Single cell RNA‐sequencing: A powerful yet still challenging technology to study cellular heterogeneity
Almost all biomedical research to date has relied upon mean measurements from cell
populations, however it is well established that what it is observed at this macroscopic level …
populations, however it is well established that what it is observed at this macroscopic level …
Gene expression based inference of cancer drug sensitivity
Inter and intra-tumoral heterogeneity are major stumbling blocks in the treatment of cancer
and are responsible for imparting differential drug responses in cancer patients. Recently …
and are responsible for imparting differential drug responses in cancer patients. Recently …
Evolution-informed strategies for combating drug resistance in cancer
The ever-changing nature of cancer poses the most difficult challenge oncologists face
today. Cancer's remarkable adaptability has inspired many to work toward understanding …
today. Cancer's remarkable adaptability has inspired many to work toward understanding …
Personalized tumor combination therapy optimization using the single-cell transcriptome
Background The precise characterization of individual tumors and immune
microenvironments using transcriptome sequencing has provided a great opportunity for …
microenvironments using transcriptome sequencing has provided a great opportunity for …
scDrugPrio: A framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases
Background Ineffective drug treatment is a major problem for many patients with immune-
mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic …
mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic …
PERCEPTION predicts patient response and resistance to treatment using single-cell transcriptomics of their tumors
Tailoring optimal treatment for individual cancer patients remains a significant challenge. To
address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression …
address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression …
Large-scale cell representation learning via divide-and-conquer contrastive learning
Single-cell RNA sequencing (scRNA-seq) data is a potent tool for comprehending the"
language of life" and can provide insights into various downstream biomedical tasks. Large …
language of life" and can provide insights into various downstream biomedical tasks. Large …
Predicting drug response from single-cell expression profiles of tumours
Background Intra-tumour heterogeneity (ITH) presents a significant obstacle in formulating
effective treatment strategies in clinical practice. Single-cell RNA sequencing (scRNA-seq) …
effective treatment strategies in clinical practice. Single-cell RNA sequencing (scRNA-seq) …
CREAMMIST: an integrative probabilistic database for cancer drug response prediction
H Yingtaweesittikul, J Wu, A Mongia… - Nucleic Acids …, 2023 - academic.oup.com
Extensive in vitro cancer drug screening datasets have enabled scientists to identify
biomarkers and develop machine learning models for predicting drug sensitivity. While most …
biomarkers and develop machine learning models for predicting drug sensitivity. While most …
A review of computational methods for predicting cancer drug response at the single-cell level through integration with bulk RNAseq data
Cancer treatment failure is often attributed to tumor heterogeneity, where diverse malignant
cell clones exist within a patient. Despite a growing understanding of heterogeneous tumor …
cell clones exist within a patient. Despite a growing understanding of heterogeneous tumor …