|Antoine Barthelet (Yu)||
Application of machine learning algorithms to identify the important components of protein-protein interactions and their networks.
|Juan Beltran||1st Year - currently rotating|
|Ian Caldas||1st Year - currently rotating|
|Nicholas Cheney (Lipson)||
Evolution of artificial agents and analysis of their brains in order to answer questions about cognition.
|Tinyi Chu (Danko)||Developing Bioinformatics tools and addressing biological questions using state of-art machine learning and statistical learning algorithms.|
|Using ancestral recombination graphs for inference in population genetics, especially demographic reconstruction of human populations.|
|Discovering trends and patterns in biological datasets, such as protein network disruption datasets and drug-drug interaction datasets, with statistical methods and machine learning tools.|
|Manisha Munasinghe (Clark)|
|Interested in both developing machine learning techniques to aid in the identification of transcription unit boundaries, and in improving our understanding of chromatin structure and how it affects gene regulation.|
|Nathan Oakes (Messer)||
Characterizing the dynamics of rapid evolution in complex demographics.
|Ying Qiao (TBD)||Developing statistical and computational methods to understand the relationship of DNA replication timing and mutational landscape of the genome.|
Afrah Shafquat (Mezey)
|Developing statistical and computational methods to identify biomarkers associated with complex phenotypes.|
|Shayne Wierbowski||1st Year - currently rotating|
|TRI-I COMPUTATIONAL BIOLOGY & MEDICINE||RESEARCH FOCUS|
|Lenore Pipes (Siepel/
|The Non-Human Primate Reference Transcriptome Resource Project.|
|Nathaniel Tippens (Yu/Lis)||
Developing an experimental technique to map all protein-DNA interactions in accessible regions of the genome. I am interested in applying this and other genomic techniques to study the transcriptional mechanisms that specify cellular identity.
|Yiping Wang (Gu)||Developing a new constraint-based computational method called FALCON, to predict metabolic flux distributions using gene expression.|