Papers Multiple Sequence Alignment
“Multiple Sequence Alignment” 태그가 달린 논문 62편 · 필터 해제
Protein Structure Prediction: From Evolutionary Constraints to Generative Modeling
Accurate protein structure prediction is fundamental to structural biology because protein structure underlies molecular function and provides a basis for mechanistic interpretation. Recent advances in deep learning have…
Protein Structure PredictionMultiple Sequence AlignmentProtein DesignBoltzmann Machine Learning with a Parallel, Persistent Markov chain Monte Carlo method for Estimating Evolutionary Fields and Couplings from a Protein Multiple Sequence Alignment
The inverse Potts problem for estimating evolutionary single-site fields and pairwise couplings in homologous protein sequences from their single-site and pairwise amino acid frequencies observed in their multiple sequen…
Multiple Sequence AlignmentTraining-Free Generation of Protein Sequences from Small Family Alignments via Stochastic Attention
Generating novel protein sequences that respect a family's statistical constraints typically requires training deep generative models on thousands to millions of examples. Yet most protein families are small: the median …
Multiple Sequence AlignmentCharacterising Behavioural Families and Dynamics of Promotional Twitter Bots via Sequence-Based Modelling
This paper asks whether promotional Twitter/X bots form behavioural families and whether members evolve similarly. We analyse 2,798,672 tweets from 2,615 ground-truth promotional bot accounts (2006-2021), focusing on com…
Multiple Sequence AlignmentClassifying Metamorphic versus Single-Fold Proteins with Statistical Learning and AlphaFold2
The remarkable success of AlphaFold2 in providing accurate atomic-level prediction of protein structures from their amino acid sequence has transformed approaches to the protein folding problem. However, its core paradig…
Protein Structure PredictionMultiple Sequence AlignmentAI-based Methods for Simulating, Sampling, and Predicting Protein Ensembles
Advances in deep learning have opened an era of abundant and accurate predicted protein structures; however, similar progress in protein ensembles has remained elusive. This review highlights several recent research dire…
Multiple Sequence AlignmentAMix-1: A Pathway to Test-Time Scalable Protein Foundation Model
We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, encompassing pretraining scaling laws, emergent capability analysis, in-context…
Multiple Sequence AlignmentProtein DesignBeyond cognacy
Computational phylogenetics has become an established tool in historical linguistics, with many language families now analyzed using likelihood-based inference. However, standard approaches rely on expert-annotated cogna…
Multiple Sequence AlignmentRiemannian Time Warping: Multiple Sequence Alignment in Curved Spaces
Temporal alignment of multiple signals through time warping is crucial in many fields, such as classification within speech recognition or robot motion learning. Almost all related works are limited to data in Euclidean …
Multiple Sequence Alignmentspeech-recognitionSpeech RecognitionState-aware protein-ligand complex prediction using AlphaFold3 with purified sequences
Deep learning-based prediction of protein-ligand complexes has advanced significantly with the development of architectures such as AlphaFold3, Boltz-1, Chai-1, Protenix, and NeuralPlexer. Multiple sequence alignment (MS…
Multiple Sequence AlignmentCVTree for 16S rRNA: Constructing Taxonomy-Compatible All-Species Living Tree Effectively and Efficiently
The Composition Vector Tree (CVTree) method, developed under the leadership of Professor Hao Bailin, is an alignment-free algorithm for constructing phylogenetic trees. Although initially designed for studying prokaryoti…
AllMultiple Sequence AlignmentAdvanced Deep Learning Methods for Protein Structure Prediction and Design
After AlphaFold won the Nobel Prize, protein prediction with deep learning once again became a hot topic. We comprehensively explore advanced deep learning methods applied to protein structure prediction and design. It b…
Deep LearningMultiple Sequence AlignmentPredictionProtein Design+1Deep Time Warping for Multiple Time Series Alignment
Time Series Alignment is a critical task in signal processing with numerous real-world applications. In practice, signals often exhibit temporal shifts and scaling, making classification on raw data prone to errors. This…
Dynamic Time WarpingMultiple Sequence AlignmentTime SeriesTime Series AlignmentExpert-guided protein language models enable accurate and blazingly fast fitness prediction
Motivation Exhaustive experimental annotation of the effect of all known protein variants remains daunting and expensive, stressing the need for scalable effect predictions. We introduce VespaG, a blazingly fast missens…
CPUMultiple Sequence AlignmentProtein Language ModelContactNet: Geometric-Based Deep Learning Model for Predicting Protein-Protein Interactions
Deep learning approaches achieved significant progress in predicting protein structures. These methods are often applied to protein-protein interactions (PPIs) yet require Multiple Sequence Alignment (MSA) which is unava…
Graph Neural NetworkMultiple Sequence AlignmentPenSLR: Persian end-to-end Sign Language Recognition Using Ensembling
Sign Language Recognition (SLR) is a fast-growing field that aims to fill the communication gaps between the hearing-impaired and people without hearing loss. Existing solutions for Persian Sign Language (PSL) are limite…
Multiple Sequence AlignmentSentenceSign Language RecognitionMSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
Multiple Sequence Alignment (MSA) plays a pivotal role in unveiling the evolutionary trajectories of protein families. The accuracy of protein structure predictions is often compromised for protein sequences that lack su…
Few-Shot LearningMultiple Sequence AlignmentProtein Structure PredictionTransfer LearningESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
Protein-nucleic acid interactions play a very important role in a variety of biological activities. Accurate identification of nucleic acid-binding residues is a critical step in understanding the interaction mechanisms.…
Language ModelingLanguage ModellingMultiple Sequence AlignmentMulti-Task Learning+1Dynamic Programming Algorithms for Discovery of Antibiotic Resistance in Microbial Genomes
The translation of comparative genomics into clinical decision support tools often depends on the quality of sequence alignments. However, currently used methods of multiple sequence alignments suffer from significant bi…
Multiple Sequence AlignmentLinear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments
The aim of this study was to develop a method that would identify the cluster centroids and the optimal number of clusters for a given sensitivity level and could work equally well for the different sequence datasets. A …
ClusteringDimensionality ReductionMultiple Sequence Alignment