cFos-ANAB: A cFos-based Web Tool for Exploring Activated Neurons and Associated Behaviors.

cFos is one of the most widely-studied genes in the field of neuroscience. Currently, there is no systematic database focusing on cFos in neuroscience. We developed a curated database-cFos-ANAB-a cFos-based web tool for exploring activated neurons and associated behaviors in rats and mice, comprising 398 brain nuclei and sub-nuclei, and five associated behaviors: pain, fear, feeding, aggression, and sexual behavior. Direct relationships among behaviors and nuclei (even cell types) under specific stimulating conditions were constructed based on cFos expression profiles extracted from original publications. Moreover, overlapping nuclei and sub-nuclei with potentially complex functions among different associated behaviors were emphasized, leading to results serving as important clues to the development of valid hypotheses for exploring as yet unknown circuits. Using the analysis function of cFos-ANAB, multi-layered pictures of networks and their relationships can quickly be explored depending on users' purposes. These features provide a useful tool and good reference for early exploration in neuroscience. The cFos-ANAB database is available at www.cfos-db.net .

TSVdb: a web-tool for TCGA splicing variants analysis.

BACKGROUND: Collaborative projects such as The Cancer Genome Atlas (TCGA) have generated various -omics and clinical data on cancer. Many computational tools have been developed to facilitate the study of the molecular characterization of tumors using data from the TCGA. Alternative splicing of a gene produces splicing variants, and accumulating evidence has revealed its essential role in cancer-related processes, implying the urgent need to discover tumor-specific isoforms and uncover their potential functions in tumorigenesis. RESULT: We developed TSVdb, a web-based tool, to explore alternative splicing based on TCGA samples with 30 clinical variables from 33 tumors. TSVdb has an integrated and well-proportioned interface for visualization of the clinical data, gene expression, usage of exons/junctions and splicing patterns. Researchers can interpret the isoform expression variations between or across clinical subgroups and estimate the relationships between isoforms and patient prognosis. TSVdb is available at http://www.tsvdb.com , and the source code is available at https://github.com/wenjie1991/TSVdb . CONCLUSION: TSVdb will inspire oncologists and accelerate isoform-level advances in cancer research.