Multiple Sequence Alignment
16 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.
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.
Algorithms and Complexity on Indexing Founder Graphs
We study the problem of matching a string in a labeled graph.
MNHN-Tree-Tools: a toolbox for tree inference using multi-scale clustering of a set of sequences
We introduce MNHN-Tree-Tools, a high performance set of algorithms that builds multi-scale, nested clusters of sequences found in a FASTA file.
