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Clustering by Passing Messages Between Data Points
Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Expand
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Factor graphs and the sum-product algorithm
In this tutorial paper, we present a generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph. Expand
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Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
Knowing the sequence specificities of DNA- and RNA-binding proteins is essential for developing models of the regulatory processes in biological systems and for identifying causal disease variants.Expand
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A compendium of RNA-binding motifs for decoding gene regulation
We report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. Expand
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Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing
We carried out the first analysis of alternative splicing complexity in human tissues using mRNA-Seq data. New splice junctions were detected in ∼20% of multiexon genes, many of which are tissueExpand
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Widespread intron retention in mammals functionally tunes transcriptomes.
Alternative splicing (AS) of precursor RNAs is responsible for greatly expanding the regulatory and functional capacity of eukaryotic genomes. Of the different classes of AS, intron retention (IR) isExpand
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The human splicing code reveals new insights into the genetic determinants of disease
Predicting defects in RNA splicing Most eukaryotic messenger RNAs (mRNAs) are spliced to remove introns. Splicing generates uninterrupted open reading frames that can be translated into proteins.Expand
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The "wake-sleep" algorithm for unsupervised neural networks.
An unsupervised learning algorithm for a multilayer network of stochastic neurons is described. Expand
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The Evolutionary Landscape of Alternative Splicing in Vertebrate Species
Whence Species Variation? Vertebrates have widely varying phenotypes that are at odds with their much more limited proteincoding genotypes and conserved messenger RNA expression patterns. Genes withExpand
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Graphical Models for Machine Learning and Digital Communication
  • B. Frey
  • Computer Science
  • 26 June 1998
Probabilistic inference in graphical models pattern classification unsupervised learning data compression channel coding future research directions. Expand
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