List of Faculty Publications

Below is a list of Faculty publications imported from PubMed or manually added. By default, publications are sorted by year with titles displayed in ascending alphabetical order.
Shortcuts: Wühr, Martin | Wingreen, Ned | Wieschaus, Eric | Troyanskaya, Olga | Tilghman, Shirley | Storey, John | Singh, Mona | Shvartsman, Stanislav | Shaevitz, Joshua | Rabinowitz, Joshua | Murphy, Coleen | Levine, Michael {Levine, Michael S.} | Gregor, Thomas | Botstein, David | Bialek, William | Ayroles, Julien | Andolfatto, Peter | Akey, Joshua

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Mutation
J. Zhou, Theesfeld, C. L., Yao, K., Chen, K. M., Wong, A. K., and Troyanskaya, O. G., “Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk.”, Nat Genet, vol. 50, no. 8, pp. 1171-1179, 2018.
J. Zhou, Park, C. Y., Theesfeld, C. L., Wong, A. K., Yuan, Y., Scheckel, C., Fak, J. J., Funk, J., Yao, K., Tajima, Y., Packer, A., Darnell, R. B., and Troyanskaya, O. G., “Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.”, Nat Genet, vol. 51, no. 6, pp. 973-980, 2019.
K. M. Chen, Cofer, E. M., Zhou, J., and Troyanskaya, O. G., “Selene: a PyTorch-based deep learning library for sequence data.”, Nat Methods, vol. 16, no. 4, pp. 315-318, 2019.
M. Costanzo, Baryshnikova, A., Bellay, J., Kim, Y., Spear, E. D., Sevier, C. S., Ding, H., L Y Koh, J., Toufighi, K., Mostafavi, S., Prinz, J., St Onge, R. P., VanderSluis, B., Makhnevych, T., Vizeacoumar, F. J., Alizadeh, S., Bahr, S., Brost, R. L., Chen, Y., Cokol, M., Deshpande, R., Li, Z., Lin, Z. - Y., Liang, W., Marback, M., Paw, J., San Luis, B. - J., Shuteriqi, E., Tong, A. Hin Yan, van Dyk, N., Wallace, I. M., Whitney, J. A., Weirauch, M. T., Zhong, G., Zhu, H., Houry, W. A., Brudno, M., Ragibizadeh, S., Papp, B., Pál, C., Roth, F. P., Giaever, G., Nislow, C., Troyanskaya, O. G., Bussey, H., Bader, G. D., Gingras, A. - C., Morris, Q. D., Kim, P. M., Kaiser, C. A., Myers, C. L., Andrews, B. J., and Boone, C., “The genetic landscape of a cell.”, Science, vol. 327, no. 5964, pp. 425-31, 2010.
A. Baryshnikova, Costanzo, M., Kim, Y., Ding, H., Koh, J., Toufighi, K., Youn, J. - Y., Ou, J., San Luis, B. - J., Bandyopadhyay, S., Hibbs, M., Hess, D., Gingras, A. - C., Bader, G. D., Troyanskaya, O. G., Brown, G. W., Andrews, B., Boone, C., and Myers, C. L., “Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.”, Nat Methods, vol. 7, no. 12, pp. 1017-24, 2010.
D. C. Hess, Myers, C. L., Huttenhower, C., Hibbs, M. A., Hayes, A. P., Paw, J., Clore, J. J., Mendoza, R. M., San Luis, B., Nislow, C., Giaever, G., Costanzo, M., Troyanskaya, O. G., and Caudy, A. A., “Computationally driven, quantitative experiments discover genes required for mitochondrial biogenesis.”, PLoS Genet, vol. 5, no. 3, p. e1000407, 2009.
Mutant Proteins
D. C. Hess, Myers, C. L., Huttenhower, C., Hibbs, M. A., Hayes, A. P., Paw, J., Clore, J. J., Mendoza, R. M., San Luis, B., Nislow, C., Giaever, G., Costanzo, M., Troyanskaya, O. G., and Caudy, A. A., “Computationally driven, quantitative experiments discover genes required for mitochondrial biogenesis.”, PLoS Genet, vol. 5, no. 3, p. e1000407, 2009.
