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

Filters: Author is Troyanskaya, Olga G  [Clear All Filters]
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Genome, Fungal
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.
C. Huttenhower, Myers, C. L., Hibbs, M. A., and Troyanskaya, O. G., Computational analysis of the yeast proteome: understanding and exploiting functional specificity in genomic data., Methods Mol Biol, vol. 548, pp. 273-93, 2009.
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.
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. 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.
Y. Guan, Dunham, M. J., and Troyanskaya, O. G., Functional analysis of gene duplications in Saccharomyces cerevisiae., Genetics, vol. 175, no. 2, pp. 933-43, 2007.
Genome-Wide Association Study
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.
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.
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.
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.
A. Krishnan, Zhang, R., Yao, V., Theesfeld, C. L., Wong, A. K., Tadych, A., Volfovsky, N., Packer, A., Lash, A., and Troyanskaya, O. G., Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder., Nat Neurosci, vol. 19, no. 11, pp. 1454-1462, 2016.
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.
Genomics
F. Markowetz and Troyanskaya, O. G., Computational identification of cellular networks and pathways., Mol Biosyst, vol. 3, no. 7, pp. 478-82, 2007.
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.
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.
C. L. Myers, Barrett, D. R., Hibbs, M. A., Huttenhower, C., and Troyanskaya, O. G., Finding function: evaluation methods for functional genomic data., BMC Genomics, vol. 7, p. 187, 2006.
C. Huttenhower, Myers, C. L., Hibbs, M. A., and Troyanskaya, O. G., Computational analysis of the yeast proteome: understanding and exploiting functional specificity in genomic data., Methods Mol Biol, vol. 548, pp. 273-93, 2009.
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.
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.
C. S. Greene and Troyanskaya, O. G., Accurate evaluation and analysis of functional genomics data and methods., Ann N Y Acad Sci, vol. 1260, pp. 95-100, 2012.
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.
M. D. Chikina and Troyanskaya, O. G., An effective statistical evaluation of ChIPseq dataset similarity., Bioinformatics, vol. 28, no. 5, pp. 607-13, 2012.
C. Huttenhower, Schroeder, M., Chikina, M. D., and Troyanskaya, O. G., The Sleipnir library for computational functional genomics., Bioinformatics, vol. 24, no. 13, pp. 1559-61, 2008.
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.
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.
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.
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. Pop, Huttenhower, C., Iyer-Pascuzzi, A., Benfey, P. N., and Troyanskaya, O. G., Integrated functional networks of process, tissue, and developmental stage specific interactions in Arabidopsis thaliana., BMC Syst Biol, vol. 4, p. 180, 2010.
Y. -suk Lee, Wong, A. K., Tadych, A., Hartmann, B. M., Park, C. Y., DeJesus, V. A., Ramos, I., Zaslavsky, E., Sealfon, S. C., and Troyanskaya, O. G., Interpretation of an individual functional genomics experiment guided by massive public data., Nat Methods, vol. 15, no. 12, pp. 1049-1052, 2018.
Humans
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.
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.
M. D. Chikina and Troyanskaya, O. G., Accurate quantification of functional analogy among close homologs., PLoS Comput Biol, vol. 7, no. 2, p. e1001074, 2011.
D. Gorenshteyn, Zaslavsky, E., Fribourg, M., Park, C. Y., Wong, A. K., Tadych, A., Hartmann, B. M., Albrecht, R. A., García-Sastre, A., Kleinstein, S. H., Troyanskaya, O. G., and Sealfon, S. C., Interactive Big Data Resource to Elucidate Human Immune Pathways and Diseases., Immunity, vol. 43, no. 3, pp. 605-14, 2015.
C. S. Greene and Troyanskaya, O. G., Integrative systems biology for data-driven knowledge discovery., Semin Nephrol, vol. 30, no. 5, pp. 443-54, 2010.
X. Chen, Leung, S. Y., Yuen, S. T., Chu, K. - M., Ji, J., Li, R., S Y Chan, A., Law, S., Troyanskaya, O. G., Wong, J., So, S., Botstein, D., and Brown, P. O., Variation in gene expression patterns in human gastric cancers., Mol Biol Cell, vol. 14, no. 8, pp. 3208-15, 2003.
O. G. Troyanskaya, Integrated analysis of microarray results., Methods Mol Biol, vol. 382, pp. 429-37, 2007.
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.
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.
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.
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.
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.
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.
J. - T. Chi, Chang, H. Y., Haraldsen, G., Jahnsen, F. L., Troyanskaya, O. G., Chang, D. S., Wang, Z., Rockson, S. G., van de Rijn, M., Botstein, D., and Brown, P. O., Endothelial cell diversity revealed by global expression profiling., Proc Natl Acad Sci U S A, vol. 100, no. 19, pp. 10623-8, 2003.
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.
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.
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.
