AIMC Topic: Genetic Heterogeneity

Clear Filters Showing 1 to 8 of 8 articles

Unravelling single-cell DNA replication timing dynamics using machine learning reveals heterogeneity in cancer progression.

Nature communications Feb 8, 2025
Genomic heterogeneity has largely been overlooked in single-cell replication timing (scRT) studies. Here, we develop MnM, an efficient machine learning-based tool that allows disentangling scRT profiles from heterogenous samples. We use single-cell c...
Machine Learning Animals Neoplasms Disease Progression Humans Genetic Heterogeneity Genomic Instability DNA Replication DNA Replication Timing Cell Line, Tumor Single-Cell Analysis Mice DNA Copy Number Variations
View on PubMed DOI

Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Feb 25, 2020
BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel ...
Neoplastic Syndromes, Hereditary Data Collection Genetic Heterogeneity Utah Pedigree Genetic Predisposition to Disease Urinary Bladder Neoplasms Data Mining Databases, Factual Aged, 80 and over Humans Middle Aged Female Young Adult Machine Learning Risk Assessment Risk Factors Adolescent Adult Aged Incidence Male
View on PubMed DOI

scAI: an unsupervised approach for the integrative analysis of parallel single-cell transcriptomic and epigenomic profiles.

Genome biology Feb 3, 2020
Simultaneous measurements of transcriptomic and epigenomic profiles in the same individual cells provide an unprecedented opportunity to understand cell fates. However, effective approaches for the integrative analysis of such data are lacking. Here,...
Epigenome Genetic Heterogeneity Humans Gene Expression Profiling Transcriptome Single-Cell Analysis Genomics Unsupervised Machine Learning A549 Cells
View on PubMed DOI

Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools.

Cancer reports (Hoboken, N.J.) Nov 11, 2019
BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide, a DNA alkylating agent. However, the a...
Tumor Suppressor Protein p53 Tumor Suppressor Proteins DNA Mutational Analysis Humans Models, Genetic DNA Repair Enzymes Machine Learning Genetic Heterogeneity Precision Medicine Drug Resistance, Neoplasm Antineoplastic Combined Chemotherapy Protocols Immune Checkpoint Inhibitors Brain Chemoradiotherapy, Adjuvant Microtubules Prognosis Glioblastoma Computational Biology Clonal Evolution Mutation DNA Modification Methylases Tumor Microenvironment Cancer Vaccines Brain Neoplasms
View on PubMed DOI

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

SLAS discovery : advancing life sciences R & D Jan 6, 2017
Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medic...
Drug Discovery Single-Cell Analysis Imaging, Three-Dimensional Systems Biology Decision Making Flow Cytometry Reference Values Genetic Heterogeneity Machine Learning Humans Histocytochemistry Decision Support Techniques Precision Medicine Neoplasms
View on PubMed DOI

scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Nucleic acids research Jan 7, 2022
Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populati...
Humans Software Animals Consensus Sequence Gene Expression Regulation Eukaryotic Cells Promoter Regions, Genetic Organ Specificity Drosophila melanogaster Databases, Genetic Single-Cell Analysis Molecular Sequence Annotation Unsupervised Machine Learning Gene Regulatory Networks Cell Lineage Internet Mice Enhancer Elements, Genetic Genetic Heterogeneity Chromatin
View on PubMed DOI

Towards multi-omics characterization of tumor heterogeneity: a comprehensive review of statistical and machine learning approaches.

Briefings in bioinformatics May 20, 2021
The multi-omics molecular characterization of cancer opened a new horizon for our understanding of cancer biology and therapeutic strategies. However, a tumor biopsy comprises diverse types of cells limited not only to cancerous cells but also to tum...
Machine Learning Algorithms Prognosis Neoplasms Humans Genetic Heterogeneity Gene Expression Profiling Genomics Computational Biology Epigenomics
View on PubMed DOI

Machine learning approaches to study glioblastoma: A review of the last decade of applications.

Cancer reports (Hoboken, N.J.) Dec 1, 2019
BACKGROUND: Glioblastoma (GB, formally glioblastoma multiforme) is a malignant type of brain cancer that currently has no cure and is characterized by being highly heterogeneous with high rates of re-incidence and therapy resistance. Thus, it is urge...
History, 21st Century Genomics Humans Glioblastoma Machine Learning Datasets as Topic Brain Neoplasms Genetic Heterogeneity
View on PubMed DOI
Popular Topics
Recent Journals