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BRANE Cut – biologically-related a priori network enhancement with graph cuts...
Inferring gene networks from high-throughput data constitutes an important step in the discovery of relevant regulatory relationships in organism cells. Despite the large number of available Gene...
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RNA-Enrich – gene set enrichment (GSE) testing for RNA-Seq data
Tests for differential gene expression with RNA-seq data have a tendency to identify certain types of transcripts as significant, e.g. longer and highly-expressed transcripts. This tendency has been...
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PAGODA – Characterizing transcriptional heterogeneity through pathway and...
The transcriptional state of a cell reflects a variety of biological factors, from cell-type-specific features to transient processes such as the cell cycle, all of which may be of interest. However,...
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GOexpress – an R/Bioconductor package for the identification and...
Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or...
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GeneAnalytics – An Integrative Gene Set Analysis Tool for Next Generation...
Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from...
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miTALOS v2 – Analyzing Tissue Specific microRNA Function
MicroRNAs are involved in almost all biological processes and have emerged as regulators of signaling pathways. Researchers from the German Research Center for Environmental Health show that miRNA...
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DIANA-mirExTra v2.0 – Uncovering microRNAs and transcription factors with...
Differential expression analysis (DEA) is one of the main instruments utilized for revealing molecular mechanisms in pathological and physiological conditions. DIANA-mirExTra v2.0 performs a combined...
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Sinova – Systematic Reconstruction of Molecular Cascades Using Single-Cell...
The growth plate (GP) comprising sequentially differentiated cell layers is a critical structure for bone elongation and regeneration. Although several key regulators in GP development have been...
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gsa4mirna – Integrated gene set analysis for microRNA studies
Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set...
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Inferring metabolic pathway activity levels from RNA-Seq data
Assessing pathway activity levels is a plausible way to quantify metabolic differences between various conditions. This is usually inferred from microarray expression data. Wide availability of NGS...
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Analyzing and interpreting genome data at the network level with ConsensusPathDB
ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a...
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GeneSCF – a real-time based functional enrichment tool with support for...
High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools...
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AbsFilterGSEA – Improving Gene-Set Enrichment Analysis of RNA-Seq Data with...
Deregulated pathways identified from transcriptome data of two sample groups have played a key role in many genomic studies. Gene-set enrichment analysis (GSEA) has been commonly used for pathway or...
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Proteome profiling outperforms transcriptome profiling for co-expression...
Co-expression of mRNAs under multiple conditions is commonly used to infer co-functionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent...
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iPANDA – a novel approach for analyzing signaling and metabolic pathway...
Today Insilico Medicine announced the publication of its in silico Pathway Activation Network Decomposition Analysis (iPANDA), a novel approach for analyzing signaling and metabolic pathway...
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Scalable latent-factor models applied to single-cell RNA-seq data separate...
Single-cell RNA-sequencing (scRNA-seq) allows heterogeneity in gene expression levels to be studied in large populations of cells. Such heterogeneity can arise from both technical and biological...
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Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases
The species-specific plant Pathway Genome Databases (PGDBs) based on the BioCyc platform provide a conceptual model of the cellular metabolic network of an organism. Such frameworks allow analysis of...
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Overview of methods and tools used to create and analyse co-expression...
Gene co-expression networks can be used to associate genes of unknown function with biological processes, to prioritize candidate disease genes or to discern transcriptional regulatory programmes. With...
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SeqGSA – gene set analysis with length bias adjustment for RNA-seq data
In gene set analysis, the researchers are interested in determining the gene sets that are significantly correlated with an outcome, e.g. disease status or treatment. With the rapid development of high...
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