Mutagenesis
K. M. Chen, Cofer, E. M., Zhou, J., and Troyanskaya, O. G., “Selene: a PyTorch-based deep learning library for sequence data.”, Nat Methods, vol. 16, no. 4, pp. 315-318, 2019.
A. Baryshnikova, Costanzo, M., Kim, Y., Ding, H., Koh, J., Toufighi, K., Youn, J. - Y., Ou, J., San Luis, B. - J., Bandyopadhyay, S., Hibbs, M., Hess, D., Gingras, A. - C., Bader, G. D., Troyanskaya, O. G., Brown, G. W., Andrews, B., Boone, C., and Myers, C. L., “Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.”, Nat Methods, vol. 7, no. 12, pp. 1017-24, 2010.
Multifactorial Inheritance
B. Haarer, Viggiano, S., Hibbs, M. A., Troyanskaya, O. G., and Amberg, D. C., “Modeling complex genetic interactions in a simple eukaryotic genome: actin displays a rich spectrum of complex haploinsufficiencies.”, Genes Dev, vol. 21, no. 2, pp. 148-59, 2007.
Monocytes
C. J. Nirschl, Suárez-Fariñas, M., Izar, B., Prakadan, S., Dannenfelser, R., Tirosh, I., Liu, Y., Zhu, Q., K Devi, S. P., Carroll, S. L., Chau, D., Rezaee, M., Kim, T. - G., Huang, R., Fuentes-Duculan, J., Song-Zhao, G. X., Gulati, N., Lowes, M. A., King, S. L., Quintana, F. J., Lee, Y. -suk, Krueger, J. G., Sarin, K. Y., Yoon, C. H., Garraway, L., Regev, iv, A., Shalek, A. K., Troyanskaya, O. G., and Anandasabapathy, N., “IFNγ-Dependent Tissue-Immune Homeostasis Is Co-opted in the Tumor Microenvironment.”, Cell, vol. 170, no. 1, pp. 127-141.e15, 2017.
Molecular Sequence Data
O. G. Troyanskaya, Arbell, O., Koren, Y., Landau, G. M., and Bolshoy, A., “Sequence complexity profiles of prokaryotic genomic sequences: a fast algorithm for calculating linguistic complexity.”, Bioinformatics, vol. 18, no. 5, pp. 679-88, 2002.
Molecular Sequence Annotation
A. A. Caudy, Guan, Y., Jia, Y., Hansen, C., DeSevo, C., Hayes, A. P., Agee, J., Alvarez-Dominguez, J. R., Arellano, H., Barrett, D., Bauerle, C., Bisaria, N., Bradley, P. H., J Breunig, S., Bush, E., Cappel, D., Capra, E., Chen, W., Clore, J., Combs, P. A., Doucette, C., Demuren, O., Fellowes, P., Freeman, S., Frenkel, E., Gadala-Maria, D., Gawande, R., Glass, D., Grossberg, S., Gupta, A., Hammonds-Odie, L., Hoisos, A., Hsi, J., Hsu, Y. - H. Huang, Inukai, S., Karczewski, K. J., Ke, X., Kojima, M., Leachman, S., Lieber, D., Liebowitz, A., Liu, J., Liu, Y., Martin, T., Mena, J., Mendoza, R., Myhrvold, C., Millian, C., Pfau, S., Raj, S., Rich, M., Rokicki, J., Rounds, W., Salazar, M., Salesi, M., Sharma, R., Silverman, S., Singer, C., Sinha, S., Staller, M., Stern, P., Tang, H., Weeks, S., Weidmann, M., Wolf, A., Young, C., Yuan, J., Crutchfield, C., McClean, M., Murphy, C. T., Llinás, M., Botstein, D., Troyanskaya, O. G., and Dunham, M. J., “A new system for comparative functional genomics of Saccharomyces yeasts.”, Genetics, vol. 195, no. 1, pp. 275-87, 2013.
Molecular Chaperones
C. L. Myers, Robson, D., Wible, A., Hibbs, M. A., Chiriac, C., Theesfeld, C. L., Dolinski, K., and Troyanskaya, O. G., “Discovery of biological networks from diverse functional genomic data.”, Genome Biol, vol. 6, no. 13, p. R114, 2005.
