Computational Biology

[Youssef et al., 2024]
 
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Ahmed Youssef, Indranil Paul, Mark Crovella and Andrew Emili (2024).
DESP: Demixing Cell State Profiles from Dynamic Bulk Molecular Measurements.
In: Cell Reports Methods, . doi:10.1016/j.crmeth.2024.100729
[Kewalramani et al., 2023]
 
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Neal Kewalramani, Andrew Emili and Mark Crovella (2023).
State-of-the-Art Computational Methods to Predict Protein-Protein Interactions with High Accuracy and Coverage.
In: Proteomics, (e2200292). doi:10.1002/pmic.202200292
[Youssef et al., 2023]
 
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Ahmed Youssef, Fei Bian, Pierre Havugimana, Mark Crovella and Andrew Emili (2023).
Dynamic Remodeling of Escherichia coli Interactome in Response to Environmental Perturbations.
In: Proteomics, . doi:10.1002/pmic.202200404
[Youssef et al., 2023]
 
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Ahmed Youssef, Indranil Paul, Mark Crovella and Andrew Emili (2023).
DESP: Demixing Cell State Profiles from Dynamic Bulk Molecular Measurements.
In: bioRxiv, . doi:10.1101/2023.01.19.524460
[Jung et al., 2022]
 
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J. Jung, M. Guo, M. Crovella, J. G. McDaniel, K. M. Warkentin (2022).
Frog embryos use multiple levels of temporal pattern in risk assessment for vibration-cued hatching.
In: Animal Cognition, . doi:10.1007/s10071-022-01634-4
[Law et al., 2021]
 
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Jeffrey N. Law, Kyle Akers, Nure Tasnina, Catherine M. Della-Santina, Shay Deutsch, Meghana Kshirsagar, Judith Klein-Seetharaman, Mark Crovella, Padmavathy Rajagopalan, Simon Kasif, T. M. Murali (2021).
Interpretable Network Propagation with Application to Expanding the Repertoire of Human Proteins that Interact with SARS-CoV-2.
In: GigaScience, 10(12). doi:10.1093/gigascience/giab082
[Lancour et al., 2020]
 
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Dan Lancour, Josee Dupuis, Richard Mayeux, Jonathan Haines, Margaret Pericak-Vance, Gerard Schellenberg, Mark Crovella, Lindsay Farrer and Simon Kasif (2020).
Analysis of Brain Region-Specific Co-Expression Networks Reveals Clustering of Established and Novel Genes Associated with Alzheimer Disease.
In: Alzheimer's Research and Therapy, 12. doi:10.1186/s13195-020-00674-7
[Fan et al., 2020]
 
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Jason Fan, Xuan Cindy Li, Mark Crovella, Mark D. M. Leiserson (2020).
Matrix (Factorization) Reloaded: Flexible Methods for Imputing Genetic Interactions with Cross-Species and Side Information.
In: Proceedings of the 19th European Conference on Computational Biology. Online. Also appears in OUP Bioinformatics Special Issue, 2020. doi:10.1093/bioinformatics/btaa818
[Law et al., 2020]
 
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Jeffrey N. Law, Nure Tasnina, Meghana Kshirsagar, Judith Klein-Seetharaman, Mark Crovella, Padmavathy Rajagopalan, Simon Kasif, T. M. Murali (2020).
Identifying Human Interactors of SARS-CoV-2 Proteins and Drug Targets for COVID-19 using Network-Based Label Propagation.
Technical Report Nr. arXiv:2006.01968.
[Ramirez et al., 2020]
 
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Alfred Ramirez, Simon Dankel, Bashir Rastegarpanah, Weikang Cai, Ruidan Xue, Mark Crovella, Yu-Hua Tseng, C. Ronald Kahn and Simon Kasif (2020).
Single-Cell Transcriptional Networks in Differentiating Preadipocytes Suggest Drivers Associated with Tissue Heterogeneity.
In: Nature Communications, 11. doi:10.1038/s41467-020-16019-9
[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, 47(9). doi:10.1186/s13195-020-00674-7
[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