From The Pathologist by Tian Yu
The accurate identification of cellular phenotype, intercellular signaling networks, and the spatial arrangement of cells within organs is critical to providing a deeper understanding of physiological processes and the disruptions that cause disease. Cellular heterogeneity is a common feature of many malignancies – and so, techniques that allow us to detect and characterize oncologic cellular heterogeneity can help advance cancer diagnostics and therapies.
One promising technology for characterizing cellular heterogeneity is single-cell sequencing. Conventional bulk sequencing methods use many cells, but lose cell heterogeneity information after the signals are summarized and averaged. Conversely, single-cell techniques use next-generation sequencing to analyze the genetic content of individual cells, providing valuable insights into their unique functional characteristics.
From The Pathologist by Tian Yu
The accurate identification of cellular phenotype, intercellular signaling networks, and the spatial arrangement of cells within organs is critical to providing a deeper understanding of physiological processes and the disruptions that cause disease. Cellular heterogeneity is a common feature of many malignancies – and so, techniques that allow us to detect and characterize oncologic cellular heterogeneity can help advance cancer diagnostics and therapies.
One promising technology for characterizing cellular heterogeneity is single-cell sequencing. Conventional bulk sequencing methods use many cells, but lose cell heterogeneity information after the signals are summarized and averaged. Conversely, single-cell techniques use next-generation sequencing to analyze the genetic content of individual cells, providing valuable insights into their unique functional characteristics.
Related Posts
Worm’s radical transformation shows metamorphosis can change the functions of cells
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Scientists map dormant cancer cells’ hideouts, opening new targets for treatment
Soluble signals released by neighboring cells direct how the human kidney is built
Genetics influence how cancer arises – and how it evolves
RNA-based testing uncovers extraordinary diversity in mutations driving lung cancer
Study offers new insights into why ex-smokers remain at elevated risk of lung disease
Learning the grammar of gene regulation
From The Pathologist by Tian Yu
The accurate identification of cellular phenotype, intercellular signaling networks, and the spatial arrangement of cells within organs is critical to providing a deeper understanding of physiological processes and the disruptions that cause disease. Cellular heterogeneity is a common feature of many malignancies – and so, techniques that allow us to detect and characterize oncologic cellular heterogeneity can help advance cancer diagnostics and therapies.
One promising technology for characterizing cellular heterogeneity is single-cell sequencing. Conventional bulk sequencing methods use many cells, but lose cell heterogeneity information after the signals are summarized and averaged. Conversely, single-cell techniques use next-generation sequencing to analyze the genetic content of individual cells, providing valuable insights into their unique functional characteristics.
Related Posts
Worm’s radical transformation shows metamorphosis can change the functions of cells
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Scientists map dormant cancer cells’ hideouts, opening new targets for treatment
Soluble signals released by neighboring cells direct how the human kidney is built
Genetics influence how cancer arises – and how it evolves
RNA-based testing uncovers extraordinary diversity in mutations driving lung cancer
Study offers new insights into why ex-smokers remain at elevated risk of lung disease
Learning the grammar of gene regulation
Stay Connected
Submit a Post to the Blog
Recent Posts
Subscribe to the RNA-Seq Blog
RNA-Seq Products & Services