C. S. Greene and Troyanskaya, O. G., Chapter 2: Data-driven view of disease biology., PLoS Comput Biol, vol. 8, no. 12, p. e1002816, 2012.
O. G. Troyanskaya, Putting microarrays in a context: integrated analysis of diverse biological data., Brief Bioinform, vol. 6, no. 1, pp. 34-43, 2005.
A. Krishnan, Zhang, R., Yao, V., Theesfeld, C. L., Wong, A. K., Tadych, A., Volfovsky, N., Packer, A., Lash, A., and Troyanskaya, O. G., Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder., Nat Neurosci, vol. 19, no. 11, pp. 1454-1462, 2016.
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. 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, 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.
S. Y. Leung, Chen, X., Chu, K. M., Yuen, S. T., Mathy, J., Ji, J., S Y Chan, A., Li, R., Law, S., Troyanskaya, O. G., Tu, I. - P., Wong, J., So, S., Botstein, D., and Brown, P. O., Phospholipase A2 group IIA expression in gastric adenocarcinoma is associated with prolonged survival and less frequent metastasis., Proc Natl Acad Sci U S A, vol. 99, no. 25, pp. 16203-8, 2002.
C. L. Myers, Chen, X., and Troyanskaya, O. G., Visualization-based discovery and analysis of genomic aberrations in microarray data., BMC Bioinformatics, vol. 6, p. 146, 2005.
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.
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.
Y. -suk Lee, Wong, A. K., Tadych, A., Hartmann, B. M., Park, C. Y., DeJesus, V. A., Ramos, I., Zaslavsky, E., Sealfon, S. C., and Troyanskaya, O. G., Interpretation of an individual functional genomics experiment guided by massive public data., Nat Methods, vol. 15, no. 12, pp. 1049-1052, 2018.
Information Storage and Retrieval
C. Huttenhower, Hibbs, M., Myers, C., and Troyanskaya, O. G., A scalable method for integration and functional analysis of multiple microarray datasets., Bioinformatics, vol. 22, no. 23, pp. 2890-7, 2006.
M. A. Hibbs, Hess, D. C., Myers, C. L., Huttenhower, C., Li, K., and Troyanskaya, O. G., Exploring the functional landscape of gene expression: directed search of large microarray compendia., Bioinformatics, vol. 23, no. 20, pp. 2692-9, 2007.
O. G. Troyanskaya, Integrated analysis of microarray results., Methods Mol Biol, vol. 382, pp. 429-37, 2007.
C. L. Myers and Troyanskaya, O. G., Context-sensitive data integration and prediction of biological networks., Bioinformatics, vol. 23, no. 17, pp. 2322-30, 2007.
R. S. G. Sealfon, Hibbs, M. A., Huttenhower, C., Myers, C. L., and Troyanskaya, O. G., GOLEM: an interactive graph-based gene-ontology navigation and analysis tool., BMC Bioinformatics, vol. 7, p. 443, 2006.
O. G. Troyanskaya, Putting microarrays in a context: integrated analysis of diverse biological data., Brief Bioinform, vol. 6, no. 1, pp. 34-43, 2005.
C. Huttenhower, Schroeder, M., Chikina, M. D., and Troyanskaya, O. G., The Sleipnir library for computational functional genomics., Bioinformatics, vol. 24, no. 13, pp. 1559-61, 2008.
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.
Lysosome-Associated Membrane Glycoproteins
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.
Metabolic Networks and Pathways
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.
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.
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. Huttenhower, Mehmood, S. O., and Troyanskaya, O. G., Graphle: Interactive exploration of large, dense graphs., BMC Bioinformatics, vol. 10, p. 417, 2009.
F. Markowetz and Troyanskaya, O. G., Computational identification of cellular networks and pathways., Mol Biosyst, vol. 3, no. 7, pp. 478-82, 2007.
Mice
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.
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.
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.
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.
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.
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.
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. 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, 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.
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.
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. 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.
Models, Biological
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.
O. G. Troyanskaya, Integrated analysis of microarray results., Methods Mol Biol, vol. 382, pp. 429-37, 2007.
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.
O. G. Troyanskaya, Putting microarrays in a context: integrated analysis of diverse biological data., Brief Bioinform, vol. 6, no. 1, pp. 34-43, 2005.
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.
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.
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.
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.
Models, Statistical
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.
J. Zhou and Troyanskaya, O. G., Global quantitative modeling of chromatin factor interactions., PLoS Comput Biol, vol. 10, no. 3, p. e1003525, 2014.
C. Huttenhower and Troyanskaya, O. G., Bayesian data integration: a functional perspective., Comput Syst Bioinformatics Conf, pp. 341-51, 2006.
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.
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.
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.
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.
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.
Molecular Biology
O. G. Troyanskaya, Putting the 'bio' into bioinformatics., Genome Biol, vol. 6, no. 10, p. 351, 2005.
Mutation
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.
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.
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.
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.
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.
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.

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