| Evaluation of categorical matrix completion algorithms: toward improved active learning for drug discovery | 0 | 0.34 | 2021 |
| Learning complex subcellular distribution patterns of proteins via analysis of immunohistochemistry images. | 0 | 0.34 | 2020 |
| Integration of Heterogeneous Experimental Data Improves Global Map of Human Protein Complexes. | 0 | 0.34 | 2019 |
| Evaluation of methods for generative modeling of cell and nuclear shape. | 1 | 0.43 | 2019 |
| Learning Generative Models of Tissue Organization with Supervised GANs | 0 | 0.34 | 2018 |
| Image-based spatiotemporal causality inference for protein signaling networks. | 0 | 0.34 | 2017 |
| Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories. | 1 | 0.35 | 2016 |
| Deciding When To Stop: Efficient Experimentation To Learn To Predict Drug-Target Interactions | 0 | 0.34 | 2015 |
| Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules. | 0 | 0.34 | 2015 |
| Design Automation for Biological Models: A Pipeline that Incorporates Spatial and Molecular Complexity | 3 | 0.48 | 2015 |
| Deciding when to stop: efficient experimentation to learn to predict drug-target interactions | 1 | 0.35 | 2015 |
| Deciding when to stop: Efficient stopping of active learning guided drug-target prediction. | 0 | 0.34 | 2015 |
| A new era in bioimage informatics. | 3 | 0.40 | 2014 |
| Efficient discovery of responses of proteins to compounds using active learning. | 9 | 0.47 | 2014 |
| Determining the subcellular location of new proteins from microscope images using local features. | 16 | 0.63 | 2013 |
| (3) The CellOrganizer project: An open source system to learn image-derived models of subcellular organization over time and space | 0 | 0.34 | 2012 |
| Protein subcellular location pattern classification in cellular images using latent discriminative models. | 7 | 0.49 | 2012 |
| Automated estimation of microtubule model parameters from 3-D live cell microscopy images | 1 | 0.38 | 2011 |
| Model building and intelligent acquisition with application to protein subcellular location classification. | 2 | 0.36 | 2011 |
| Determination of protein location diversity via analysis of immunohistochemical images from the Human Protein Atlas | 1 | 0.35 | 2011 |
| Learning cellular sorting pathways using protein interactions and sequence motifs. | 0 | 0.34 | 2011 |
| Discriminative motif finding for predicting protein subcellular localization. | 8 | 0.51 | 2011 |
| A Graphical Model to Determine the Subcellular Protein Location in Artificial Tissues. | 0 | 0.34 | 2010 |
| Structured Literature Image Finder: Parsing Text and Figures in Biomedical Literature. | 3 | 0.44 | 2010 |
| Automated analysis of protein subcellular location in time series images. | 6 | 0.76 | 2010 |
| Quantifying the distribution of probes between subcellular locations using unsupervised pattern unmixing | 9 | 0.58 | 2010 |
| Nuclear segmentation in microscope cell images: a hand-segmented dataset and comparison of algorithms | 22 | 1.33 | 2009 |
| Intelligent acquisition and learning of fluorescence microscope data models. | 4 | 0.61 | 2009 |
| Instance-Based Generative Biological Shape Modeling. | 4 | 0.45 | 2009 |
| Structured Correspondence Topic Models for Mining Captioned Figures in Biological Literature. | 18 | 1.16 | 2009 |
| Automated analysis of human protein atlas immunofluorescence images | 7 | 0.60 | 2009 |
| Workshop summary: Automated interpretation and modelling of cell images | 0 | 0.34 | 2009 |
| Structured literature image finder: extracting information from text and images in biomedical literature | 9 | 0.71 | 2008 |
| Bioinformatics Research and Development: Second International Conference, BIRD 2008 Vienna, Austria, July 7-9, 2008 Proceedings | 49 | 3.75 | 2008 |
| Improved recognition of figures containing fluorescence microscope images in online journal articles using graphical models. | 15 | 0.90 | 2008 |
| Automated Proteome-Wide Determination Of Subcellular Location Using High Throughput Microscopy | 1 | 0.35 | 2008 |
| Principles of bioimage informatics: focus on machine learning of cell patterns | 3 | 0.42 | 2008 |
| Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns | 6 | 0.55 | 2008 |
| Identifying Subcellular Locations from Images of Unknown Resolution | 0 | 0.34 | 2008 |
| Deformation-Based Nonlinear Dimension Reduction: Applications To Nuclear Morphometry | 10 | 0.89 | 2008 |
| Automated Comparison Of Protein Subcellular Location Patterns Between Images Of Normal And Cancerous Tissues | 6 | 0.45 | 2008 |
| A Stacked Graphical Model For Associating Sub-Images With Sub-Captions | 9 | 0.59 | 2007 |
| Efficient Acquisition and Learning of Fluorescence Microscope Data Models | 4 | 0.51 | 2007 |
| A multiresolution approach to automated classification of protein subcellular location images. | 47 | 2.84 | 2007 |
| Automated image analysis of protein localization in budding yeast. | 16 | 1.11 | 2007 |
| IDENTIFYING FLUORESCENCE MICROSCOPE IMAGES IN ONLINE JOURNAL ARTICLES USING BOTH IMAGE AND TEXT FEATURES | 3 | 0.44 | 2007 |
| Interpretation of protein subcellular location patterns in 3D images across cell types and resolutions | 5 | 0.55 | 2007 |
| A Novel Graphical Model Approach to Segmenting Cell Images | 11 | 1.01 | 2006 |
| A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images. | 35 | 1.16 | 2006 |
| Application Of Temporal Texture Features To Automated Analysis Of Protein Subcellular Locations In Time Series Fluorescence Microscope Images | 4 | 0.47 | 2006 |
