Rehan Akbani
Professor
The University of Texas MD Anderson Cancer Center
Department of Bioinformatics and Computational Biology
Dr. Rehan Akbani has dedicated himself to working on high-profile large-scale genomics projects such as The Cancer Genome Atlas (TCGA) and other projects from the Center for Cancer Genomics (CCG) at NCI, with twin emphases on (i) proteomic analysis (principally by reverse-phase proteomic array; RPPA) and (ii) quality control and batch effects mitigation for cancer molecular data sets. He is a Principal Investigator (PI) on several grants from the NCI and DoD. Dr. Akbani leads the bioinformatics analysis and quality control of CCG’s Reverse Phase Protein Array (RPPA) based protein expression data that’s produced by Dr. Gordon Mills’ lab at MD Anderson. He also leads CCG’s overall data quality control and batch effects effort. Besides those projects, Dr. Akbani is the PI on a gastric cancer research project whose goal is to identify disrupted biomarkers and pathways in gastric cancer. The project compares gastric cancer with other GI cancers to gain insights into its biology. Furthermore, Dr. Akbani leads several TCGA projects, notably a Pan-gynecologic cancers effort and a Pan-Cancer TGF-beta pathway project which study molecular aberrations in those tumor types or pathway. Students in his lab can expect to work on such high-profile projects, where they can learn (i) how to work with genomic, proteomic and other molecular data sets, (ii) how to perform quality control and batch effects mitigation in the data, (iii) perform cutting edge bioinformatics research in gastric, gynecologic and other cancers, (iv) study several pathways in detail, such as the TGF-beta pathway.
Publications
- Protocol for obtaining cancer type and subtype predictions using subSCOPE
- Protocol for assessing distances in pathway space for classifier feature sets from machine learning methods
- DrBioRight 2.0: an LLM-powered bioinformatics chatbot for large-scale cancer functional proteomics analysis
- Ion suppression correction and normalization for non-targeted metabolomics
- Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers
- A protein expression atlas on tissue samples and cell lines from cancer patients provides insights into tumor heterogeneity and dependencies
- The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma
- An IROA Workflow for correction and normalization of ion suppression in mass spectrometry-based metabolomic profiling data
- PCA-Plus: Enhanced principal component analysis with illustrative applications to batch effects and their quantitation
- Chimeric RNAs reveal putative neoantigen peptides for developing tumor vaccines for breast cancer
- SETD2 Loss and ATR Inhibition Synergize to Promote cGAS Signaling and Immunotherapy Response in Renal Cell Carcinoma
- Author Correction: Butler enables rapid cloud-based analysis of thousands of human genomes
- Author Correction: Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition
- Author Correction: Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer
- Author Correction: The landscape of viral associations in human cancers
Education & Training
PhD, University of Texas at San Antonio, 2009