Computational Biology

[Fan et al., 2019]
 
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Jason Fan, Anthony Cannistra, Inbar Fried, Tim Lim, Thomas Schaffner, Mark Crovella, Benjamin Hescott, Mark D. M. Leiserson (2019).
Functional Protein Representations from Biological Networks Enable Diverse Cross-Species Inference.
In: Nucleic Acids Research, . doi:10.1093/nar/gkz132
[Lancour et al., 2018]
 
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Daniel Lancour, Adam Naj, Richard Mayeux, Jonathan L. Haines, Margaret A. Pericak-Vance, Gerard C. Schellenberg, Mark Crovella, Lindsay A. Farrer and Simon Kasif (2018).
One for all and all for One: Improving replication of genetic studies through network diffusion.
In: PLoS Genetics, 14(4):1--20. doi:10.1371/journal.pgen.1007306
[Leiserson et al., 2018]
 
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Mark D. M. Leiserson, Jason Fan, Anthony Cannistra, Inbar Fried, Tim Lim, Thomas Schaffner, Mark Crovella and Benjamin Hescott (2018).
A Multi-Species Functional Embedding Integrating Sequence and Network Structure.
In: Proceedings of RECOMB: Lecture Notes in Bioinformatics. Volume 10812. Paris, France. Published by Springer. Code and demo for this method are available at links below. doi:10.1007/978-3-319-89929-9
[Leiserson et al., 2017]
 
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Mark D. M. Leiserson, Jason Fan, Anthony Cannistra, Inbar Fried, Tim Lim, Thomas Schaffner, Mark Crovella and Benjamin Hescott (2017).
A Multi-Species Functional Embedding Integrating Sequence and Network Structure.
Technical Report. bioRxiv. Code and demo for this method are available at links below. doi:10.1101/229211
[Cao et al., 2013]
 
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Mengfei Cao, Hao Zhang, Jisoo Park, Noah Daniels, Mark Crovella, Lenore Cowen and Benjamin Hescott (2013).
Going the Distance for Protein Function Prediction: A New Distance Metric for Protein Interaction Networks.
In: PLOS One, 8(10):e76339. doi:10.1371/journal.pone.0076339