Molecular Biology
O. G. Troyanskaya, “Putting the 'bio' into bioinformatics.”, Genome Biol, vol. 6, no. 10, p. 351, 2005.
Models, Statistical
C. Huttenhower and Troyanskaya, O. G., “Bayesian data integration: a functional perspective.”, Comput Syst Bioinformatics Conf, pp. 341-51, 2006.
M. A. Hibbs, Dirksen, N. C., Li, K., and Troyanskaya, O. G., “Visualization methods for statistical analysis of microarray clusters.”, BMC Bioinformatics, vol. 6, p. 115, 2005.
J. Zhou and Troyanskaya, O. G., “Global quantitative modeling of chromatin factor interactions.”, PLoS Comput Biol, vol. 10, no. 3, p. e1003525, 2014.
Y. Guan, Myers, C. L., Lu, R., Lemischka, I. R., Bult, C. J., and Troyanskaya, O. G., “A genomewide functional network for the laboratory mouse.”, PLoS Comput Biol, vol. 4, no. 9, p. e1000165, 2008.
K. M. Chen, Cofer, E. M., Zhou, J., and Troyanskaya, O. G., “Selene: a PyTorch-based deep learning library for sequence data.”, Nat Methods, vol. 16, no. 4, pp. 315-318, 2019.
C. Y. Park, Wong, A. K., Greene, C. S., Rowland, J., Guan, Y., Bongo, L. A., Burdine, R. D., and Troyanskaya, O. G., “Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.”, PLoS Comput Biol, vol. 9, no. 3, p. e1002957, 2013.
Y. -suk Lee, Krishnan, A., Zhu, Q., and Troyanskaya, O. G., “Ontology-aware classification of tissue and cell-type signals in gene expression profiles across platforms and technologies.”, Bioinformatics, vol. 29, no. 23, pp. 3036-44, 2013.
O. G. Troyanskaya, Garber, M. E., Brown, P. O., Botstein, D., and Altman, R. B., “Nonparametric methods for identifying differentially expressed genes in microarray data.”, Bioinformatics, vol. 18, no. 11, pp. 1454-61, 2002.
Models, Genetic
M. A. Hibbs, Dirksen, N. C., Li, K., and Troyanskaya, O. G., “Visualization methods for statistical analysis of microarray clusters.”, BMC Bioinformatics, vol. 6, p. 115, 2005.
M. D. Chikina, Huttenhower, C., Murphy, C. T., and Troyanskaya, O. G., “Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans.”, PLoS Comput Biol, vol. 5, no. 6, p. e1000417, 2009.
J. Zhou, Theesfeld, C. L., Yao, K., Chen, K. M., Wong, A. K., and Troyanskaya, O. G., “Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk.”, Nat Genet, vol. 50, no. 8, pp. 1171-1179, 2018.
O. G. Troyanskaya, Arbell, O., Koren, Y., Landau, G. M., and Bolshoy, A., “Sequence complexity profiles of prokaryotic genomic sequences: a fast algorithm for calculating linguistic complexity.”, Bioinformatics, vol. 18, no. 5, pp. 679-88, 2002.
O. G. Troyanskaya, Garber, M. E., Brown, P. O., Botstein, D., and Altman, R. B., “Nonparametric methods for identifying differentially expressed genes in microarray data.”, Bioinformatics, vol. 18, no. 11, pp. 1454-61, 2002.
Models, Biological
O. G. Troyanskaya, “Integrated analysis of microarray results.”, Methods Mol Biol, vol. 382, pp. 429-37, 2007.
Y. Guan, Gorenshteyn, D., Burmeister, M., Wong, A. K., Schimenti, J. C., Handel, M. Ann, Bult, C. J., Hibbs, M. A., and Troyanskaya, O. G., “Tissue-specific functional networks for prioritizing phenotype and disease genes.”, PLoS Comput Biol, vol. 8, no. 9, p. e1002694, 2012.
C. Y. Park, Wong, A. K., Greene, C. S., Rowland, J., Guan, Y., Bongo, L. A., Burdine, R. D., and Troyanskaya, O. G., “Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.”, PLoS Comput Biol, vol. 9, no. 3, p. e1002957, 2013.
