Han Liang's Research Group
Computational Cancer Genomics
MCLP (TCPA)To facilitate access of the broader research community to cancer proteomics datasets, we have developed a user-friendly data portal for cell lines.
- Website: http://tcpaportal.org/mclp/#/
The Atlas of Noncoding RNA in Cancer (TANRIC)To facilitate access of the broader research community to cancer lncRNA expression datasets, we have developed a user-friendly data portal for lncRNA.
- Website: http://bioinformatics.mdanderson.org/main/TANRIC:Overview
The Cancer Proteome Atlas (TCPA)To facilitate access of the broader research community to cancer proteomics datasets, we have developed a user-friendly data portal, TCPA (The Cancer Proteome Atlas). The current data release contains 4,495 tumor samples in total, and mainly consists of three parts. (i) TCGA tumor tissue sample sets; (ii) independent tumor tissue sample set; and (iii) >500 cell-line samples. TCPA currently provides six modules: Summary, My Protein, Download, Visualization, Analysis and Cell line. Importantly, this resource provides a unique opportunity to validate the findings from TCGA data and identify model cell lines for functional investigation.
- Website: http://bioinformatics.mdanderson.org/main/TCPA
BM-MapA next-generation sequencing genomic loci mapping refiner, which improves the mapping of the multireads (reads mapped to more than one genomic location with the same or similar fidelities), as a refinement step after the general read-alignment is completed.
- Website: http://bioinformatics.mdanderson.org/main/BM-Map
SurvNetSurvNet is a valuable bioinformatic tool for identifying network-based biomarkers that most correlate with patient survival data. SurvNet takes three input files: one biological network file as the searching platform (one human protein interaction network is provided as default), one molecular profiling file (e.g., array-based gene expression or DNA methylation data or mutation data), and one patient survival data file. Given user-defined parameters, SurvNet will automatically identify sub-networks that most correlate with patient survival data and display the results in a visually appealing manner.
- Website: http://bioinformatics.mdanderson.org/main/SurvNet
eFISMICHuman cancer is usually initiated by acquiring critical somatic mutations in tumor cells. In particular, Driver somatic mutations in the coding regions can modify protein functions, thereby resulting in a phenotypic effect on cell survival and proliferation. eFISMIC is a comprehensive database containing experimental evidence on the functional impacts of somatic mutations detected in human cancer.
- Website: http://bioinformatics.mdanderson.org/main/EFISMIC
SWAKKSWAKK is a bioinformatic web server for detecting amino acid sites under positive selection using a sliding window substitution rate analysis
- Website: http://oxytricha.princeton.edu/SWAKK/