CYCLoPs: A Comprehensive Database Constructed from Automated Analysis of Protein Abundance and Subcellular Localization Patterns in Saccharomyces cerevisiae

Bagging predictors

Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325 · see citing works

Fast Training of Support Vector Machines Using Sequential Minimal Optimization

Platt, J. C. (1998) · The MIT Press eBooks · doi:10.7551/mitpress/1130.003.0016 · Cited by 5,501 · see citing works

CellProfiler: image analysis software for identifying and quantifying cell phenotypes

Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., et al. (2006) · Genome biology · doi:10.1186/gb-2006-7-10-r100 · Cited by 5,077 · see citing works

Global analysis of protein localization in budding yeast

Huh, W.-K., Falvo, J. V., Gerke, L. C., Carroll, A. S., Howson, R. W., Weissman, J. S., & O'Shea, E. K. (2003) · Nature · doi:10.1038/nature02026 · Cited by 4,248 · cited 12× · see citing works

Global analysis of protein expression in yeast

Ghaemmaghami, S., Huh, W.-K., Bower, K., Howson, R. W., Belle, A., Dephoure, N., O'Shea, E. K., & Weissman, J. S. (2003) · Nature · doi:10.1038/nature02046 · Cited by 3,750 · see citing works

Ensemble-based classifiers

Rokach, L. (2010) · Artificial Intelligence Review · doi:10.1007/s10462-009-9124-7 · Cited by 2,657 · see citing works

Image analysis via the general theory of moments*

Teague, M. R. (1980) · Journal of the Optical Society of America · doi:10.1364/josa.70.000920 · Cited by 2,287 · see citing works

Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants

Tong, A. H. Y., Evangelista, M., Parsons, A. B., Xu, H., Bader, G. D., Pagé, N., Robinson, M., Raghibizadeh, S., Hogue, C. W. V., Bussey, H., et al. (2001) · Science · doi:10.1126/science.1065810 · Cited by 2,138 · see citing works

Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells

Kulak, N. A., Pichler, G., Paron, I., Nagaraj, N., & Mann, M. (2014) · Nature Methods · doi:10.1038/nmeth.2834 · Cited by 1,719 · see citing works

Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise

Newman, J. R. S., Ghaemmaghami, S., Ihmels, J., Breslow, D. K., Noble, M., DeRisi, J. L., & Weissman, J. S. (2006) · Nature · doi:10.1038/nature04785 · Cited by 1,483 · see citing works

Chi2: feature selection and discretization of numeric attributes

Liu, H., & Setiono, R. (2002) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/tai.1995.479783 · Cited by 939 · see citing works

System-wide perturbation analysis with nearly complete coverage of the yeast proteome by single-shot ultra HPLC runs on a bench top Orbitrap

Nagaraj, N., Alexander Kulak, N., Cox, J., Neuhauser, N., Mayr, K., Hoerning, O., Vorm, O., & Mann, M. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.013722 · Cited by 392 · see citing works

Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis

Chong, Y. T., Koh, J. L. Y., Friesen, H., Kaluarachchi Duffy, S., Cox, M. J., Moses, A., Moffat, J., Boone, C., & Andrews, B. J. (2015) · Cell · doi:10.1016/j.cell.2015.04.051 · Cited by 274 · see citing works

A novel single-cell screening platform reveals proteome plasticity during yeast stress responses

Breker, M., Gymrek, M., & Schuldiner, M. (2013) · The Journal of Cell Biology · doi:10.1083/jcb.201301120 · Cited by 205 · see citing works

Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous

Gashler, M., Giraud-Carrier, C. G., & Martinez, T. R. (2008) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2008.154 · Cited by 156 · see citing works

A chemostat array enables the spatio-temporal analysis of the yeast proteome

Dénervaud, N., Becker, J., Delgado-Gonzalo, R., Damay, P., Rajkumar, A. S., Unser, M. A., Shore, D., Naef, F., & Maerkl, S. J. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1308265110 · Cited by 119 · see citing works

SCMD: Saccharomyces cerevisiae Morphological Database

Saito, T. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh113 · Cited by 97 · see citing works

Automated image analysis of protein localization in budding yeast

Chen, S.-C., Zhao, T., Gordon, G. J., & Murphy, R. F. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm206 · Cited by 78 · see citing works