O. G. Troyanskaya, “Putting microarrays in a context: integrated analysis of diverse biological data.”, Brief Bioinform, vol. 6, no. 1, pp. 34-43, 2005.
E. M. Airoldi, Huttenhower, C., Gresham, D., Lu, C., Caudy, A. A., Dunham, M. J., Broach, J. R., Botstein, D., and Troyanskaya, O. G., “Predicting cellular growth from gene expression signatures.”, PLoS Comput Biol, vol. 5, no. 1, p. e1000257, 2009.
M. A. Hibbs, Myers, C. L., Huttenhower, C., Hess, D. C., Li, K., Caudy, A. A., and Troyanskaya, O. G., “Directing experimental biology: a case study in mitochondrial biogenesis.”, PLoS Comput Biol, vol. 5, no. 3, p. e1000322, 2009.
F. Markowetz, Kostka, D., Troyanskaya, O. G., and Spang, R., “Nested effects models for high-dimensional phenotyping screens.”, Bioinformatics, vol. 23, no. 13, pp. i305-12, 2007.
M. J. Brauer, Huttenhower, C., Airoldi, E. M., Rosenstein, R., Matese, J. C., Gresham, D., Boer, V. M., Troyanskaya, O. G., and Botstein, D., “Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast.”, Mol Biol Cell, vol. 19, no. 1, pp. 352-67, 2008.
Mitosis
Z. Barutcuoglu, Schapire, R. E., and Troyanskaya, O. G., “Hierarchical multi-label prediction of gene function.”, Bioinformatics, vol. 22, no. 7, pp. 830-6, 2006.
Mitochondrial Proteins
D. C. Hess, Myers, C. L., Huttenhower, C., Hibbs, M. A., Hayes, A. P., Paw, J., Clore, J. J., Mendoza, R. M., San Luis, B., Nislow, C., Giaever, G., Costanzo, M., Troyanskaya, O. G., and Caudy, A. A., “Computationally driven, quantitative experiments discover genes required for mitochondrial biogenesis.”, PLoS Genet, vol. 5, no. 3, p. e1000407, 2009.
Y. Guan, Myers, C. L., Hess, D. C., Barutcuoglu, Z., Caudy, A. A., and Troyanskaya, O. G., “Predicting gene function in a hierarchical context with an ensemble of classifiers.”, Genome Biol, vol. 9 Suppl 1, p. S3, 2008.
M. A. Hibbs, Myers, C. L., Huttenhower, C., Hess, D. C., Li, K., Caudy, A. A., and Troyanskaya, O. G., “Directing experimental biology: a case study in mitochondrial biogenesis.”, PLoS Comput Biol, vol. 5, no. 3, p. e1000322, 2009.
Mitochondria
D. C. Hess, Myers, C. L., Huttenhower, C., Hibbs, M. A., Hayes, A. P., Paw, J., Clore, J. J., Mendoza, R. M., San Luis, B., Nislow, C., Giaever, G., Costanzo, M., Troyanskaya, O. G., and Caudy, A. A., “Computationally driven, quantitative experiments discover genes required for mitochondrial biogenesis.”, PLoS Genet, vol. 5, no. 3, p. e1000407, 2009.
C. Huttenhower, Hibbs, M. A., Myers, C. L., Caudy, A. A., Hess, D. C., and Troyanskaya, O. G., “The impact of incomplete knowledge on evaluation: an experimental benchmark for protein function prediction.”, Bioinformatics, vol. 25, no. 18, pp. 2404-10, 2009.
M. A. Hibbs, Myers, C. L., Huttenhower, C., Hess, D. C., Li, K., Caudy, A. A., and Troyanskaya, O. G., “Directing experimental biology: a case study in mitochondrial biogenesis.”, PLoS Comput Biol, vol. 5, no. 3, p. e1000322, 2009.
Middle Aged
S. P. Bohen, Troyanskaya, O. G., Alter, O., Warnke, R., Botstein, D., Brown, P. O., and Levy, R., “Variation in gene expression patterns in follicular lymphoma and the response to rituximab.”, Proc Natl Acad Sci U S A, vol. 100, no. 4, pp. 1926-30, 2003.
