Opportunities and obstacles for deep learning in biology and medicine
T Ching, DS Himmelstein… - Journal of the …, 2018 - royalsocietypublishing.org
Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …
combining raw inputs into layers of intermediate features. These algorithms have recently …
Absence of a simple code: how transcription factors read the genome
Transcription factors (TFs) influence cell fate by interpreting the regulatory DNA within a
genome. TFs recognize DNA in a specific manner; the mechanisms underlying this …
genome. TFs recognize DNA in a specific manner; the mechanisms underlying this …
Predicting effects of noncoding variants with deep learning–based sequence model
J Zhou, OG Troyanskaya - Nature methods, 2015 - nature.com
Identifying functional effects of noncoding variants is a major challenge in human genetics.
To predict the noncoding-variant effects de novo from sequence, we developed a deep …
To predict the noncoding-variant effects de novo from sequence, we developed a deep …
Landscape of transcription in human cells
Eukaryotic cells make many types of primary and processed RNAs that are found either in
specific subcellular compartments or throughout the cells. A complete catalogue of these …
specific subcellular compartments or throughout the cells. A complete catalogue of these …
Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features
Oligomers of length k, or k-mers, are convenient and widely used features for modeling the
properties and functions of DNA and protein sequences. However, k-mers suffer from the …
properties and functions of DNA and protein sequences. However, k-mers suffer from the …
ChIPBase v2. 0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data
The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding
genes (PCGs) is contributed to various biological processes and linked with human …
genes (PCGs) is contributed to various biological processes and linked with human …
Machine learning for big data analytics in plants
Rapid advances in high-throughput genomic technology have enabled biology to enter the
era of 'Big Data'(large datasets). The plant science community not only needs to build its …
era of 'Big Data'(large datasets). The plant science community not only needs to build its …
Genomic regions flanking E-box binding sites influence DNA binding specificity of bHLH transcription factors through DNA shape
DNA sequence is a major determinant of the binding specificity of transcription factors (TFs)
for their genomic targets. However, eukaryotic cells often express, at the same time, TFs with …
for their genomic targets. However, eukaryotic cells often express, at the same time, TFs with …
High-throughput functional testing of ENCODE segmentation predictions
JC Kwasnieski, C Fiore, HG Chaudhari… - Genome …, 2014 - genome.cshlp.org
The histone modification state of genomic regions is hypothesized to reflect the regulatory
activity of the underlying genomic DNA. Based on this hypothesis, the ENCODE Project …
activity of the underlying genomic DNA. Based on this hypothesis, the ENCODE Project …
In pursuit of design principles of regulatory sequences
Instructions for when, where and to what level each gene should be expressed are encoded
within regulatory sequences. The importance of motifs recognized by DNA-binding …
within regulatory sequences. The importance of motifs recognized by DNA-binding …