The G protein-coupled receptors in the pufferfish Takifugu rubripes

Sarkar, A., Kumar, S., & Sundar, D. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-s1-s3 · Cited by 49 · see citing works

The Yeast Resource Center Public Image Repository: A large database of fluorescence microscopy images

Riffle, M. E., & Davis, T. N. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-263 · Cited by 41 · see citing works

Organelle DB: an updated resource of eukaryotic protein localization and function

Wiwatwattana, N., Landau, C., Cope, G., Harp, G., & Kumar, A. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl1000 · Cited by 34 · see citing works

YPL.db2: the yeast protein localization database, version 2.0

Kals, M., Natter, K., Thallinger, G., Trajanoski, Z., & Kohlwein, S. D. (2005) · Yeast · doi:10.1002/yea.1204 · Cited by 31 · see citing works

Efficient framework for automated classification of subcellular patterns in budding yeast

Huh, S., Lee, D., & Murphy, R. F. (2009) · Cytometry Part A · doi:10.1002/cyto.a.20793 · Cited by 25 · see citing works

Selecting a single model or combining multiple models for microarray-based classifier development? – A comparative analysis based on large and diverse datasets generated from the MAQC-II project

Chen, M., Shi, L. M., Kelly, R. J., Perkins, R., Fang, H., & Tong, W. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-s10-s3 · Cited by 19 · see citing works

PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae

Jin, K., Li, J., Vizeacoumar, F. S., Li, Z., Min, R., Zamparo, L., Vizeacoumar, F. S., Datti, A., Andrews, B., Boone, C., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr827 · Cited by 16 · see citing works

Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis

Chong, Y. T., Koh, J. L. Y., Friesen, H., Duffy, S., Cox, M. J., Moses, A. M., Moffat, J., Boone, C. M., & Andrews, B. (2015) · Cell · doi:10.1016/j.cell.2015.06.047 · Cited by 16 · see citing works

genEnsemble: A new model for the combination of classifiers and integration of biological knowledge applied to genomic data

Reboiro‐Jato, M., Laza, R., López-Fernández, H., Glez‐Peña, D., Díaz, F., & Fdez‐Riverola, F. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.07.003 · Cited by 6 · see citing works

A global genetic interaction network maps a wiring diagram of cellular function

Costanzo, M., VanderSluis, B., Koch, E. N., Baryshnikova, A., Pons, C., Tan, G., Wang, W., Usaj, M., Hanchard, J., Lee, S. D., et al. (2016) · Science · doi:10.1126/science.aaf1420 · Cited by 1,240 · see citing works

Spatial proteomics: a powerful discovery tool for cell biology

Lundberg, E., & Borner, G. H. H. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0094-y · Cited by 591 · see citing works

Image Data Resource: a bioimage data integration and publication platform

Williams, E. M., Moore, J., Li, S., Rustici, G., Tarkowska, A., Chessel, A., Leo, S., Antal, B., Ferguson, R. K., Sarkans, U., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4326 · Cited by 310 · see citing works

Automated analysis of high‐content microscopy data with deep learning

Kraus, O. Z., Grys, B. T., Ba, J. L., Chong, Y. T., Frey, B. J., Boone, C. M., & Andrews, B. (2017) · Molecular Systems Biology · doi:10.15252/msb.20177551 · Cited by 274 · see citing works

Applications in image-based profiling of perturbations

Caicedo, J. C., Singh, S., & Carpenter, A. E. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.04.003 · Cited by 166 · see citing works

An ER surface retrieval pathway safeguards the import of mitochondrial membrane proteins in yeast

Hansen, K. G., Aviram, N., Laborenz, J., Bibi, C., Meyer, M., Spang, A., Schuldiner, M., & Herrmann, J. M. (2018) · Science · doi:10.1126/science.aar8174 · Cited by 156 · see citing works

Engineering cytosolic acetyl-coenzyme A supply in Saccharomyces cerevisiae: Pathway stoichiometry, free-energy conservation and redox-cofactor balancing

van Rossum, H. M., Kozak, B. U., Pronk, J. T., & van Maris, A. J. A. (2016) · Metabolic Engineering · doi:10.1016/j.ymben.2016.03.006 · Cited by 150 · see citing works