M. L. Whitfield, Finlay, D. R., Murray, J. Isaac, Troyanskaya, O. G., Chi, J. - T., Pergamenschikov, A., McCalmont, T. H., Brown, P. O., Botstein, D., and M Connolly, K., “Systemic and cell type-specific gene expression patterns in scleroderma skin.”, Proc Natl Acad Sci U S A, vol. 100, no. 21, pp. 12319-24, 2003.
Microscopy, Fluorescence
C. Huttenhower, Haley, E. M., Hibbs, M. A., Dumeaux, V., Barrett, D. R., Coller, H. A., and Troyanskaya, O. G., “Exploring the human genome with functional maps.”, Genome Res, vol. 19, no. 6, pp. 1093-106, 2009.
MicroRNAs
M. D. Chikina, Huttenhower, C., Murphy, C. T., and Troyanskaya, O. G., “Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans.”, PLoS Comput Biol, vol. 5, no. 6, p. e1000417, 2009.
Microfilament Proteins
B. Haarer, Viggiano, S., Hibbs, M. A., Troyanskaya, O. G., and Amberg, D. C., “Modeling complex genetic interactions in a simple eukaryotic genome: actin displays a rich spectrum of complex haploinsufficiencies.”, Genes Dev, vol. 21, no. 2, pp. 148-59, 2007.
Mice, Transgenic
Y. Guan, Ackert-Bicknell, C. L., Kell, B., Troyanskaya, O. G., and Hibbs, M. A., “Functional genomics complements quantitative genetics in identifying disease-gene associations.”, PLoS Comput Biol, vol. 6, no. 11, p. e1000991, 2010.
Mice, Knockout
Y. Guan, Myers, C. L., Lu, R., Lemischka, I. R., Bult, C. J., and Troyanskaya, O. G., “A genomewide functional network for the laboratory mouse.”, PLoS Comput Biol, vol. 4, no. 9, p. e1000165, 2008.
Mice
A. K. Wong, Park, C. Y., Greene, C. S., Bongo, L. A., Guan, Y., and Troyanskaya, O. G., “IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.”, Nucleic Acids Res, vol. 40, no. Web Server issue, pp. W484-90, 2012.
C. J. Nirschl, Suárez-Fariñas, M., Izar, B., Prakadan, S., Dannenfelser, R., Tirosh, I., Liu, Y., Zhu, Q., K Devi, S. P., Carroll, S. L., Chau, D., Rezaee, M., Kim, T. - G., Huang, R., Fuentes-Duculan, J., Song-Zhao, G. X., Gulati, N., Lowes, M. A., King, S. L., Quintana, F. J., Lee, Y. -suk, Krueger, J. G., Sarin, K. Y., Yoon, C. H., Garraway, L., Regev, iv, A., Shalek, A. K., Troyanskaya, O. G., and Anandasabapathy, N., “IFNγ-Dependent Tissue-Immune Homeostasis Is Co-opted in the Tumor Microenvironment.”, Cell, vol. 170, no. 1, pp. 127-141.e15, 2017.
Y. Guan, Gorenshteyn, D., Burmeister, M., Wong, A. K., Schimenti, J. C., Handel, M. Ann, Bult, C. J., Hibbs, M. A., and Troyanskaya, O. G., “Tissue-specific functional networks for prioritizing phenotype and disease genes.”, PLoS Comput Biol, vol. 8, no. 9, p. e1002694, 2012.
Y. Guan, Myers, C. L., Lu, R., Lemischka, I. R., Bult, C. J., and Troyanskaya, O. G., “A genomewide functional network for the laboratory mouse.”, PLoS Comput Biol, vol. 4, no. 9, p. e1000165, 2008.
R. Lu, Markowetz, F., Unwin, R. D., Leek, J. T., Airoldi, E. M., MacArthur, B. D., Lachmann, A., Rozov, R., Ma'ayan, A., Boyer, L. A., Troyanskaya, O. G., Whetton, A. D., and Lemischka, I. R., “Systems-level dynamic analyses of fate change in murine embryonic stem cells.”, Nature, vol. 462, no. 7271, pp. 358-62, 2009.
