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Comparative Study of Single-stranded Oligonucleotides Secondary Structure Prediction Tools
BackgroundSingle-stranded nucleic acids (ssNAs) have important biological roles and a high biotechnological potential linked to their ability to bind...
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REDfold: accurate RNA secondary structure prediction using residual encoder-decoder network
BackgroundAs the RNA secondary structure is highly related to its stability and functions, the structure prediction is of great value to biological...
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Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials
Pseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present...
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RNA Secondary Structure Thermodynamics
Several different ways to predict RNA secondary structures have been suggested in the literature. Statistical methods, such as those that utilize...
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AttSec: protein secondary structure prediction by capturing local patterns from attention map
BackgroundProtein secondary structures that link simple 1D sequences to complex 3D structures can be used as good features for describing the local...
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Modified Nucleotides and RNA Structure Prediction
Nucleotide modifications are occurrent in all types of RNA and play an important role in RNA structure formation and stability. Modified bases not...
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LTPConstraint: a transfer learning based end-to-end method for RNA secondary structure prediction
BackgroundRNA secondary structure is very important for deciphering cell’s activity and disease occurrence. The first method which was used by the...
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Phylogenetic Information as Soft Constraints in RNA Secondary Structure Prediction
Pseudo-energies are a generic method to incorporate extrinsic information into energy-directed RNA secondary structure predictions. Consensus...
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RNA Secondary Structure Modeling Following the IPANEMAP Workflow
The structure of RNA molecules and their complexes are crucial for understanding biology at the molecular level. Resolving these structures holds the...
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AI-Assisted Methods for Protein Structure Prediction and Analysis
Proteins are the workhorses of cells. Their sequence is determined by the genetic code embedded in the DNA, which translates it faithfully into a...
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Deep Learning Approach to Identify Protein’s Secondary Structure Elements
Cryo-electron microscopy (cryo-EM) has become a crucial method for structure determination. Despite the substantial growth in deposited cryo-EM maps...
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The Multiscale Ernwin/SPQR RNA Structure Prediction Pipeline
Aside from the well-known role in protein synthesis, RNA can perform catalytic, regulatory, and other essential biological functions which are...
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Lightweight ProteinUnet2 network for protein secondary structure prediction: a step towards proper evaluation
BackgroundThe prediction of protein secondary structures is a crucial and significant step for ab initio tertiary structure prediction which delivers...
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RNA secondary structure prediction with convolutional neural networks
BackgroundPredicting the secondary, i.e. base-pairing structure of a folded RNA strand is an important problem in synthetic and computational...
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Estimating RNA Secondary Structure Folding Free Energy Changes with efn2
A number of analyses require estimates of the folding free energy changes of specific RNA secondary structures. These predictions are often based on...
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Secondary structure specific simpler prediction models for protein backbone angles
MotivationProtein backbone angle prediction has achieved significant accuracy improvement with the development of deep learning methods. Usually the...
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System Biology and Protein Structure Prediction by Computer
In the twenty-first century, whole-genome sequencing has become possible, and the amino acid sequence of all proteins can be revealed by genome...
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Prediction of plant secondary metabolic pathways using deep transfer learning
BackgroundPlant secondary metabolites are highly valued for their applications in pharmaceuticals, nutrition, flavors, and aesthetics. It is of great...
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Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data
Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single-...
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RNA secondary structure packages evaluated and improved by high-throughput experiments
Despite the popularity of computer-aided study and design of RNA molecules, little is known about the accuracy of commonly used structure modeling...