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

Pärnamaa, T., & Parts, L. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.116.033654 · Cited by 144 · see citing works

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

Ušaj, M., Tan, Y., Wang, W., VanderSluis, B., Zou, A., Myers, C. L., Costanzo, M., Andrews, B., & Boone, C. M. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.117.040220 · Cited by 130 · see citing works

The cellular economy of the Saccharomyces cerevisiae zinc proteome

Wang, Y., Weisenhorn, E., MacDiarmid, C. W., Andreini, C., Bucci, M. D., Taggart, J., Banci, L., Russell, J. D., Coon, J. J., & Eide, D. J. (2018) · Metallomics · doi:10.1039/c8mt00269j · Cited by 95 · see citing works

Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting

Lu, A. X., Kraus, O. Z., Cooper, S., & Moses, A. M. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007348 · Cited by 94 · see citing works

Functional annotation of chemical libraries across diverse biological processes

Piotrowski, J. S., Li, S. C., Deshpande, R., Simpkins, S. W., Nelson, J., Yashiroda, Y., Barber, J. M., Safizadeh, H., Wilson, E. H., Okada, H., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2436 · Cited by 93 · see citing works

YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells

Lu, A. X., Zarin, T., Hsu, I. S., & Moses, A. M. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz402 · Cited by 92 · see citing works

Saccharomyces cerevisiae Forms d-2-Hydroxyglutarate and Couples Its Degradation to d-Lactate Formation via a Cytosolic Transhydrogenase

Becker‐Kettern, J., Paczia, N., Conrotte, J., Kay, D. P., Guignard, C., Jung, P. P., & Linster, C. L. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.m115.704494 · Cited by 75 · see citing works

Harnessing sub-organelle metabolism for biosynthesis of isoprenoids in yeast

Cao, X. D., Yang, S. L., Cao, C., & Zhou, Y. J. (2020) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2020.06.005 · Cited by 70 · see citing works

A vast evolutionarily transient translatome contributes to phenotype and fitness

Wacholder, A. C., Parikh, S. B., Coelho, N. C., Acar, O., Houghton, C. J., Chou, L., & Carvunis, A. (2023) · Cell Systems · doi:10.1016/j.cels.2023.04.002 · Cited by 61 · see citing works

YeastRGB: comparing the abundance and localization of yeast proteins across cells and libraries

Dubreuil, B., Sass, E., Nadav, Y., Heidenreich, M., Georgeson, J. M., Weill, U., Duan, Y., Meurer, M., Schuldiner, M., Knop, M., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky941 · Cited by 65 · see citing works

PP2A Controls Genome Integrity by Integrating Nutrient-Sensing and Metabolic Pathways with the DNA Damage Response

Ferrari, E., Bruhn, C., Peretti, M., Cassani, C., Carotenuto, W., Elgendy, M., Shubassi, G., Lucca, C., Bermejo, R., Varasi, M., et al. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.05.027 · Cited by 58 · see citing works

Alternative reactions at the interface of glycolysis and citric acid cycle inSaccharomyces cerevisiae

van Rossum, H. M., Kozak, B. U., Niemeijer, M. S., Duine, H. J., Luttik, M. A. H., Boer, V. M., Kötter, P., Daran, J.-M. G., van Maris, A. J. A., & Pronk, J. T. (2016) · FEMS Yeast Research · doi:10.1093/femsyr/fow017 · Cited by 54 · see citing works

Evidence for a Nonendosomal Function of the Saccharomyces cerevisiae ESCRT-III-Like Protein Chm7

Bauer, I., Brune, T., Preiss, R., & Kölling, R. (2015) · Genetics · doi:10.1534/genetics.115.178939 · Cited by 52 · see citing works

Subcellular Transcriptomics and Proteomics: A Comparative Methods Review

Christopher, J. A., Geladaki, A., Dawson, C. S., Vennard, O. L., & Lilley, K. S. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100186 · Cited by 48 · see citing works

The structure and function of deubiquitinases: lessons from budding yeast

Suresh, H. G., Pascoe, N., & Andrews, B. (2020) · Open Biology · doi:10.1098/rsob.200279 · Cited by 50 · see citing works

Application of Machine Learning in Spatial Proteomics

Mou, M., Pan, Z., Lu, M., Sun, H., Wang, Y., Luo, Y., & Zhu, F. (2022) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.2c01161 · Cited by 48 · see citing works

