Multiple Sequence Alignment
18 papers with code • 3 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Multiple Sequence Alignment
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Most implemented papers
Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations
idrori/cu-tsp
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Our dataset consists of amino acid sequences, Q8 secondary structures, position specific scoring matrices, multiple sequence alignment co-evolutionary features, backbone atom distance matrices, torsion angles, and 3D coordinates.
Phylogenetic automata, pruning, and multiple alignment
We present an extension of Felsenstein's algorithm to indel models defined on entire sequences, without the need to condition on one multiple alignment.
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation
magiccircuit/msa-augmentor
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The field of protein folding research has been greatly advanced by deep learning methods, with AlphaFold2 (AF2) demonstrating exceptional performance and atomic-level precision.
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
Meanwhile, the ESM-NBR obtains the MCC values for DNA-binding residues prediction of 0. 427 and 0. 391 on two independent test sets, which are 18. 61 and 10. 45% higher than those of the second-best methods, respectively.
Ultra-large alignments using Phylogeny-aware Profiles
Many biological questions, including the estimation of deep evolutionary histories and the detection of remote homology between protein sequences, rely upon multiple sequence alignments (MSAs) and phylogenetic trees of large datasets.
QuickProbs 2: towards rapid construction of high-quality alignments of large protein families
Increasing size of sequence databases caused by the development of high throughput sequencing, poses multiple alignment algorithms to face one of the greatest challenges yet.
Optimizing scoring function of dynamic programming of pairwise profile alignment using derivative free neural network
Nepal, the pairwise profile aligner with the novel scoring function significantly improved both alignment sensitivity and precision, compared to aligners with the existing functions.
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
For such complex tasks, the recently proposed RUDDER uses reward redistribution to leverage steps in the Q-function that are associated with accomplishing sub-tasks.
DLPAlign: A Deep Learning based Progressive Alignment Method for Multiple Protein Sequences
This paper proposed a novel and straightforward approach to improve the accuracy of progressive multiple protein sequence alignment method.
MSA Transformer
The-AI-Summer/self-attention-cv
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Unsupervised protein language models trained across millions of diverse sequences learn structure and function of proteins.
