Obtaining genetics insights from deep learning via explainable artificial intelligence
Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …
for making functional predictions in genomics research. However, the underlying basis on …
Artificial intelligence aids in development of nanomedicines for cancer management
P Tan, X Chen, H Zhang, Q Wei, K Luo - Seminars in cancer biology, 2023 - Elsevier
Over the last decade, the nanomedicine has experienced unprecedented development in
diagnosis and management of diseases. A number of nanomedicines have been approved …
diagnosis and management of diseases. A number of nanomedicines have been approved …
Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution
Genomic (DNA) sequences encode an enormous amount of information for gene regulation
and protein synthesis. Similar to natural language models, researchers have proposed …
and protein synthesis. Similar to natural language models, researchers have proposed …
[HTML][HTML] Effective gene expression prediction from sequence by integrating long-range interactions
How noncoding DNA determines gene expression in different cell types is a major unsolved
problem, and critical downstream applications in human genetics depend on improved …
problem, and critical downstream applications in human genetics depend on improved …
The evolution, evolvability and engineering of gene regulatory DNA
Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal
phenotype and fitness,–. Constructing complete fitness landscapes, in which DNA …
phenotype and fitness,–. Constructing complete fitness landscapes, in which DNA …
[HTML][HTML] CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores
Background Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate
synthesis of human proteins. Genetic variants impacting splicing underlie a substantial …
synthesis of human proteins. Genetic variants impacting splicing underlie a substantial …
[HTML][HTML] Multimodal deep learning models for early detection of Alzheimer's disease stage
Most current Alzheimer's disease (AD) and mild cognitive disorders (MCI) studies use single
data modality to make predictions such as AD stages. The fusion of multiple data modalities …
data modality to make predictions such as AD stages. The fusion of multiple data modalities …
Big bird: Transformers for longer sequences
Transformers-based models, such as BERT, have been one of the most successful deep
learning models for NLP. Unfortunately, one of their core limitations is the quadratic …
learning models for NLP. Unfortunately, one of their core limitations is the quadratic …
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Motivation Deciphering the language of non-coding DNA is one of the fundamental
problems in genome research. Gene regulatory code is highly complex due to the existence …
problems in genome research. Gene regulatory code is highly complex due to the existence …
Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes
J Schwartzentruber, S Cooper, JZ Liu… - Nature …, 2021 - nature.com
Genome-wide association studies have discovered numerous genomic loci associated with
Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We …
Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We …