Multi-Faceted Systems Biology Approaches Present a Cellular Landscape of Phenolic Compound Inhibition in Saccharomyces cerevisiae

Fletcher, E., & Baetz, K. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.539902 · Cited by 43 · see citing works

Rotation equivariant and invariant neural networks for microscopy image analysis

Chidester, B., Zhou, T., Do, M. N., & Ma, J. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz353 · Cited by 43 · see citing works

Yeast as a Heterologous Model System to Uncover Type III Effector Function

Popa, C., Coll, N. S., Valls, M., & Sessa, G. (2016) · PLoS Pathogens · doi:10.1371/journal.ppat.1005360 · Cited by 42 · see citing works

Non-histone protein acetylation by the evolutionarily conserved GCN5 and PCAF acetyltransferases

Downey, M. (2020) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2020.194608 · Cited by 40 · see citing works

Bioimage-based protein subcellular location prediction: a comprehensive review

Xu, Y., Yao, L., & Shen, H. (2017) · Frontiers of Computer Science · doi:10.1007/s11704-016-6309-5 · Cited by 39 · see citing works

Systematic bacterialization of yeast genes identifies a near-universally swappable pathway

Kachroo, A. H., Laurent, J. M., Akhmetov, A., Szilagyi-Jones, M., McWhite, C. D., Zhao, A. S., & Marcotte, E. M. (2017) · eLife · doi:10.7554/elife.25093 · Cited by 37 · see citing works

Profiles of Long Noncoding RNAs in Human Naive and Memory T Cells

Spurlock, C. F., Shaginurova, G. I., Tossberg, J. T., Hester, J., Chapman, N. S., Guo, Y. P., Crooke, P. S., & Aune, T. M. (2017) · The Journal of Immunology · doi:10.4049/jimmunol.1700232 · Cited by 35 · see citing works

Proteomic analysis reveals the direct recruitment of intrinsically disordered regions to stress granules in S. cerevisiae

Zhu, M., Kuechler, E. R., Zhang, J., Matalon, O., Dubreuil, B., Hofmann, A., Loewen, C., Levy, E. D., Gsponer, J., & Mayor, T. (2020) · Journal of Cell Science · doi:10.1242/jcs.244657 · Cited by 33 · see citing works

Quantitative Operating Principles of Yeast Metabolism during Adaptation to Heat Stress

Pereira, T., Vilaprinyó, E., Bellı́, G., Herrero, E., Salvadó, B., Albert Sorribas, B., Altés, G., & Alves, R. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.020 · Cited by 28 · see citing works

Requirements for Carnitine Shuttle-Mediated Translocation of Mitochondrial Acetyl Moieties to the Yeast Cytosol

van Rossum, H. M., Kozak, B. U., Niemeijer, M. S., Dykstra, J. C., Luttik, M. A. H., Daran, J.-M. G., van Maris, A. J. A., & Pronk, J. T. (2016) · mBio · doi:10.1128/mbio.00520-16 · Cited by 27 · see citing works

Integrating images from multiple microscopy screens reveals diverse patterns of change in the subcellular localization of proteins

Lu, A. X., Chong, Y. T., Hsu, I. S., Strome, B., Handfield, L., Kraus, O. Z., Andrews, B., & Moses, A. M. (2018) · eLife · doi:10.7554/elife.31872 · Cited by 24 · see citing works

Rotation Equivariance and Invariance in Convolutional Neural NetworksPreprint

Chidester, B., Do, M. N., & Ma, J. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.12301 · Cited by 23 · see citing works

Switching a conflicted bacterial DTD-tRNA code is essential for the emergence of mitochondria

Gogoi, J., Bhatnagar, A., Ann, K. J., Pottabathini, S., Singh, R. P., Mazeed, M., Kuncha, S. K., Kruparani, S. P., & Sankaranarayanan, R. (2022) · Science Advances · doi:10.1126/sciadv.abj7307 · Cited by 22 · see citing works

The emerging landscape of eukaryotic polyphosphatases

McCarthy, L., & Downey, M. (2023) · FEBS Letters · doi:10.1002/1873-3468.14584 · Cited by 22 · see citing works

