Cargando…

Protein Design with Deep Learning

Computational Protein Design (CPD) has produced impressive results for engineering new proteins, resulting in a wide variety of applications. In the past few years, various efforts have aimed at replacing or improving existing design methods using Deep Learning technology to leverage the amount of p...

Descripción completa

Detalles Bibliográficos
Autores principales:	Defresne, Marianne, Barbe, Sophie, Schiex, Thomas
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584038/ https://www.ncbi.nlm.nih.gov/pubmed/34769173 http://dx.doi.org/10.3390/ijms222111741

Ejemplares similares

Protein design via deep learning
por: Ding, Wenze, et al.
Publicado: (2022)

Deep Learning in Protein Structural Modeling and Design
por: Gao, Wenhao, et al.
Publicado: (2020)

A Comparative Study to Decipher the Structural and Dynamics Determinants Underlying the Activity and Thermal Stability of GH-11 Xylanases
por: Vucinic, Jelena, et al.
Publicado: (2021)

LeARN: a platform for detecting, clustering and annotating non-coding RNAs
por: Noirot, Céline, et al.
Publicado: (2008)

From sequence to function through structure: Deep learning for protein design
por: Ferruz, Noelia, et al.
Publicado: (2022)

Deep learning of protein sequence design of protein–protein interactions
por: Syrlybaeva, Raulia, et al.
Publicado: (2022)

Computational Protein Design with Deep Learning Neural Networks
por: Wang, Jingxue, et al.
Publicado: (2018)

Integrating alternative splicing detection into gene prediction
por: Foissac, Sylvain, et al.
Publicado: (2005)

Computational design of symmetrical eight-bladed β-propeller proteins
por: Noguchi, Hiroki, et al.
Publicado: (2019)

Improving de novo protein binder design with deep learning
por: Bennett, Nathaniel R., et al.
Publicado: (2023)

Principles and practice of constraint programming: 25th international conference, CP 2019, Stamford, CT, USA, September 30 - october 4, 2019, proceedings
por: Schiex, Thomas, et al.
Publicado: (2019)

A review on machine learning and deep learning for various antenna design applications
por: Khan, Mohammad Monirujjaman, et al.
Publicado: (2022)

Robust deep learning based protein sequence design using ProteinMPNN
por: Dauparas, J., et al.
Publicado: (2022)

Detecting long tandem duplications in genomic sequences
por: Audemard, Eric, et al.
Publicado: (2012)

Unsupervised Learning in Drug Design from Self-Organization to Deep Chemistry
por: Polanski, Jaroslaw
Publicado: (2022)

Deep learning frameworks for protein–protein interaction prediction
por: Hu, Xiaotian, et al.
Publicado: (2022)

Recent Progress in the Discovery and Design of Antimicrobial Peptides Using Traditional Machine Learning and Deep Learning
por: Yan, Jielu, et al.
Publicado: (2022)

Deep learning approaches for conformational flexibility and switching properties in protein design
por: Rudden, Lucas S. P., et al.
Publicado: (2022)

FrameDP: sensitive peptide detection on noisy matured sequences
por: Gouzy, Jérôme, et al.
Publicado: (2009)

Deep Learning-Based Advances in Protein Structure Prediction
por: Pakhrin, Subash C., et al.
Publicado: (2021)

Protein–protein interaction prediction with deep learning: A comprehensive review
por: Soleymani, Farzan, et al.
Publicado: (2022)

Deep learning methods in protein structure prediction
por: Torrisi, Mirko, et al.
Publicado: (2020)

Deep learning in prediction of intrinsic disorder in proteins
por: Zhao, Bi, et al.
Publicado: (2022)

Clinical Situations in Which the Diagnosis of Autism is Debatable: An Analysis and Recommendations
por: Defresne, Pierre, et al.
Publicado: (2021)

Protein–RNA interaction prediction with deep learning: structure matters
por: Wei, Junkang, et al.
Publicado: (2021)

Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
por: Wilman, Wiktoria, et al.
Publicado: (2022)

Molecular de-novo design through deep reinforcement learning
por: Olivecrona, Marcus, et al.
Publicado: (2017)

Recent Advances in Deep Learning for Protein-Protein Interaction Analysis: A Comprehensive Review
por: Lee, Minhyeok
Publicado: (2023)

Deep Learning for Novel Antimicrobial Peptide Design
por: Wang, Christina, et al.
Publicado: (2021)

DeepCRISPR: optimized CRISPR guide RNA design by deep learning
por: Chuai, Guohui, et al.
Publicado: (2018)

In silico evolution of protein binders with deep learning models for structure prediction and sequence design
por: Goudy, Odessa J, et al.
Publicado: (2023)

Deep metabolome: Applications of deep learning in metabolomics
por: Pomyen, Yotsawat, et al.
Publicado: (2020)

Deep Learning in Proteomics
por: Wen, Bo, et al.
Publicado: (2020)

Deep learning for protein secondary structure prediction: Pre and post-AlphaFold
por: Ismi, Dewi Pramudi, et al.
Publicado: (2022)

Universal Approach to De Novo Drug Design for Target Proteins Using Deep Reinforcement Learning
por: Zhang, Yunjiang, et al.
Publicado: (2023)

Deep reinforcement learning for de novo drug design
por: Popova, Mariya, et al.
Publicado: (2018)

Plasmonic nanostructure design and characterization via Deep Learning
por: Malkiel, Itzik, et al.
Publicado: (2018)

Packaging Design Based on Deep Learning and Image Enhancement
por: Liu, Jinping
Publicado: (2022)

Deep learning for non-parameterized MEMS structural design
por: Guo, Ruiqi, et al.
Publicado: (2022)

Designing Deep Learning Hardware Accelerator and Efficiency Evaluation
por: Qi, Zhi, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_7fojf1e8s6ggap9dp2e2gpt1op