C. Y. Park, Wong, A. K., Greene, C. S., Rowland, J., Guan, Y., Bongo, L. A., Burdine, R. D., and Troyanskaya, O. G., “Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.”, PLoS Comput Biol, vol. 9, no. 3, p. e1002957, 2013.
Y. Guan, Ackert-Bicknell, C. L., Kell, B., Troyanskaya, O. G., and Hibbs, M. A., “Functional genomics complements quantitative genetics in identifying disease-gene associations.”, PLoS Comput Biol, vol. 6, no. 11, p. e1000991, 2010.
Y. Guan, Myers, C. L., Hess, D. C., Barutcuoglu, Z., Caudy, A. A., and Troyanskaya, O. G., “Predicting gene function in a hierarchical context with an ensemble of classifiers.”, Genome Biol, vol. 9 Suppl 1, p. S3, 2008.
C. S. Greene and Troyanskaya, O. G., “PILGRM: an interactive data-driven discovery platform for expert biologists.”, Nucleic Acids Res, vol. 39, no. Web Server issue, pp. W368-74, 2011.
W. Ju, Greene, C. S., Eichinger, F., Nair, V., Hodgin, J. B., Bitzer, M., Lee, Y. -suk, Zhu, Q., Kehata, M., Li, M., Jiang, S., Rastaldi, M. Pia, Cohen, C. D., Troyanskaya, O. G., and Kretzler, M., “Defining cell-type specificity at the transcriptional level in human disease.”, Genome Res, vol. 23, no. 11, pp. 1862-73, 2013.
L. Peña-Castillo, Tasan, M., Myers, C. L., Lee, H., Joshi, T., Zhang, C., Guan, Y., Leone, M., Pagnani, A., Kim, W. Kyu, Krumpelman, C., Tian, W., Obozinski, G., Qi, Y., Mostafavi, S., Lin, G. Ning, Berriz, G. F., Gibbons, F. D., Lanckriet, G., Qiu, J., Grant, C., Barutcuoglu, Z., Hill, D. P., Warde-Farley, D., Grouios, C., Ray, D., Blake, J. A., Deng, M., Jordan, M. I., Noble, W. S., Morris, Q., Klein-Seetharaman, J., Bar-Joseph, iv, Z., Chen, T., Sun, F., Troyanskaya, O. G., Marcotte, E. M., Xu, D., Hughes, T. R., and Roth, F. P., “A critical assessment of Mus musculus gene function prediction using integrated genomic evidence.”, Genome Biol, vol. 9 Suppl 1, p. S2, 2008.
F. Markowetz, Mulder, K. W., Airoldi, E. M., Lemischka, I. R., and Troyanskaya, O. G., “Mapping dynamic histone acetylation patterns to gene expression in nanog-depleted murine embryonic stem cells.”, PLoS Comput Biol, vol. 6, no. 12, p. e1001034, 2010.
Methods
J. A. Brown, Sherlock, G., Myers, C. L., Burrows, N. M., Deng, C., H Wu, I., McCann, K. E., Troyanskaya, O. G., and J Brown, M., “Global analysis of gene function in yeast by quantitative phenotypic profiling.”, Mol Syst Biol, vol. 2, p. 2006.0001, 2006.
Metabolomics
P. H. Bradley, Brauer, M. J., Rabinowitz, J. D., and Troyanskaya, O. G., “Coordinated concentration changes of transcripts and metabolites in Saccharomyces cerevisiae.”, PLoS Comput Biol, vol. 5, no. 1, p. e1000270, 2009.
Metabolic Networks and Pathways
F. Markowetz and Troyanskaya, O. G., “Computational identification of cellular networks and pathways.”, Mol Biosyst, vol. 3, no. 7, pp. 478-82, 2007.
C. Huttenhower, Mehmood, S. O., and Troyanskaya, O. G., “Graphle: Interactive exploration of large, dense graphs.”, BMC Bioinformatics, vol. 10, p. 417, 2009.
C. Y. Park, Hess, D. C., Huttenhower, C., and Troyanskaya, O. G., “Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.”, PLoS Comput Biol, vol. 6, no. 11, p. e1001009, 2010.
