Carl Kingsford
Academic Editor

Carl Kingsford


Summary

Associate Professor, Computational Biology Department, School of Computer Science, Carnegie Mellon University, and Co-Associate Director, Joint CMU-Pitt Ph.D. Program in Computational Biology. Recipient of the Moore Investigators in Data-Driven Discovery award.

Bioinformatics Computational Biology

Institution affiliations

Work details

Associate Professor

Carnegie Mellon University
http://cbd.cmu.edu
We are interested in designing graph and optimization algorithms to extract insight from biological data. In particular, we focus on the following classes of problems: 1) Genomics & genome assembly: RNA-seq expression quantification; genome assembly; large-scale sequence search, etc. This work is currently supported by a Data-Driven Invesgator grant from the Gordon and Betty Moore Foundation. It was previously supported by NIH grant 1R21HG006913, and NSF grant CCF-1319998. 2) Chromatin structure and function: Algorithms for determining the spatial organization of eukaryotic genomes from Chromosome Conformation Capture data. Supported by NIH grant R01HG007104. 3) Protein interactions and networks: Evolution of interactions; protein function prediction; clustering within networks; protein structure prediction. This work was supported by NSF grant EF-0849899 and by NSF grant CCF-1053918/CCF-1256087 (CAREER award).

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PeerJ Contributions