• Publications
  • Influence
Deciphering the splicing code
TLDR
We propose a splicing code that uses combinations of hundreds of RNA features to predict tissue-dependent changes in alternative splicing for thousands of exons. Expand
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Modeling dependencies in protein-DNA binding sites
TLDR
We explore Bayesian network representations of transcription factor binding sites that provide different tradeoffs between complexity (number of parameters) and richness of dependencies between positions. Expand
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A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites
TLDR
A central issue in molecular biology is understanding the regulatory mechanisms that control gene expression. Expand
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From promoter sequence to expression: a probabilistic framework
TLDR
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Expand
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Outlier detection for improved differential splicing quantification from RNA-Seq experiments with replicates
TLDR
We develop a probability model to weigh a given RNA-Seq sample as a representative of an experimental condition when performing alternative splicing analysis. Expand
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Context-Specific Bayesian Clustering for Gene Expression Data
TLDR
We present a class of mathematical models that help in understanding the connections between transcription factors and functional classes of genes based on genetic and genomic data and a new search method that rapidly learns a model according to a Bayesian score. Expand
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Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays
TLDR
We combine two kinds of tests to assess the effect of an SQ algorithm in terms of signal to noise ratio. Expand
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Integrative deep models for alternative splicing
TLDR
We address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors. Expand
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Context-specific Bayesian clustering for gene expression data
TLDR
The recent growth in genomic data and measurement of genome-wide expression patterns allows to examine gene regulation by transcription factors using computational tools. Expand
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Bayesian prediction of tissue-regulated splicing using RNA sequence and cellular context
TLDR
We formulate the assembly of a splicing code as a problem of statistical inference and introduce a Bayesian method that uses an adaptively selected number of hidden variables to combine subgroups of features into a network, allows different tissues to share feature subgroups and uses a Gibbs sampler to hedge the statistical significance of identified features. Expand
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