M. Costanzo, Baryshnikova, A., Bellay, J., Kim, Y., Spear, E. D., Sevier, C. S., Ding, H., L Y Koh, J., Toufighi, K., Mostafavi, S., Prinz, J., St Onge, R. P., VanderSluis, B., Makhnevych, T., Vizeacoumar, F. J., Alizadeh, S., Bahr, S., Brost, R. L., Chen, Y., Cokol, M., Deshpande, R., Li, Z., Lin, Z. - Y., Liang, W., Marback, M., Paw, J., San Luis, B. - J., Shuteriqi, E., Tong, A. Hin Yan, van Dyk, N., Wallace, I. M., Whitney, J. A., Weirauch, M. T., Zhong, G., Zhu, H., Houry, W. A., Brudno, M., Ragibizadeh, S., Papp, B., Pál, C., Roth, F. P., Giaever, G., Nislow, C., Troyanskaya, O. G., Bussey, H., Bader, G. D., Gingras, A. - C., Morris, Q. D., Kim, P. M., Kaiser, C. A., Myers, C. L., Andrews, B. J., and Boone, C., “The genetic landscape of a cell.”, Science, vol. 327, no. 5964, pp. 425-31, 2010.
C. L. Myers, Chiriac, C., and Troyanskaya, O. G., “Discovering biological networks from diverse functional genomic data.”, Methods Mol Biol, vol. 563, pp. 157-75, 2009.
Melanoma
C. J. Nirschl, Suárez-Fariñas, M., Izar, B., Prakadan, S., Dannenfelser, R., Tirosh, I., Liu, Y., Zhu, Q., K Devi, S. P., Carroll, S. L., Chau, D., Rezaee, M., Kim, T. - G., Huang, R., Fuentes-Duculan, J., Song-Zhao, G. X., Gulati, N., Lowes, M. A., King, S. L., Quintana, F. J., Lee, Y. -suk, Krueger, J. G., Sarin, K. Y., Yoon, C. H., Garraway, L., Regev, iv, A., Shalek, A. K., Troyanskaya, O. G., and Anandasabapathy, N., “IFNγ-Dependent Tissue-Immune Homeostasis Is Co-opted in the Tumor Microenvironment.”, Cell, vol. 170, no. 1, pp. 127-141.e15, 2017.
MAP Kinase Signaling System
Y. Guan, Myers, C. L., Lu, R., Lemischka, I. R., Bult, C. J., and Troyanskaya, O. G., “A genomewide functional network for the laboratory mouse.”, PLoS Comput Biol, vol. 4, no. 9, p. e1000165, 2008.
Mammography
V. N. Kristensen, Vaske, C. J., Ursini-Siegel, J., Van Loo, P., Nordgard, S. H., Sachidanandam, R., Sørlie, T., Wärnberg, F., Haakensen, V. D., Helland, Å., Naume, B., Perou, C. M., Haussler, D., Troyanskaya, O. G., and Børresen-Dale, A. - L., “Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling.”, Proc Natl Acad Sci U S A, vol. 109, no. 8, pp. 2802-7, 2012.
Male
S. P. Bohen, Troyanskaya, O. G., Alter, O., Warnke, R., Botstein, D., Brown, P. O., and Levy, R., “Variation in gene expression patterns in follicular lymphoma and the response to rituximab.”, Proc Natl Acad Sci U S A, vol. 100, no. 4, pp. 1926-30, 2003.
M. L. Whitfield, Finlay, D. R., Murray, J. Isaac, Troyanskaya, O. G., Chi, J. - T., Pergamenschikov, A., McCalmont, T. H., Brown, P. O., Botstein, D., and M Connolly, K., “Systemic and cell type-specific gene expression patterns in scleroderma skin.”, Proc Natl Acad Sci U S A, vol. 100, no. 21, pp. 12319-24, 2003.
Machine Learning
J. Zhou, Schor, I. E., Yao, V., Theesfeld, C. L., Marco-Ferreres, R., Tadych, A., Furlong, E. E. M., and Troyanskaya, O. G., “Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development.”, PLoS Genet, vol. 15, no. 9, p. e1008382, 2019.