Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene expression at a cellular resolution. However, noise due to amplification and dropout may obstruct analyses, so scalable...
Read More »MetaMap – An atlas of metatranscriptomic reads in human disease-related RNA-seq data
With the advent of the age of big data in bioinformatics, large volumes of data and high performance computing power enable researchers to perform re-analyses of publicly available datasets...
Read More »Single cell RNA-seq denoising using a deep count autoencoder
Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene expression at a cellular resolution. However, noise due to amplification and dropout may obstruct analyses, so scalable...
Read More »A new statistical method allows researchers to infer different developmental processes from RNA-Seq data
Through RNA sequencing, researchers can measure which genes are expressed in each individual cell of a sample. A new statistical method allows researchers to infer different developmental processes from a cell mixture consisting of asynchronous stages. This finding has been ...
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