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Results for Predictive Alignment

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14 papers · ranked by Valyu relevance

01
PPubMed23 Jul 2025
Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks
Toshitake Asabuki, Claudia Clopath
Recurrent neural circuits often face inherent complexities in learning and generating their desired outputs, especially when they initially exhibit chaotic spontaneous activity. While the celebrated FORCE learning rule can train chaotic recurrent networks to produce coherent patterns by suppressing chaos, it requires…
83relevance
02
BbioRxiv17 Jul 2024
Taming the chaos gently: a Predictive Alignment learning rule in recurrent neural networks
Toshitake Asabuki, Claudia Clopath
Recurrent neural circuits often face inherent complexities in learning and generating their desired outputs, especially when they initially exhibit chaotic spontaneous activity. While the celebrated FORCE learning rule can train chaotic recurrent networks to produce coherent patterns by suppressing chaos, it requires…
81relevance
03
PPubMed4 Jul 2007
Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method
Morten Nielsen, Claus Lundegaard, Ole Lund
Background Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules.…
81relevance
04
BbioRxiv28 Apr 2022
ConsAlign: simultaneous RNA structural aligner based on rich transfer learning and thermodynamic ensemble model of alignment scoring
Masaki Tagashira
To capture structural homology in RNAs, predicting RNA structural alignments has been a fundamental framework around RNA science. Learning simultaneous RNA structural alignments in their rich scoring parameterization is an undeveloped subject because evaluating them is computationally expensive in nature. We developed…
76relevance
05
PPubMed24 Jan 2014
Sequence alignment by passing messages
Byung-Jun Yoon
Background Sequence alignment has become an indispensable tool in modern molecular biology research, and probabilistic sequence alignment models have been shown to provide an effective framework for building accurate sequence alignment tools. One such example is the pair hidden Markov model (pair-HMM), which has been…
74relevance
06
PPubMed28 Sep 2017
TurboFold II: RNA structural alignment and secondary structure prediction informed by multiple homologs
Zhen Tan, Yinghan Fu, Gaurav Sharma, David H. Mathews
This paper presents TurboFold II, an extension of the TurboFold algorithm for predicting secondary structures for multiple RNA homologs. TurboFold II augments the structure prediction capabilities of TurboFold by additionally providing multiple sequence alignments. Probabilities for alignment of nucleotide positions…
74relevance
07
PPubMed12 Mar 2024
Enhancing coevolutionary signals in protein–protein interaction prediction through clade-wise alignment integration
Tao Fang, Damian Szklarczyk, Radja Hachilif, Christian von Mering
Protein-protein interactions (PPIs) play essential roles in most biological processes. The binding interfaces between interacting proteins impose evolutionary constraints that have successfully been employed to predict PPIs from multiple sequence alignments (MSAs). To construct MSAs, critical choices have to be made…
73relevance
08
BbioRxiv30 Jul 2023
Clade-wise alignment integration improves co-evolutionary signals for protein-protein interaction prediction
Tao Fang, Damian Szklarczyk, Radja Hachilif, Christian von Mering
Protein-protein interactions play essential roles in almost all biological processes. The binding interfaces between interacting proteins impose evolutionary constraints, leading to co-evolutionary signals that have successfully been employed to predict protein interactions from multiple sequence alignments (MSAs).…
72relevance
09
PPubMed22 Nov 2024
Impact of Alignments on the Accuracy of Protein Subcellular Localization Predictions
Maryam Gillani, Gianluca Pollastri
Alignments in bioinformatics refer to the arrangement of sequences to identify regions of similarity that can indicate functional, structural, or evolutionary relationships. They are crucial for bioinformaticians as they enable accurate predictions and analyses in various applications, including protein subcellular…
72relevance
10
PPubMed1 Nov 2018
Motif-Aware PRALINE: Improving the alignment of motif regions MA-PRALINE: Motif-aware alignment
Maurits Dijkstra, Punto Bawono, Sanne Abeln, K. Anton Feenstra + 3 more
'Wan Fokkink' 'Jaap Heringa' 'Ilya Ioshikhes'] Protein or DNA motifs are sequence regions which possess biological importance. These regions are often highly conserved among homologous sequences. The generation of multiple sequence alignments (MSAs) with a correct alignment of the conserved sequence motifs is still…
71relevance
11
BbioRxiv5 Feb 2026
A deep-learning-based score to evaluate multiple sequence alignments
Nimrod Serok, Ksenia Polonsky, Haim Ashkenazy, Itay Mayrose + 2 more
Multiple sequence alignment (MSA) inference is a central task in molecular evolution and comparative genomics, and the reliability of downstream analyses, including phylogenetic inference, depends critically on alignment quality. Despite this importance, most widely used MSA methods optimize the sum-of-pairs (SP)…
71relevance
12
PPubMed1 Aug 2019
Tailor-made multiple sequence alignments using the PRALINE 2 alignment toolkit
Maurits J J Dijkstra, Atze J van der Ploeg, K Anton Feenstra, Wan J Fokkink + 3 more
Multiple sequence alignment (MSA) is one of the fundamental tasks in bioinformatics, essential to a wide variety of workflows, including fold prediction, phylogenetic analysis and mutation impact prediction. The exact solution with dynamic programming is not feasible for more than a handful of sequences. For protein…
71relevance
13
BbioRxiv15 Jan 2023
Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
Andreas Grigorjew, Artur Gynter, Fernando Dias, Benjamin Buchfink + 2 more
Sequence alignments have become the foundation of life science research by unlocking biological mechanisms through protein comparisons. Despite its methodological success, most algorithmic innovation in the past decades focused on the optimal alignment problem, while often ignoring information derived from suboptimal…
70relevance
14
BbioRxiv2 Jun 2016
Statistical inference of protein structural alignments using information and compression
James H. Collier, Lloyd Allison, Arthur M. Lesk, Peter J. Stuckey + 2 more
Structural molecular biology depends crucially on computational techniques that compare protein three-dimensional structures and generate structural alignments (the assignment of one-to-one correspondences between subsets of amino acids based on atomic coordinates.) Despite its importance, the structural alignment…
68relevance

