A group of genes controlled as a unit, usually by the same repressor or activator gene, is known as a regulon. The ability to identify active regulons...
Read More »circRNAprofiler – an R-based computational framework for the downstream analysis of circular RNAs
Circular RNAs (circRNAs) are a newly appreciated class of non-coding RNA molecules. Numerous tools have been developed for the detection of circRNAs, however computational tools to perform downstream...
Read More »ConSReg – prediction of condition-specific regulatory genes using machine learning
Recent advances in genomic technologies have generated data on large-scale protein–DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To ...
Read More »Tximeta – Reference sequence checksums for provenance identification in RNA-seq
Correct annotation metadata is critical for reproducible and accurate RNA-seq analysis. When files are shared publicly or among collaborators with incorrect or missing annotation metadata, it becomes difficult or impossible to reproduce bioinformatic...
Read More »VARUS – sampling complementary RNA reads from the sequence read archive
Vast amounts of next generation sequencing RNA data has been deposited in archives, accompanying very diverse original studies. The data is readily...
Read More »RNAsamba: long-noncoding RNA identification using a neural network classification model
The advent of high-throughput sequencing technologies made it possible to obtain large volumes of genetic information, quickly and inexpensively. Thus, many efforts are devoted to unveiling the biological roles of genomic elements, being the distinction between protein-coding and long non-coding ...
Read More »Machine learning-based annotation of long noncoding RNAs using PLncPRO
Long noncoding RNAs (lncRNAs) are noncoding RNAs with transcript length more than 200 nucleotides. Although poorly conserved, lncRNAs are expressed across diverse species, including plants and animals, and are known to be involved in...
Read More »Comet – combinatorial prediction of marker panels from single-cell transcriptomic data
Single-cell transcriptomic studies are identifying novel cell populations with exciting functional roles in various in vivo contexts, but identification of succinct gene marker panels for such populations remains a challenge. Researchers at the Dana-Farber...
Read More »A comparison of automatic cell identification methods for single-cell RNA sequencing data
Single-cell transcriptomics is rapidly advancing our understanding of the cellular composition of complex tissues and organisms. A major limitation in most...
Read More »CellAssign – probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling
Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering...
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