NEW: The ChIPseeqer paper is out and highlighted as

We strongly encourage graduate students already accepted in the PBSB and Tri-I CBM programs to contact us about potential rotation and thesis projects in our lab. We are an ambitious group of people dedicated to using systems biology approaches to solve cancer and make genomic medicine become reality.

Programming experience (e.g., in Perl, Python, C, C++, Java, R), knowledge in statistics and/or machine learning are particularly useful for the type of research going on in the lab, but are not required. Bench work experience is also a plus.

A non-exhaustive list of potential thesis projects, in no particular order, includes:

  • Revealing the impact of mutations on regulatory networks using RNA-seq data
  • Development of computational methods for gene, pathway and network-level analysis of chromatin conformation data (e.g. ChIA-PET and HiC; we have unpublished datasets for each of these types of data)
  • Novel methods for annotating the B cell regulatory and expressed genome using deep sequencing data
  • Characterization of B cell enhancers using RNA-seq and motif analysis
  • Improved methodologies for detecting cancer mutations from deep sequencing data using machine learning and statistical modelling
  • Studying the impact of DNA methylation measured using genome-wide approaches on transcriptional networks
  • Algorithms and methods for genomic data exploration in the CAVE
  • Computational methods for nucleosome landscape exploration (we have generated genome-wide nucleosome localization maps in normal and malignant B cells)
  • New approaches for revealing transcription factor and miRNA activity and their target genes in cancer cells
  • Revealing post-translational networks using protein motifs
  • Predicting cancer mutations in kinases and transcription factors using machine learning
  • Revealing transcriptor factors, miRNAs and signaling molecules involved in tumor interactions with micro-environment
  • Additional projects here
  • Since we are a joint computational-experimental lab, each of these projects can have an experimental component. Students in the lab are free to choose their own projects, and new project suggestions are always welcome. If you are interested, please contact us:

    Olivier Elemento
    Assistant Professor
    Weill Medical College of Cornell University
    Institute for Computational Biomedicine
    1305 York Avenue
    New York, NY, 10021