. The data are high-dimensional, and conventional statistical methods often fail to…

Recently, there has been a resurgence of interest in rigorous algorithms for the inference of cancer progression from genomic data. The motivations are manifold: (i) growing NGS and single cell data from cancer patients, (ii) need for novel…

机器学习 · 计算机科学 2016-02-25 Daniele Ramazzotti

Single-cell RNA-seq data allow the quantification of cell type differences across a growing set of biological contexts. However, pinpointing a small subset of genomic features explaining this variability can be ill-defined and…

Identifying cell clusters is a critical step for single-cell transcriptomics study. Despite the numerous clustering tools developed recently, the rapid growth of scRNA-seq volumes prompts for a more (computationally) efficient clustering…

定量方法 · 定量生物学 2023-01-11 Nana Wei , Yating Nie , Lin Liu , Xiaoqi Zheng , Hua-Jun Wu4

As immunotherapies become standard cancer treatments, it is increasingly important to identify a patient's immune profile, which encompasses the activity of immune cells within the tumor microenvironment and the presence of specific…

基因组学 · 定量生物学 2026-03-31 Soham Chatterjee

In this study, we develop consistent estimators for key parameters that govern the dynamics of tumor cell populations when subjected to pharmacological treatments. While these treatments often lead to an initial reduction in the abundance…

应用统计 · 统计学 2024-03-21 Kevin Leder , Ruping Sun , Zicheng Wang , Xuanming Zhang

The vast amount of sequencing data presently available allow the scientific community to explore a range of genetic variables that may drive and progress cancer. A myriad of predictive tools has been proposed, allowing researchers and…

基因组学 · 定量生物学 2023-03-31 Mona Nourbakhsh , Kristine Degn , Astrid Saksager , Matteo Tiberti , Elena Papaleo
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