GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels.

Cancer initiation and progression are likely caused by the dysregulation of biological pathways. Gene set analysis (GSA) could improve the signal-to-noise ratio and identify potential biological insights on the gene set level. However, platforms exploring cancer multi-omics data using GSA methods are lacking.

Three Major Gastrointestinal Cancers Could Be Distinguished through Subclass-Specific IgG Glycosylation.

Esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC) are three major digestive tract tumors with higher morbidity and mortality due to significant molecular heterogeneity. Altered IgG glycosylation has been observed in inflammatory activities and disease progression, and the IgG glycome profile could be used for disease stratification. However, IgG -glycome profiles in these three cancers have not been systematically investigated.

EVAtool: an optimized reads assignment tool for small ncRNA quantification and its application in extracellular vesicle datasets.

Extracellular vesicles (EVs) carrying various small non-coding RNAs (sncRNAs) play a vital roles in cell communication and diseases. Correct quantification of multiple sncRNA biotypes simultaneously in EVs is a challenge due to the short reads (<30 bp) could be mapped to multiple sncRNA types. To address this question, we developed an optimized reads assignment algorithm (ORAA) to dynamically map multi-mapping reads to the sncRNA type with a higher proportion.

EVAtlas: a comprehensive database for ncRNA expression in human extracellular vesicles.

Extracellular vesicles (EVs) packing various molecules play vital roles in intercellular communication. Non-coding RNAs (ncRNAs) are important functional molecules and biomarkers in EVs. A comprehensive investigation of ncRNAs expression in EVs under different conditions is a fundamental step for functional discovery and application of EVs.

hTFtarget: A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets.

Transcription factors (TFs) as key regulators play crucial roles in biological processes. The identification of TF-target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression. The accumulated data of chromatin immunoprecipitation sequencing (ChIP-seq) provide great opportunities to discover the TF-target regulations across different conditions.

ImmuCellAI: A Unique Method for Comprehensive T-Cell Subsets Abundance Prediction and its Application in Cancer Immunotherapy.

The distribution and abundance of immune cells, particularly T-cell subsets, play pivotal roles in cancer immunology and therapy. T cells have many subsets with specific function and current methods are limited in estimating them, thus, a method for predicting comprehensive T-cell subsets is urgently needed in cancer immunology research. Here, Immune Cell Abundance Identifier (ImmuCellAI), a gene set signature-based method, is introduced for precisely estimating the abundance of 24 immune cell types including 18 T-cell subsets, from gene expression data.

FFLtool: a web server for transcription factor and miRNA feed forward loop analysis in human.

Summary: Transcription factors (TFs) and microRNAs (miRNAs) are two kinds of important regulators for transcriptional and post-transcriptional regulations. Understanding cross-talks between the two regulators and their targets is critical to reveal complex molecular regulatory mechanisms. Here, we developed FFLtool, a web server for detecting potential feed forward loop (FFL) of TF-miRNA-target regulation in human.

Systematic Transcriptome and Regulatory Network Analyses Reveal the Hypoglycemic Mechanism of Dendrobium fimbriatum.

Type 2 diabetes (T2D) is a long-term metabolic disorder disease characterized by high blood sugar and relative lack of insulin. Previous studies have demonstrated that Dendrobium has potent glucose-lowing effects and may serve as add-ons or alternatives to classic medications for T2D prevention and treatment, but the underlying molecular mechanisms were still unclear. We performed biochemical and transcriptional profiling (RNA sequencing [RNA-seq] and microRNA sequencing [miRNA-seq]) analyses on the pancreas and liver of Dendrobium fimbriatum extract (DFE)-fed diabetic rats and control animals.