RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning
The majority of our human genome transcribes into noncoding RNAs with unknown
structures and functions. Obtaining functional clues for noncoding RNAs requires accurate …
structures and functions. Obtaining functional clues for noncoding RNAs requires accurate …
Probing RNA structures and functions by solvent accessibility: an overview from experimental and computational perspectives
Characterizing RNA structures and functions have mostly been focused on 2D, secondary
and 3D, tertiary structures. Recent advances in experimental and computational techniques …
and 3D, tertiary structures. Recent advances in experimental and computational techniques …
Advances in RNA 3D structure prediction
X Ou, Y Zhang, Y Xiong, Y Xiao - Journal of Chemical Information …, 2022 - ACS Publications
RNA molecules carry out various cellular functions, and understanding the mechanisms
behind their functions requires the knowledge of their 3D structures. Different types of …
behind their functions requires the knowledge of their 3D structures. Different types of …
Multiple sequence alignment-based RNA language model and its application to structural inference
Compared with proteins, DNA and RNA are more difficult languages to interpret because
four-letter coded DNA/RNA sequences have less information content than 20-letter coded …
four-letter coded DNA/RNA sequences have less information content than 20-letter coded …
Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning
Motivation The recent discovery of numerous non-coding RNAs (long non-coding RNAs, in
particular) has transformed our perception about the roles of RNAs in living organisms. Our …
particular) has transformed our perception about the roles of RNAs in living organisms. Our …
RLBind: a deep learning method to predict RNA–ligand binding sites
Identification of RNA–small molecule binding sites plays an essential role in RNA-targeted
drug discovery and development. These small molecules are expected to be leading …
drug discovery and development. These small molecules are expected to be leading …
RNAcmap: a fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis
Motivation The accuracy of RNA secondary and tertiary structure prediction can be
significantly improved by using structural restraints derived from evolutionary coupling or …
significantly improved by using structural restraints derived from evolutionary coupling or …
Probabilistic transformer: Modelling ambiguities and distributions for rna folding and molecule design
Our world is ambiguous and this is reflected in the data we use to train our algorithms. This
is particularly true when we try to model natural processes where collected data is affected …
is particularly true when we try to model natural processes where collected data is affected …
Synonymous variants that disrupt messenger RNA structure are significantly constrained in the human population
Background The role of synonymous single-nucleotide variants in human health and
disease is poorly understood, yet evidence suggests that this class of “silent” genetic …
disease is poorly understood, yet evidence suggests that this class of “silent” genetic …
Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network
Motivation RNA solvent accessibility, similar to protein solvent accessibility, reflects the
structural regions that are accessible to solvents or other functional biomolecules, and plays …
structural regions that are accessible to solvents or other functional biomolecules, and plays …