Building a KATalogue of acetyllysine targeting and function

Downey, M., & Baetz, K. (2015) · Briefings in Functional Genomics · doi:10.1093/bfgp/elv045 · Cited by 22 · see citing works

Function and structure-based screening of compounds, peptides and proteins to identify drug candidates

Malik, V., Dhanjal, J. K., Kumari, A., Radhakrishnan, N., Singh, K., & Sundar, D. (2017) · Methods · doi:10.1016/j.ymeth.2017.08.010 · Cited by 20 · see citing works

Decoding the chromatin proteome of a single genomic locus by DNA sequencing

Korthout, T., Poramba‐Liyanage, D. W., van Kruijsbergen, I., Verzijlbergen, K. F., van Gemert, F. P. A., van Welsem, T., & van Leeuwen, F. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2005542 · Cited by 20 · see citing works

A multi-scale multi-model deep neural network via ensemble strategy on high-throughput microscopy image for protein subcellular localization

Ding, J., Xu, J., Wei, J., Tang, J., & Guo, F. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118744 · Cited by 16 · see citing works

Application of deep convolutional neural networks in classification of protein subcellular localization with microscopy images

Xiao, M., Shen, X., & Pan, W. (2019) · Genetic Epidemiology · doi:10.1002/gepi.22182 · Cited by 16 · see citing works

Vacuolar Localization via the N-terminal Domain of Sch9 is Required for TORC1-dependent Phosphorylation and Downstream Signal Transduction

Novarina, D., Guerra, P., & Milias‐Argeitis, A. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167326 · Cited by 16 · see citing works

PIFiA: self-supervised approach for protein functional annotation from single-cell imaging data

Razdaibiedina, A., Brechalov, A. V., Friesen, H., Ušaj, M. M., Masinas, M. P. D., Suresh, H. G., Wang, K. E., Boone, C. M., Ba, J. L., & Andrews, B. (2024) · Molecular Systems Biology · doi:10.1038/s44320-024-00029-6 · Cited by 15 · see citing works

An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images

Lu, A. X., & Moses, A. M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158712 · Cited by 15 · see citing works

The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiersPreprint

Lu, A. X., Lu, A. X., Schormann, W., Ghassemi, M., Andrews, D. W., & Moses, A. M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.07282 · Cited by 15 · see citing works

Current and novel approaches in yeast cell death research

Chaves, S. R., Rego, A., Santos‐Pereira, C., Sousa, M. J., & Côrte‐Real, M. (2024) · Cell Death and Differentiation · doi:10.1038/s41418-024-01298-2 · Cited by 14 · see citing works

Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology

Bhushan, V., & Nita‐Lazar, A. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00839 · Cited by 13 · see citing works

CytoImageNet: A large-scale pretraining dataset for bioimage transfer learningPreprint

Hua, S. B. Z., Lu, A. X., & Moses, A. M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.11646 · Cited by 10 · see citing works

Phenomic screen identifies a role for the yeast lysine acetyltransferase NuA4 in the control of Bcy1 subcellular localization, glycogen biosynthesis, and mitochondrial morphology

Walden, E. A., Fong, R. Y., Pham, T. T., Knill, H., Laframboise, S. J., Huard, S., Harper, M., & Baetz, K. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009220 · Cited by 9 · see citing works

The Genetic and Physical Interactomes of the Saccharomyces cerevisiae Hrq1 Helicase

Rogers, C. M., Sanders, E., Nguyen, P. A., Smith-Kinnaman, W. R., Mosley, A. L., & Bochman, M. L. (2020) · G3 Genes Genomes Genetics · doi:10.1534/g3.120.401864 · Cited by 8 · see citing works

Binary interactome models of inner- versus outer-complexome organisationPreprint

Lambourne, L., Yadav, A., Wang, Y., Desbuleux, A., Kim, D., Cafarelli, T. M., Pons, C., Kovács, I. A., Jailkhani, N., Schlabach, S., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.16.435663 · Cited by 8 · see citing works

GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation forSaccharomyces cerevisiae

Mondeel, T. D. G. A., Crémazy, F. G. E., & Barberis, M. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty052 · Cited by 7 · see citing works

TheCellVision.org: A Database for Visualizing and Mining High-Content Cell Imaging Projects