Results for Predictive Alignment

Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks

Taming the chaos gently: a Predictive Alignment learning rule in recurrent neural networks

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

ConsAlign: simultaneous RNA structural aligner based on rich transfer learning and thermodynamic ensemble model of alignment scoring

Sequence alignment by passing messages

TurboFold II: RNA structural alignment and secondary structure prediction informed by multiple homologs

Enhancing coevolutionary signals in protein–protein interaction prediction through clade-wise alignment integration

Clade-wise alignment integration improves co-evolutionary signals for protein-protein interaction prediction

Impact of Alignments on the Accuracy of Protein Subcellular Localization Predictions

Motif-Aware PRALINE: Improving the alignment of motif regions MA-PRALINE: Motif-aware alignment

A deep-learning-based score to evaluate multiple sequence alignments

Tailor-made multiple sequence alignments using the PRALINE 2 alignment toolkit

Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD

Statistical inference of protein structural alignments using information and compression

Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks

Taming the chaos gently: a Predictive Alignment learning rule in recurrent neural networks

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

ConsAlign: simultaneous RNA structural aligner based on rich transfer learning and thermodynamic ensemble model of alignment scoring

Sequence alignment by passing messages

TurboFold II: RNA structural alignment and secondary structure prediction informed by multiple homologs

Enhancing coevolutionary signals in protein–protein interaction prediction through clade-wise alignment integration

Clade-wise alignment integration improves co-evolutionary signals for protein-protein interaction prediction

Impact of Alignments on the Accuracy of Protein Subcellular Localization Predictions

Motif-Aware PRALINE: Improving the alignment of motif regions MA-PRALINE: Motif-aware alignment

A deep-learning-based score to evaluate multiple sequence alignments

Tailor-made multiple sequence alignments using the PRALINE 2 alignment toolkit

Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD

Statistical inference of protein structural alignments using information and compression