Fang Lab @ Mount Sinai

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Office: 212-659-1570
Now: openings for postdoctoral fellows, visiting scholars and graduate students.
Aug 2013: Gang invited to give a Frontiers of Science talk on Epigenomics and Diseases, Kavli Foundation, Korean and US National Academy of Science (link).
Jul 2013: Gang selected to give a Frontiers in Science talk on Epigenomics and SMRT-Seq, JPI meeting, ISMB (link).
May 2013: Gang received U of Minn Best Dissertation Award,  "Discovering Combinatorial Disease Biomarkers" (cs, umn).
Mar 2013: Leverage sequence context effects for control-free detection of DNA modifications, PLoS Comp Bio (link).
Jan 2013: Comparative methylomes between two Mycoplasma strains, published in PLoS Genetics (link).
Nov 2012: The methylome of the German outbreak E. Coli, Nature Biotechnology (Fang et al.). Also, highlighted in Nature Reviews Genetics, Nature Reviews Microbiology. Media coverage: Bio-IT World, TheScientist, PHYS.

Oct 2012: Statistical modeling of kinetic variation data and the first map of base-resolution human mitochondrial DNA modifications, Genome Research. (link)

Gang Fang, PhD

Assistant Professor
Department of Genetics and Genomic Sciences
Institute for Genomics and Multi-scale Biology

Mount Sinai School of Medicine
1425 Madison Ave, Suite 3-70 Room J
New YorK, NY 10029

Functional/comparative epigenomics/genomics
Third-gen Seq (single molecule real-time)
Pathogen-host interactions in infectious disease
damages in mitochondrial DNA
Genetic interactions in Mental Disorders

We are a computational biology labotorary that emphasizes biological and clinical impacts in the design of effective computational and statistical models. Our research goal is to reveal uncharacterized (often neglected) aspects of disease mechanisms that hold promise for better disease diagnosis and treatment. We are also interested in disease-related fundamental biological problems such as regulation and evolution. Towards this goal, we leverage novel types of high-throughput data and ask novel questions with existing types of data.

Computational integration of large scale functional and comparative (epi)genomic data in an epistasis-aware and multi-scale manner is the major theme of our research. We are currently pursuing two research directions, each with specific projects that aim towards answering the following question sets, respectively:

  • How does DNA chemical modifications contribute to pathogen virulence and drug resistance?
  • Are there methylations in mitochondrial DNA or just damages? Where are they?
  • What are the functional roles of mitochondrial DNA modifications in diseases and cell reprogramming?
  • How do genomic variations and epigenomic variations interact with each other?

  • How does epistasis (genetic interactions) add to the missing heritability of diseases?
  • How to discover statistically significant and biologically relevant epistasis from GWAS and Sequencing data?
  • How do brain regions functionally compensate each other?
  • How to integrate genomic, epigenomic and brain imaging data to identify novel and reliable drug targets?

Refer to Research and Publication for more details on our projects and join our team to reveal the answers and cool biology!