[HTML][HTML] Single cell dynamics of tumor specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer
DM Borràs, S Verbandt, M Ausserhofer, G Sturm, J Lim… - Cell Discovery, 2023 - nature.com
CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite
instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of …
instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of …
[HTML][HTML] BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks
SJ Pelletier, M Leclercq, F Roux-Dalvai… - Nature …, 2024 - nature.com
Abstract Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for
profiling complex biological samples. However, batch effects typically arise from differences …
profiling complex biological samples. However, batch effects typically arise from differences …
[HTML][HTML] q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics
Unlocking the full dimensionality of single-cell RNA sequencing data (scRNAseq) is the next
frontier to a richer, fuller understanding of cell biology. We introduce q-diffusion, a framework …
frontier to a richer, fuller understanding of cell biology. We introduce q-diffusion, a framework …
The differential impacts of dataset imbalance in single-cell data integration
Single-cell transcriptomic data measured across distinct samples has led to a surge in
computational methods for data integration. Few studies have explicitly examined the …
computational methods for data integration. Few studies have explicitly examined the …
[HTML][HTML] Integrating single-cell RNA-seq datasets with substantial batch effects
K Hrovatin, AA Moinfar, L Zappia, AT Lapuerta… - bioRxiv, 2023 - ncbi.nlm.nih.gov
Integration of single-cell RNA-sequencing (scRNA-seq) datasets has become a standard
part of the analysis, with conditional variational autoencoders (cVAE) being among the most …
part of the analysis, with conditional variational autoencoders (cVAE) being among the most …
[HTML][HTML] Enhancing Classification of liquid chromatography mass spectrometry data with Batch Effect Removal Neural Networks (BERNN)
A Droit, S Pelletier, M Leclerq, F Roux-Dalvai… - Research …, 2023 - ncbi.nlm.nih.gov
Abstract Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for
profiling complex biological samples. However, batch effects typically arise from differences …
profiling complex biological samples. However, batch effects typically arise from differences …
Enhancing Single-Cell VAE Latent Space via Semi-Supervision
M Gong, K Ivanov, M Heinäniemi… - ICML 2024 Workshop on … - openreview.net
Single-cell data are crucial for biomedical discovery, facilitated by low-dimensional latent
space encoding of single-cell RNA-seq profile. Obtained latent codes can then be plotted …
space encoding of single-cell RNA-seq profile. Obtained latent codes can then be plotted …
[PDF][PDF] Enhancing Classification of liquid chromatography mass spectrometry data with Batch Effect Removal Neural Networks (BERNN)
SJ Pelletier, M Leclerq, F Roux-Dalvai, MB de Geus… - assets-eu.researchsquare.com
Abstract Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for pro
ling complex biological samples. However, batch effects typically arise from differences in …
ling complex biological samples. However, batch effects typically arise from differences in …