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: Keyword is Cluster Analysis  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Cluster Analysis
M. M. Klosinska, Crutchfield, C. A., Bradley, P. H., Rabinowitz, J. D., and Broach, J. R., Yeast cells can access distinct quiescent states., Genes Dev, vol. 25, no. 4, pp. 336-49, 2011.
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.
T. O. Nielsen, Hsu, F. D., O'Connell, J. X., C Gilks, B., Sorensen, P. H. B., Linn, S., West, R. B., Liu, C. Long, Botstein, D., Brown, P. O., and van de Rijn, M., Tissue microarray validation of epidermal growth factor receptor and SALL2 in synovial sarcoma with comparison to tumors of similar histology., Am J Pathol, vol. 163, no. 4, pp. 1449-56, 2003.
P. Jiang and Singh, M., SPICi: a fast clustering algorithm for large biological networks., Bioinformatics, vol. 26, no. 8, pp. 1105-11, 2010.
C. Lu, Brauer, M. J., and Botstein, D., Slow growth induces heat-shock resistance in normal and respiratory-deficient yeast., Mol Biol Cell, vol. 20, no. 3, pp. 891-903, 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.
Y. Pritykin and Singh, M., Simple topological features reflect dynamics and modularity in protein interaction networks., PLoS Comput Biol, vol. 9, no. 10, p. e1003243, 2013.
M. L. Skoge, Endres, R. G., and Wingreen, N. S., Receptor-receptor coupling in bacterial chemotaxis: evidence for strongly coupled clusters., Biophys J, vol. 90, no. 12, pp. 4317-26, 2006.
P. A. Gibney, Hickman, M. J., Bradley, P. H., Matese, J. C., and Botstein, D., Phylogenetic portrait of the Saccharomyces cerevisiae functional genome., G3 (Bethesda), vol. 3, no. 8, pp. 1335-40, 2013.
C. Huttenhower, Flamholz, A. I., Landis, J. N., Sahi, S., Myers, C. L., Olszewski, K. L., Hibbs, M. A., Siemers, N. O., Troyanskaya, O. G., and Coller, H. A., Nearest Neighbor Networks: clustering expression data based on gene neighborhoods., BMC Bioinformatics, vol. 8, p. 250, 2007.
K. C. Rowe, Singhal, S., Macmanes, M. D., Ayroles, J. F., Morelli, T. Lyn, Rubidge, E. M., Bi, K., and Moritz, C. C., Museum genomics: low-cost and high-accuracy genetic data from historical specimens., Mol Ecol Resour, vol. 11, no. 6, pp. 1082-92, 2011.
E. A. Stone and Ayroles, J. F., Modulated modularity clustering as an exploratory tool for functional genomic inference., PLoS Genet, vol. 5, no. 5, p. e1000479, 2009.
O. Troyanskaya, Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., and Altman, R. B., Missing value estimation methods for DNA microarrays., Bioinformatics, vol. 17, no. 6, pp. 520-5, 2001.
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.
N. Slonim, Atwal, G. Singh, Tkačik, G., and Bialek, W., Information-based clustering., Proc Natl Acad Sci U S A, vol. 102, no. 51, pp. 18297-302, 2005.
S. D. Kocher, Ayroles, J. F., Stone, E. A., and Grozinger, C. M., Individual variation in pheromone response correlates with reproductive traits and brain gene expression in worker honey bees., PLoS One, vol. 5, no. 2, p. e9116, 2010.
J. Song and Singh, M., How and when should interactome-derived clusters be used to predict functional modules and protein function?, Bioinformatics, vol. 25, no. 23, pp. 3143-50, 2009.
V. M. Boer, Crutchfield, C. A., Bradley, P. H., Botstein, D., and Rabinowitz, J. D., Growth-limiting intracellular metabolites in yeast growing under diverse nutrient limitations., Mol Biol Cell, vol. 21, no. 1, pp. 198-211, 2010.
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.
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.
M. Diehn, Bhattacharya, R., Botstein, D., and Brown, P. O., Genome-scale identification of membrane-associated human mRNAs., PLoS Genet, vol. 2, no. 1, p. e11, 2006.
C. T. Murphy, McCarroll, S. A., Bargmann, C. I., Fraser, A., Kamath, R. S., Ahringer, J., Li, H., and Kenyon, C., Genes that act downstream of DAF-16 to influence the lifespan of Caenorhabditis elegans., Nature, vol. 424, no. 6946, pp. 277-83, 2003.
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.
M. Wyart, Botstein, D., and Wingreen, N. S., Evaluating gene expression dynamics using pairwise RNA FISH data., PLoS Comput Biol, vol. 6, no. 11, p. e1000979, 2010.
R. Shyamsundar, Kim, Y. H., Higgins, J. P., Montgomery, K., Jorden, M., Sethuraman, A., van de Rijn, M., Botstein, D., Brown, P. O., and Pollack, J. R., A DNA microarray survey of gene expression in normal human tissues., Genome Biol, vol. 6, no. 3, p. R22, 2005.
C. Huttenhower, K Mutungu, T., Indik, N., Yang, W., Schroeder, M., Forman, J. J., Troyanskaya, O. G., and Coller, H. A., Detailing regulatory networks through large scale data integration., Bioinformatics, vol. 25, no. 24, pp. 3267-74, 2009.
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.
N. Slavov, Airoldi, E. M., van Oudenaarden, A., and Botstein, D., A conserved cell growth cycle can account for the environmental stress responses of divergent eukaryotes., Mol Biol Cell, vol. 23, no. 10, pp. 1986-97, 2012.
M. J. Brauer, Yuan, J., Bennett, B. D., Lu, W., Kimball, E., Botstein, D., and Rabinowitz, J. D., Conservation of the metabolomic response to starvation across two divergent microbes., Proc Natl Acad Sci U S A, vol. 103, no. 51, pp. 19302-7, 2006.
J. Cande, Goltsev, Y., and Levine, M. S., Conservation of enhancer location in divergent insects., Proc Natl Acad Sci U S A, vol. 106, no. 34, pp. 14414-9, 2009.
P. A. DiMaggio, McAllister, S. R., Floudas, C. A., Feng, X. - J., Rabinowitz, J. D., and Rabitz, H. A., Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies., BMC Bioinformatics, vol. 9, p. 458, 2008.
T. V. Morozova, Ayroles, J. F., Jordan, K. W., Duncan, L. H., Carbone, M. Anna, Lyman, R. F., Stone, E. A., Govindaraju, D. R., R Ellison, C., Mackay, T. F. C., and Anholt, R. R. H., Alcohol sensitivity in Drosophila: translational potential of systems genetics., Genetics, vol. 183, no. 2, pp. 733-45, 1SI-12SI, 2009.
J. P. Nguyen, Linder, A. N., Plummer, G. S., Shaevitz, J. W., and Leifer, A. M., Automatically tracking neurons in a moving and deforming brain., PLoS Comput Biol, vol. 13, no. 5, p. e1005517, 2017.
A. V. Rangan, McGrouther, C. C., Kelsoe, J., Schork, N., Stahl, E., Zhu, Q., Krishnan, A., Yao, V., Troyanskaya, O., Bilaloglu, S., Raghavan, P., Bergen, S., Jureus, A., and Landen, M., A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data., PLoS Comput Biol, vol. 14, no. 5, p. e1006105, 2018.