Eric Kernfeld
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View article: A collection of draft gene regulatory networks and perturbation transcriptomics data
A collection of draft gene regulatory networks and perturbation transcriptomics data Open
These are collections of previously published gene regulatory networks and perturbation transcriptomics data analyzed in our manuscript "A systematic comparison of computational methods for expression forecasting". For more information and…
View article: A collection of draft gene regulatory networks and perturbation transcriptomics data
A collection of draft gene regulatory networks and perturbation transcriptomics data Open
These are collections of previously published gene regulatory networks and perturbation transcriptomics data analyzed in our manuscript "A systematic comparison of computational methods for expression forecasting". For more information and…
View article: A collection of draft gene regulatory networks and perturbation transcriptomics data
A collection of draft gene regulatory networks and perturbation transcriptomics data Open
These are collections of previously published gene regulatory networks and perturbation transcriptomics data analyzed in our manuscript "A systematic comparison of computational methods for expression forecasting". For more information and…
View article: Organogenetic transcriptomes of the <i>Drosophila</i> embryo at single cell resolution
Organogenetic transcriptomes of the <i>Drosophila</i> embryo at single cell resolution Open
To gain insight into the transcription programs activated during the formation of Drosophila larval structures, we carried out single cell RNA sequencing during two periods of Drosophila embryogenesis: stages 10-12, when most organs are fi…
View article: A collection of draft gene regulatory networks and perturbation transcriptomics data
A collection of draft gene regulatory networks and perturbation transcriptomics data Open
These are collections of previously published gene regulatory networks and perturbation transcriptomics data analyzed in our manuscript "A systematic comparison of computational methods for expression forecasting". For more information and…
View article: Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification"
Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification" Open
This collection of data was used in our manuscript tentatively entitled "Model-X knockoffs reveal data-dependent limits on regulatory network identification". It is entirely from public sources, but to enable easy repetition of our analyse…
View article: Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification"
Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification" Open
This collection of data was used in our manuscript tentatively entitled "Model-X knockoffs reveal data-dependent limits on regulatory network identification". It is entirely from public sources, but to enable easy repetition of our analyse…
View article: A systematic comparison of computational methods for expression forecasting
A systematic comparison of computational methods for expression forecasting Open
Expression forecasting methods use machine learning models to predict how a cell will alter its transcriptome upon perturbation. Such methods are enticing because they promise to answer pressing questions in fields ranging from development…
View article: Model-X knockoffs reveal data-dependent limits on regulatory network identification
Model-X knockoffs reveal data-dependent limits on regulatory network identification Open
Summary Computational biologists have long sought to automatically infer transcriptional regulatory networks (TRNs) from gene expression data, but such approaches notoriously suffer from false positives. Two points of failure could yield f…
View article: Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification"
Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification" Open
This collection of data was used in our manuscript "Model-X knockoffs reveal data-dependent limits on regulatory network identification". It is entirely from publicly available sources, but to enable easy repetition of our analyses, we col…
View article: Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification"
Benchmark data for "Model-X knockoffs reveal data-dependent limits on regulatory network identification" Open
This collection of data was used in our manuscript "Model-X knockoffs reveal data-dependent limits on regulatory network identification". It is entirely from publicly available sources, but to enable easy repetition of our analyses, we col…
View article: Beyond pseudotime: Following T-cell maturation in single-cell RNAseq time series
Beyond pseudotime: Following T-cell maturation in single-cell RNAseq time series Open
Cellular development has traditionally been described as a series of transitions between discrete cell states, such as the sequence of double negative, double positive and single positive stages in T-cell development. Recent advances in si…
View article: Situated Language Understanding with Human-like and Visualization-Based Transparency
Situated Language Understanding with Human-like and Visualization-Based Transparency Open
Communication with robots is challenging, partly due to their differences from humans and the consequent discrepancy in people's mental model of what robots can see, hear, or understand.Transparency mechanisms aim to mitigate this challeng…
View article: Multilinear subspace clustering
Multilinear subspace clustering Open
In this paper we present a new model and an algorithm for unsupervised clustering of 2-D data such as images. We assume that the data comes from a union of multilinear subspaces (UOMS) model, which is a specific structured case of the much…