• Publications
  • Influence
Clustering by Passing Messages Between Data Points
TLDR
Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Expand
  • 5,225
  • 509
  • PDF
Factor graphs and the sum-product algorithm
TLDR
In this tutorial paper, we present a generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph. Expand
  • 3,637
  • 276
  • PDF
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
  • 1,401
  • 139
  • PDF
A compendium of RNA-binding motifs for decoding gene regulation
TLDR
We report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. Expand
  • 964
  • 105
  • PDF
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
  • 2,864
  • 97
  • PDF
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
  • 380
  • 48
  • PDF
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
  • 785
  • 47
  • PDF
The "wake-sleep" algorithm for unsupervised neural networks.
TLDR
An unsupervised learning algorithm for a multilayer network of stochastic neurons is described. Expand
  • 909
  • 40
  • PDF
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
  • 725
  • 33
  • PDF
Graphical Models for Machine Learning and Digital Communication
  • B. Frey
  • Computer Science
  • 26 June 1998
TLDR
Probabilistic inference in graphical models pattern classification unsupervised learning data compression channel coding future research directions. Expand
  • 604
  • 32
  • PDF