Masinas, M. P. D., Ušaj, M. M., Ušaj, M., Boone, C. M., & Andrews, B. (2020) · G3 Genes Genomes Genetics · doi:10.1534/g3.120.401570 · Cited by 7 · see citing works

The Genetic Requirements for Pentose Fermentation in Budding Yeast

Mittelman, K., & Barkai, N. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.117.039610 · Cited by 7 · see citing works

Comprehensive Synthetic Genetic Array Analysis of Alleles That Interact with Mutation of the Saccharomyces cerevisiae RecQ Helicases Hrq1 and Sgs1

Sanders, E., Nguyen, P. A., Rogers, C. M., & Bochman, M. L. (2020) · G3 Genes Genomes Genetics · doi:10.1534/g3.120.401709 · Cited by 7 · see citing works

Towards the construction of a virtual yeast

Qian, L., Zhou, Z., Zhou, P., Dong, Z., Zhang, X., Dai, Z., Gao, Z., Sun, S., Roy, K. R., Wang, S., et al. (2026) · Nature · doi:10.1038/s41586-026-10574-9 · Cited by 10 · see citing works

A deep dive into the RecQ interactome: something old and something new

Simmons, R. H., Rogers, C. M., & Bochman, M. L. (2021) · Current Genetics · doi:10.1007/s00294-021-01190-3 · Cited by 6 · see citing works

Experimental assessment of AI-based interactome mapping

Lambourne, L., Yadav, A., Wang, Y., Desbuleux, A., Kim, D.-K., Laval, F., Spirohn, K., Cafarelli, T. M., Pons, C., Kovács, I. A., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-70942-x · Cited by 5 · see citing works

Hoi1 targets BLTP2 to ER–PM contact sites to regulate lipid homeostasis

Dziurdzik, S. K., Sridhar, V., Eng, H. L., Neuman, S. D., Yan, J., Davey, M., Taubert, S., Bashirullah, A., & Conibear, E. (2026) · The Journal of Cell Biology · doi:10.1083/jcb.202502131 · Cited by 5 · see citing works

Overproduction of Sch9 leads to its aggregation and cell elongation in Saccharomyces cerevisiae

Drozdova, P. B., Lipaeva, P., Rogoza, T. M., Zhouravleva, G. A., & Bondarev, S. A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0193726 · Cited by 3 · see citing works

Single-cell imaging of protein dynamics of paralogs reveals sources of gene retention

Dandage, R., Papkov, M., Greco, B. M., Pereira, V., Fishman, D., Friesen, H., Wang, K. E., Styles, E. B., Kraus, O. Z., Grys, B., et al. (2025) · iScience · doi:10.1016/j.isci.2025.112771 · Cited by 3 · see citing works

Unveiling Forkhead-mediated regulation of yeast cell cycle and metabolic networks

Barberis, M., & Mondeel, T. D. G. A. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.03.033 · Cited by 3 · see citing works

PARPAL: PARalog Protein redistribution using Abundance and Localization in yeast database

Greco, B. M., Zapata, G. A., Dandage, R., Papkov, M., Pereira, V., Lefebvre, F., Bourque, G., Parts, L., & Kuzmin, E. (2025) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkaf148 · Cited by 2 · see citing works

Investigating symmetry breaking in yeast

Singh, P., Das, A., & Li, R. (2017) · Methods in cell biology · doi:10.1016/bs.mcb.2016.12.001 · Cited by 2 · see citing works

Social-Psychological Intervention: Cognitive Empathy Development

Rajaram, K. (2021) · Springer eBooks · doi:10.1007/978-981-33-6804-0_4 · Cited by 2 · see citing works

Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retentionPreprint

Dandage, R., Papkov, M., Greco, B. M., Fishman, D., Friesen, H., Wang, K. E., Styles, E. B., Kraus, O. Z., Grys, B., Boone, C. M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.23.568466 · Cited by 2 · see citing works

A screen for synthetic genetic interactions with the Saccharomyces cerevisiae hrq1ΔN allele

Shumaker, K. A., Kumcu, M. E., McDevitt, F. E., Rogers, C. M., & Bochman, M. L. (2025) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkaf222 · Cited by 1 · see citing works

