Eleven grand challenges in single-cell data science
The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers
The rapid growth of high-throughput technologies has transformed biomedical research.
With the increasing amount and complexity of data, scalability and reproducibility have …
With the increasing amount and complexity of data, scalability and reproducibility have …
Benchmarking graph neural networks
In the last few years, graph neural networks (GNNs) have become the standard toolkit for
analyzing and learning from data on graphs. This emerging field has witnessed an extensive …
analyzing and learning from data on graphs. This emerging field has witnessed an extensive …
State of the field in multi-omics research: from computational needs to data mining and sharing
Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine
two or more omics data sets to aid in data analysis, visualization and interpretation to …
two or more omics data sets to aid in data analysis, visualization and interpretation to …
DNA methylation-based predictors of health: applications and statistical considerations
DNA methylation data have become a valuable source of information for biomarker
development, because, unlike static genetic risk estimates, DNA methylation varies …
development, because, unlike static genetic risk estimates, DNA methylation varies …
AltWOA: Altruistic Whale Optimization Algorithm for feature selection on microarray datasets
The data-driven modern era has enabled the collection of large amounts of biomedical and
clinical data. DNA microarray gene expression datasets have mainly gained significant …
clinical data. DNA microarray gene expression datasets have mainly gained significant …
A benchmark for RNA-seq deconvolution analysis under dynamic testing environments
Background Deconvolution analyses have been widely used to track compositional
alterations of cell types in gene expression data. Although a large number of novel methods …
alterations of cell types in gene expression data. Although a large number of novel methods …
Benchmarking computational doublet-detection methods for single-cell RNA sequencing data
In single-cell RNA sequencing (scRNA-seq), doublets form when two cells are encapsulated
into one reaction volume. The existence of doublets, which appear to be—but are not—real …
into one reaction volume. The existence of doublets, which appear to be—but are not—real …
A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells
We present dyngen, a multi-modal simulation engine for studying dynamic cellular
processes at single-cell resolution. dyngen is more flexible than current single-cell …
processes at single-cell resolution. dyngen is more flexible than current single-cell …