Image de couverture de livre

RINAMI: Residue-attributed Interpretable Neural network for predicting Absolute folding free energy by Merging structure and sequence Information

Fuente: Zenodo

Enregistré dans:

Détails bibliographiques
Auteur principal:	Tomita, Naoki
Format:	Recurso digital
Publié:	Zenodo 2026
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Using recurrent neural networks to predict aspects of 3-D structure of folded copolymer sequences
par: Reilly, R. G., et autres
Publié: (2024)

Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
par: Frellsen, Jes, et autres
Publié: (2025)

Absolute zeta functions arising from ceiling and floor Puiseux polynomials
par: Hirakawa, Yoshinosuke, et autres
Publié: (2023)

SaeGraphDTI: drug-target interaction prediction based on sequence attribute extraction and graph neural network.
par: Zhang, Qiaosheng, et autres
Publié: (2025)

Selection originating from protein stability/foldability: Relationships between protein folding free energy, sequence ensemble, and fitness
par: Miyazawa, Sanzo
Publié: (2016)

On real algebraic realization of round fold maps of codimension $-1$
par: Kitazawa, Naoki
Publié: (2026)

Residual network improves the prediction accuracy of genomic selection
par: Huaxuan Wu, et autres
Publié: (2024)

Absolutely continuous representing measures of complex sequences
par: di Dio, Philipp J.
Publié: (2025)

Solvation free energy in governing equations for DNA hybridization, protein–ligand binding, and protein folding
par: Caroline Harmon, et autres
Publié: (2024)

Deep Model Merging: The Sister of Neural Network Interpretability -- A Survey
par: Khan, Arham, et autres
Publié: (2024)

Zero-energy modes in super-chiral nanographene networks of phenalenyl-tessellation molecules
par: Morishita, Naoki, et autres
Publié: (2021)

Design of low-energy transfers in cislunar space using sequences of lobe dynamics
par: Hiraiwa, Naoki, et autres
Publié: (2026)

Predicting protein folding dynamics using sequence information
par: Galpern, Ezequiel A., et autres
Publié: (2025)

Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction
par: Chakravarty, Devlina, et autres
Publié: (2024)

Improving link prediction accuracy of network embedding algorithms via rich node attribute information
par: Gu, Weiwei, et autres
Publié: (2024)

Cell culture product quality attribute prediction using convolutional neural networks and Raman spectroscopy
par: Hamid Khodabandehlou, et autres
Publié: (2024)

Longitudinal loneliness changes are associated with cognitive decline and brain structure alterations: evidence from the Whitehall II cohort study
par: Ye Zhang, et autres
Publié: (2024)

Longitudinal loneliness changes are associated with cognitive decline and brain structure alterations: evidence from the Whitehall II cohort study
par: Ye Zhang, et autres
Publié: (2024)

Real-Aware Residual Model Merging for Deepfake Detection
par: Park, Jinhee, et autres
Publié: (2025)

Crystal structure prediction with nuclear quantum and finite-temperature effects via deep free energy learning
par: Wang, Xiaoyang, et autres
Publié: (2026)

Inferring protein folding mechanisms from natural sequence diversity
par: Galpern, Ezequiel A., et autres
Publié: (2024)

Neural network prediction of model parameters for strong lensing samples from Hyper Suprime-Cam Survey
par: Gawade, Priyanka, et autres
Publié: (2024)

Scalable 3D Registration via Truncated Entry-wise Absolute Residuals
par: Huang, Tianyu, et autres
Publié: (2024)

Accelerated structure-stability energy-free calculator
par: Boucher, Alexandre, et autres
Publié: (2024)

RankMerging: A supervised learning-to-rank framework to predict links in large social network
par: Tabourier, Lionel, et autres
Publié: (2014)

Training-free Heterogeneous Model Merging
par: Xu, Zhengqi, et autres
Publié: (2024)

Efficient aerodynamic coefficients prediction with a long sequence neural network
par: Cai, Zemin, et autres
Publié: (2024)

Unavailability of experimental 3D structural data on protein folding dynamics and necessity for a new generation of structure prediction methods in this context
par: Wells, Aydin, et autres
Publié: (2025)

Making ends meet or just meeting at the ends? Assessing end-to-end distance in folded RNA sequences and other branched structures
par: Greenwood, Torin, et autres
Publié: (2026)

Co-folding model guided by structural proteomics
par: Shtrikman, Alon, et autres
Publié: (2026)

Flexible inference in heterogeneous and attributed multilayer networks
par: Contisciani, Martina, et autres
Publié: (2024)

Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation
par: Nagahisa, Haruto, et autres
Publié: (2026)

Interpretable machine learned predictions of adsorption energies at the metal--oxide interface
par: Nielsen, Marius Juul, et autres
Publié: (2025)

Penalty-free quantum optimization applied to lattice protein folding
par: Gellsersen, Leif, et autres
Publié: (2026)

Ideals of equations for elements in a free group and Stallings folding
par: Ascari, Dario
Publié: (2022)

Prime Fano $4$-folds with semi-free torus actions
par: Lindsay, Nicholas
Publié: (2025)

Interpretable attributed scattering center extracted via deep unfolding
par: Yang, Haodong, et autres
Publié: (2024)

New data on opioid use disorder and risk of overdose in adolescent and young adult disease‐free survivors prescribed opioids after cancer treatment
par: Natalie Moryl, et autres
Publié: (2025)

LiteToken: Removing Intermediate Merge Residues From BPE Tokenizers
par: Sun, Yike, et autres
Publié: (2026)

Model-free prediction of multistability using echo state network
par: Roy, Mousumi, et autres
Publié: (2022)