The Hemoprotein Hhy1 Promotes Heme‐Dependent Catalase Activity of Ctt1

Vahsen, T., Plante, S., Mbuya, B., & Labbé, S. (2026) · Molecular Microbiology · doi:10.1111/mmi.70062 · Cited by 1 · see citing works

Extracting and Integrating Protein Localization Changes from Multiple Image Screens of Yeast Cells

Lu, A. X., Handfield, L., & Moses, A. M. (2018) · BIO-PROTOCOL · doi:10.21769/bioprotoc.3022 · Cited by 1 · see citing works

Expanding TheCellVision.org: a central repository for visualizing and mining high-content cell imaging projects

Masinas, M. P. D., Litsios, A., Razdaibiedina, A., Ušaj, M., Boone, C. M., & Andrews, B. (2024) · Genetics · doi:10.1093/genetics/iyae044 · Cited by 1 · see citing works

Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy

Lu, A. X., & Moses, A. M. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-3834-7_15 · Cited by 1 · see citing works

Identification of uncharacterized proteins potentially localized to mitochondria (UPMs) in Saccharomyces cerevisiae using a fluorescent protein unstable in the cytoplasm

Horiuchi, S., Namba, S., Saeki, N., Satoh, A., & Moriya, H. (2021) · Yeast · doi:10.1002/yea.3685 · Cited by 1 · see citing works

Phenotypic Heterogeneity in the DNA Replication Stress Response Revealed by Quantitative Protein Dynamics MeasurementsPreprint

Ho, B., Loll‐Krippleber, R., Torres, N. P., Cuny, A. P., Rudolf, F., & Brown, G. W. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.08.495346 · Cited by 1 · see citing works

Functional Analysis of Short Linear Motifs in Intrinsically Disordered Regions

Man, M. L. C. (2017) · TSpace (University of Toronto)

Identification and Investigation of Novel DNA Damage Repair Genes Via Network Analysis

Potter, T. A. (2018) · doi:10.22215/etd/2018-13233

TheCellVision.org: A Database for Visualizing and Mining High-Content Cell Imaging Projects

Masinas, M. P. D., Ušaj, M. M., Ušaj, M., Boone, C. M., & Andrews, B. (2023) · doi:10.32920/22149035.v1

TheCellVision.org: A Database for Visualizing and Mining High-Content Cell Imaging Projects

Masinas, M. P. D., Ušaj, M. M., Ušaj, M., Boone, C. M., & Andrews, B. (2023) · doi:10.32920/22149035

Representation Learning Methods for Single-Cell Microscopy are Confounded by Background CellsPreprint

Gupta, A., Moses, A. M., & Lu, A. X. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.26.661577

FAIRsharing record for: Image Data Resource

FAIRsharing Team, & Besson, S. (2018) · Discovery Research Portal (University of Dundee) · doi:10.25504/fairsharing.6wf1zw

Vermeer: Autoregressive generative modeling of microscopy predicts protein localizationPreprint

Kambhampati, S., Zimmermann, E., Hayir, E., Yang, K. K., Chen, F., & Lu, A. X. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.01.729395

Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis

Chong, Y. T., Koh, J. L. Y., Friesen, H., Kaluarachchi Duffy, S., Cox, M. J., Moses, A., Moffat, J., Boone, C., & Andrews, B. J. (2015) · Cell · doi:10.1016/j.cell.2015.04.051 · Cited by 274 · see citing works

LoQAtE—Localization and Quantitation ATlas of the yeast proteomE. A new tool for multiparametric dissection of single-protein behavior in response to biological perturbations in yeast

Breker, M., Gymrek, M., Moldavski, O., & Schuldiner, M. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt933 · Cited by 83 · see citing works

A Global Analysis of Molecular Fluctuations Associated with Cell Cycle Progression in Saccharomyces cerevisiae

Grys, B. (2019) · TSpace (University of Toronto)

Automated Image Analysis for Systematic and Quantitative Comparison of Protein Expression within Cell Populations

Handfield, L. (2014) · TSpace (University of Toronto)

Subcellular localization of the yeast proteomePreprint

Kumar, A., Agarwal, S., Heyman, J. A., Matson, S., Heidtman, M. I., Piccirillo, S., Umansky, L., Drawid, A., Jansen, R., Liu, Y., et al. (2002) · Genes & Development · doi:10.1101/gad.970902 · Cited by 737 · see citing works