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Papers by Iulian Pruteanu-Malinici

Research paper thumbnail of Infinite Hidden Markov Models and ISA Features for Unusual-Event Detection in Video

2007 IEEE International Conference on Image Processing, 2007

Research paper thumbnail of A microfluidic device and computational platform for high-throughput live imaging of gene expression

Nature Methods, 2012

To fully describe gene expression dynamics requires the ability to quantitatively capture express... more To fully describe gene expression dynamics requires the ability to quantitatively capture expression in individual cells over time. Automated systems for acquiring and analyzing real-time images are needed to obtain unbiased data across many samples and conditions. We developed a microfluidics device, the RootArray, in which 64 Arabidopsis thaliana seedlings can be grown and their roots imaged by confocal microscopy over several days without manual intervention. To achieve high throughput, we decoupled acquisition from analysis. In the acquisition phase, we obtain images at low resolution and segment to identify regions of interest. Coordinates are communicated to the microscope to record the regions of interest at high resolution. In the analysis phase, we reconstruct three-dimensional objects from stitched high-resolution images and extract quantitative measurements from a virtual medial section of the root. We tracked hundreds of roots to capture detailed expression patterns of 12 transgenic reporter lines under different conditions.

Research paper thumbnail of Infinite Hidden Markov Models for Unusual-Event Detection in Video

IEEE Transactions on Image Processing, 2000

Research paper thumbnail of Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields

Research paper thumbnail of Pharmacogenomic agreement between two cancer cell line data sets

Research paper thumbnail of Landscape of Targeted Anti-Cancer Drug Synergies in Melanoma Identifies a Novel BRAF-VEGFR/PDGFR Combination Treatment

PloS one, 2015

A newer generation of anti-cancer drugs targeting underlying somatic genetic driver events have r... more A newer generation of anti-cancer drugs targeting underlying somatic genetic driver events have resulted in high single-agent or single-pathway response rates in selected patients, but few patients achieve complete responses and a sizeable fraction of patients relapse within a year. Thus, there is a pressing need for identification of combinations of targeted agents which induce more complete responses and prevent disease progression. We describe the results of a combination screen of an unprecedented scale in mammalian cells performed using a collection of targeted, clinically tractable agents across a large panel of melanoma cell lines. We find that even the most synergistic drug pairs are effective only in a discrete number of cell lines, underlying a strong context dependency for synergy, with strong, widespread synergies often corresponding to non-specific or off-target drug effects such as multidrug resistance protein 1 (MDR1) transporter inhibition. We identified drugs sensit...

Research paper thumbnail of Small molecules facilitate rapid and synchronous iPSC generation

Research paper thumbnail of A microfluidic device and computational platform for high-throughput live imaging of gene expression

Nature Methods, 2012

To fully describe gene expression dynamics requires the ability to quantitatively capture express... more To fully describe gene expression dynamics requires the ability to quantitatively capture expression in individual cells over time. Automated systems for acquiring and analyzing real-time images are needed to obtain unbiased data across many samples and conditions. We developed a microfluidics device, the RootArray, in which 64 Arabidopsis thaliana seedlings can be grown and their roots imaged by confocal microscopy over several days without manual intervention. To achieve high throughput, we decoupled acquisition from analysis. In the acquisition phase, we obtain images at low resolution and segment to identify regions of interest. Coordinates are communicated to the microscope to record the regions of interest at high resolution. In the analysis phase, we reconstruct three-dimensional objects from stitched high-resolution images and extract quantitative measurements from a virtual medial section of the root. We tracked hundreds of roots to capture detailed expression patterns of 12 transgenic reporter lines under different conditions.

Research paper thumbnail of Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

Research paper thumbnail of Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields

Research paper thumbnail of Dynamic hierarchical Dirichlet process for modeling topics in timestamped documents

Research paper thumbnail of Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

PLoS Computational Biology, 2011

Research paper thumbnail of Infinite Hidden Markov Models and ISA Features for Unusual-Event Detection in Video

2007 IEEE International Conference on Image Processing, 2007

Research paper thumbnail of A microfluidic device and computational platform for high-throughput live imaging of gene expression

Nature Methods, 2012

To fully describe gene expression dynamics requires the ability to quantitatively capture express... more To fully describe gene expression dynamics requires the ability to quantitatively capture expression in individual cells over time. Automated systems for acquiring and analyzing real-time images are needed to obtain unbiased data across many samples and conditions. We developed a microfluidics device, the RootArray, in which 64 Arabidopsis thaliana seedlings can be grown and their roots imaged by confocal microscopy over several days without manual intervention. To achieve high throughput, we decoupled acquisition from analysis. In the acquisition phase, we obtain images at low resolution and segment to identify regions of interest. Coordinates are communicated to the microscope to record the regions of interest at high resolution. In the analysis phase, we reconstruct three-dimensional objects from stitched high-resolution images and extract quantitative measurements from a virtual medial section of the root. We tracked hundreds of roots to capture detailed expression patterns of 12 transgenic reporter lines under different conditions.

Research paper thumbnail of Infinite Hidden Markov Models for Unusual-Event Detection in Video

IEEE Transactions on Image Processing, 2000

Research paper thumbnail of Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields

Research paper thumbnail of Pharmacogenomic agreement between two cancer cell line data sets

Research paper thumbnail of Landscape of Targeted Anti-Cancer Drug Synergies in Melanoma Identifies a Novel BRAF-VEGFR/PDGFR Combination Treatment

PloS one, 2015

A newer generation of anti-cancer drugs targeting underlying somatic genetic driver events have r... more A newer generation of anti-cancer drugs targeting underlying somatic genetic driver events have resulted in high single-agent or single-pathway response rates in selected patients, but few patients achieve complete responses and a sizeable fraction of patients relapse within a year. Thus, there is a pressing need for identification of combinations of targeted agents which induce more complete responses and prevent disease progression. We describe the results of a combination screen of an unprecedented scale in mammalian cells performed using a collection of targeted, clinically tractable agents across a large panel of melanoma cell lines. We find that even the most synergistic drug pairs are effective only in a discrete number of cell lines, underlying a strong context dependency for synergy, with strong, widespread synergies often corresponding to non-specific or off-target drug effects such as multidrug resistance protein 1 (MDR1) transporter inhibition. We identified drugs sensit...

Research paper thumbnail of Small molecules facilitate rapid and synchronous iPSC generation

Research paper thumbnail of A microfluidic device and computational platform for high-throughput live imaging of gene expression

Nature Methods, 2012

To fully describe gene expression dynamics requires the ability to quantitatively capture express... more To fully describe gene expression dynamics requires the ability to quantitatively capture expression in individual cells over time. Automated systems for acquiring and analyzing real-time images are needed to obtain unbiased data across many samples and conditions. We developed a microfluidics device, the RootArray, in which 64 Arabidopsis thaliana seedlings can be grown and their roots imaged by confocal microscopy over several days without manual intervention. To achieve high throughput, we decoupled acquisition from analysis. In the acquisition phase, we obtain images at low resolution and segment to identify regions of interest. Coordinates are communicated to the microscope to record the regions of interest at high resolution. In the analysis phase, we reconstruct three-dimensional objects from stitched high-resolution images and extract quantitative measurements from a virtual medial section of the root. We tracked hundreds of roots to capture detailed expression patterns of 12 transgenic reporter lines under different conditions.

Research paper thumbnail of Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

Research paper thumbnail of Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields

Research paper thumbnail of Dynamic hierarchical Dirichlet process for modeling topics in timestamped documents

Research paper thumbnail of Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

PLoS Computational Biology, 2011

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