Cristian Coarfa, Ph.D.
Associate Professor
Positions
- Associate Professor
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Mol & Cell Biology-Mol.Regulation
Baylor College of Medicine
Houston, TX, US
- Associate Professor
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Dan L Duncan Comprehensive Cancer Center
Baylor College of Medicine
Houston, Texas, United States
- Associate Professor
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Center for Precision Environmental Health
BAYLOR COLLEGE OF MEDICINE
Houston, Texas, United States
Education
- PhD from Rice University
- Houston, TX, United States
- Computer Science
- MS from Rice University
- Houston, TX, United States
- Computer Science
Professional Statement
Our research focuses on achieving biological insight via integrative analysis, interpretation, and visualization of large scale multi-omics datasets, and enabling of scientific advancements via collaborative tools and computing platforms. Our lab has extensive experience with analysis of RNA-Seq coding and non-coding transcriptomics, Small RNA-Seq, Whole-Genome Bisulfite-Seq, MS-based Metabolomics and Lipidomics, MS Proteomics, and RPPA Proteomics. We have developed methods for integration of genetic and epigenetic variation, reference pipelines for epigenetic assays, and bioinformatic tools for high-throughput reads mapping and structural variants detection. Our current focus is on tool development for metabolomics and transcriptomics integration, and mining of large transcriptomic and epigenomic data collections.
Websites
Selected Publications
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Coarfa C, Yu F, Miller CA, Chen Z, Harris RA, Milosavljevic A. " Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing. " BMC Bioinformatics. 2010 ; 11 : 572.
Pubmed PMID: 21092284. -
Van Baak TE, Coarfa C, et al, Waterland RA.. " Epigenetic supersimilarity of monozygotic twin pairs " Genome Biology. 2018 Jan 9; 19
Pubmed PMID: 29310692. -
Mindikoglu AL, Opekun AR, Putluri N, Coarfa C. " Unique metabolomic signature associated with hepatorenal dysfunction and mortality in cirrhosis " Transl Res. 2018 May ;
Pubmed PMID: 29291380. -
Abbas HA, Bui NHB, Rajapakshe K, Wong J, Gunaratne P, Tsai KY, Coarfa C, Flores ER. " Distinct TP63 Isoform-Driven Transcriptional Signatures Predict Tumor Progression and Clinical Outcomes " Cancer Research. 2018 Jan ;
Pubmed PMID: 29180475.
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