• Translational Systems Bioinformatics Software

    1. QRNAseq: for Functional Isoform, Driver Mutation Gene and Fusion Gene Detection

    Introduction

    QRNAseq is a tool to manage huge amounts of RNA-seq data in an integrative way which includes RNA-seq data quality control, read alignment, gene fusion, gene mutation, isoform identification and function analysis. TheQRNAseqsystem comprises pipelines that load input, analyzes the NGS data, exports outputs into a relational database, integrates and mines the data with other data types, and generates key gene signatures of interest.
    Please download the software here. QRNAseq software

    2. NSMAP: A Method for Spliced Isoforms Identification and Quantification from RNA-Seq

    Introduction
    NSMAP (Nonnegativity and Sparsity constrained Maximum A Posteriori ) is designed to identify and quantify isoforms from RNA-seq by incorporating a sparsity term into expression level estimation to enable isoform structure prediction and expression estimation simultaneously.

    Please download the software here. NSMAP: A Method for Spliced Isoforms Identification and Quantification from RNA-Seq

    3. FusionQ: A tool for gene fusion detection and quantification using paired-end RNA-Seq

    This document provides the information of how to download, install and run FusionQ. FusionQ is written in C++ and perl, and prefer performing on a multi-core computer. FusionQ is tested on Linux Ubuntu and Debian. We used gcc complier (Debian 4.6.3 and Ubuntu/Linaro 4.6.1-9ubuntu3) to compile the source code.

    Please download the software here. FusionQ: a Tool for Detection and Quantification of Chimerical RNAs from Paired-end RNA-seq

    4. Conditional Random Pattern Model for Copy Number Aberration (CNA) Detection

    Please download the software here. CRP_CNV: Conditional Random Pattern Model for Copy Number Aberration (CNA) Detection

    • 5. Conditional Random Pattern Algorithm for LOH Inference and Segmentation

    Please download the software here. CRP_LOH: Conditional Random Pattern Algorithm for LOH Inference and Segmentation

    6. Multi-scale Agent-Based Brain Tumor Modeling Project

    "ABM-TKI" is a tool, employing agent-based model (ABM), to simulate brain tumor growth that includes an EGFR signaling pathway together with a related cell-cycle pathway, angiogenesis and tyrosine kinase inhibitors (TKIs) treatment. We can apply this tool to predict the responses of brain cancer to TKIs, and to reveal the dual role of angiogenesis during TKI treatment.

    Please download the software here. ABM-TKI: Multi-scale Agent-Based Brain Tumor Modeling