☆ 4.7 Article

Data Size and Quality Matter: Generating Physically-Realistic Distance Maps of Protein Tertiary Structures

BIOMOLECULES (2022)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Interdisciplinary Applications

Progressive assembly of multi-domain protein structures from cryo-EM density maps

Xiaogen Zhou et al.

Summary: Researchers have developed an automatic method called DEMO-EM, which combines rigid-body domain fitting and deep-neural-network inter-domain distance profiles to assemble and determine the structure of multi-domain proteins from cryo-electron microscopy maps.

NATURE COMPUTATIONAL SCIENCE (2022)

添加到收藏夹

Article Biochemistry & Molecular Biology

Generative Adversarial Learning of Protein Tertiary Structures

Taseef Rahman et al.

Summary: The study reveals that current GAN models struggle to capture complex structural patterns in protein molecules, and that mechanisms believed to stabilize training may not be effective. Additionally, performance based solely on loss may not correlate with the quality of generated datasets. The novel contribution of the study is the demonstration that Wasserstein GAN strikes a good balance in capturing both local and distal patterns in protein tertiary structures, paving the way for deeper generative models in exploring diverse protein activities.

MOLECULES (2021)

添加到收藏夹

Article Biochemistry & Molecular Biology

Generative deep learning for macromolecular structure and dynamics

Pourya Hoseini et al.

Summary: Scientific enquiries often rely on a mechanistic treatment of dynamic systems, linking form to function. Molecular biology emphasizes characterizing macromolecular structure and dynamics for a better understanding of biological processes in living cells. Computational biology researchers are now exploring deep neural networks as an alternative computational paradigm for generative models.

CURRENT OPINION IN STRUCTURAL BIOLOGY (2021)

添加到收藏夹

Article Biochemical Research Methods

Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks

Yang Li et al.

Summary: TripletRes is a novel deep-learning architecture for high-accuracy protein contact prediction, leveraging multiple evolutionary feature matrices extracted from whole-genome and metagenome databases to minimize information loss. It demonstrates competitive performance in large-scale benchmarks and blind tests, providing important medium- and long-range contact maps for guiding protein folding simulations.

PLOS COMPUTATIONAL BIOLOGY (2021)

添加到收藏夹

Article Multidisciplinary Sciences

Highly accurate protein structure prediction with AlphaFold

John Jumper et al.

Summary: Proteins are essential for life, and accurate prediction of their structures is a crucial research problem. Current experimental methods are time-consuming, highlighting the need for accurate computational approaches to address the gap in structural coverage. Despite recent progress, existing methods fall short of atomic accuracy in protein structure prediction.

NATURE (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Improved protein structure prediction by deep learning irrespective of co-evolution information

Jinbo Xu et al.

Summary: Recent advances in computational protein structure prediction have shown significant improvements by integrating deep learning and co-evolutionary analysis. Using ResNet, predictions of correct protein folds have been successful even without co-evolution information, suggesting potential for learning important protein sequence-structure relationships.

NATURE MACHINE INTELLIGENCE (2021)

添加到收藏夹

Article Biochemistry & Molecular Biology

Evaluating Autoencoder-Based Featurization and Supervised Learning for Protein Decoy Selection

Fardina Fathmiul Alam et al.

MOLECULES (2020)

添加到收藏夹

Article Biochemical Research Methods

SciPy 1.0: fundamental algorithms for scientific computing in Python

Pauli Virtanen et al.

NATURE METHODS (2020)

添加到收藏夹

Article Chemistry, Multidisciplinary

Predicting the Real-Valued Inter-Residue Distances for Proteins

Wenze Ding et al.

ADVANCED SCIENCE (2020)

添加到收藏夹

Article Chemistry, Multidisciplinary

Compact Spatial Pyramid Pooling Deep Convolutional Neural Network Based Hand Gestures Decoder

Akm Ashiquzzaman et al.

APPLIED SCIENCES-BASEL (2020)

添加到收藏夹

Article Computer Science, Information Systems

GANcon: Protein Contact Map Prediction With Deep Generative Adversarial Network

Hang Yang et al.

IEEE ACCESS (2020)

添加到收藏夹

Article Biochemistry & Molecular Biology

Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13

Jie Hou et al.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2019)

添加到收藏夹

Article Multidisciplinary Sciences

Distance-based protein folding powered by deep learning

Jinbo Xu

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

添加到收藏夹

Article Biochemical Research Methods

Structure-Guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm

Tatiana Maximova et al.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2018)

添加到收藏夹

Article Biochemistry & Molecular Biology

Assessment of model accuracy estimations in CASP12

Andriy Kryshtafovych et al.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2018)

添加到收藏夹

Article Biochemical Research Methods

From Optimization to Mapping: An Evolutionary Algorithm for Protein Energy Landscapes

Emmanuel Sapin et al.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2018)

添加到收藏夹

Article Biochemical Research Methods

Sample-Based Models of Protein Energy Landscapes and Slow Structural Rearrangements

Tatiana Maximova et al.

JOURNAL OF COMPUTATIONAL BIOLOGY (2018)

添加到收藏夹

Article Respiratory System

A general introduction to adjustment for multiple comparisons

Shi-Yi Chen et al.

JOURNAL OF THORACIC DISEASE (2017)

添加到收藏夹

Article Biotechnology & Applied Microbiology

Computing energy landscape maps and structural excursions of proteins

Emmanuel Sapin et al.

BMC GENOMICS (2016)

添加到收藏夹

Review Biochemical Research Methods

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Tatiana Maximova et al.

PLOS COMPUTATIONAL BIOLOGY (2016)

添加到收藏夹

Editorial Material Biochemical Research Methods

Computational Methods for Exploration and Analysis of Macromolecular Structure and Dynamics

Amarda Shehu et al.

PLOS COMPUTATIONAL BIOLOGY (2015)

添加到收藏夹

Article Biochemical Research Methods

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins

David T. Jones et al.

BIOINFORMATICS (2015)

添加到收藏夹

Article Social Sciences, Mathematical Methods

Nonparametric pairwise multiple comparisons in independent groups using Dunn's test

Alexis Dinno

STATA JOURNAL (2015)

添加到收藏夹

Article Biochemistry & Molecular Biology

The role of dynamic conformational ensembles in biomolecular recognition

David D. Boehr et al.

NATURE CHEMICAL BIOLOGY (2009)

添加到收藏夹

Article Multidisciplinary Sciences

Toward high-resolution de novo structure prediction for small proteins

P Bradley et al.

SCIENCE (2005)

添加到收藏夹

Letter Biochemistry & Molecular Biology

Announcing the worldwide Protein Data Bank

H Berman et al.

NATURE STRUCTURAL BIOLOGY (2003)

添加到收藏夹

Article Biochemical Research Methods

PISCES: a protein sequence culling server

GL Wang et al.

BIOINFORMATICS (2003)

添加到收藏夹

Article Computer Science, Artificial Intelligence

The Earth Mover's Distance as a metric for image retrieval

Y Rubner et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2000)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.