AIMC Topic: Regulatory Sequences, Nucleic Acid
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Deciphering the regulatory syntax of genomic DNA with deep learning.
Journal of biosciences
Jan 1, 2022
An organism's genome contains many sequence regions that perform diverse functions. Examples of such regions include genes, promoters, enhancers, and binding sites for regulatory proteins and RNAs. One of biology's most important open problems is how...
TempoMAGE: a deep learning framework that exploits the causal dependency between time-series data to predict histone marks in open chromatin regions at time-points with missing ChIP-seq datasets.
Bioinformatics (Oxford, England)
Dec 7, 2021
MOTIVATION: Identifying histone tail modifications using ChIP-seq is commonly used in time-series experiments in development and disease. These assays, however, cover specific time-points leaving intermediate or early stages with missing information....
Interpreting machine learning models to investigate circadian regulation and facilitate exploration of clock function.
Proceedings of the National Academy of Sciences of the United States of America
Aug 10, 2021
The circadian clock is an important adaptation to life on Earth. Here, we use machine learning to predict complex, temporal, and circadian gene expression patterns in Most significantly, we classify circadian genes using DNA sequence features genera...
DeepATT: a hybrid category attention neural network for identifying functional effects of DNA sequences.
Briefings in bioinformatics
May 20, 2021
Quantifying DNA properties is a challenging task in the broad field of human genomics. Since the vast majority of non-coding DNA is still poorly understood in terms of function, this task is particularly important to have enormous benefit for biology...
Sequence-Based Deep Learning Frameworks on Enhancer-Promoter Interactions Prediction.
Current pharmaceutical design
Jan 1, 2021
Enhancer-promoter interactions (EPIs) in the human genome are of great significance to transcriptional regulation, which tightly controls gene expression. Identification of EPIs can help us better decipher gene regulation and understand disease mecha...
Identifying enhancer-promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism.
Bioinformatics (Oxford, England)
Feb 15, 2020
MOTIVATION: Identification of enhancer-promoter interactions (EPIs) is of great significance to human development. However, experimental methods to identify EPIs cost too much in terms of time, manpower and money. Therefore, more and more research ef...
Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.
Bioinformatics (Oxford, England)
Jan 15, 2020
MOTIVATION: Interactions among cis-regulatory elements such as enhancers and promoters are main driving forces shaping context-specific chromatin structure and gene expression. Although there have been computational methods for predicting gene expres...
Convolutional neural network model to predict causal risk factors that share complex regulatory features.
Nucleic acids research
Dec 16, 2019
Major progress in disease genetics has been made through genome-wide association studies (GWASs). One of the key tasks for post-GWAS analyses is to identify causal noncoding variants with regulatory function. Here, on the basis of >2000 functional fe...
TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes.
Nucleic acids research
Aug 22, 2019
Genome-wide association studies (GWAS) associate single nucleotide polymorphisms (SNPs) to complex phenotypes. Most human SNPs fall in non-coding regions and are likely regulatory SNPs, but linkage disequilibrium (LD) blocks make it difficult to dist...
DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learning.
Nucleic acids research
Jun 4, 2019
Interactions between regulatory elements are of crucial importance for the understanding of transcriptional regulation and the interpretation of disease mechanisms. Hi-C technique has been developed for genome-wide detection of chromatin contacts. Ho...
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