Cargando…

A critical analysis of computational protein design with sparse residue interaction graphs

Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the...

Descripción completa

Detalles Bibliográficos
Autores principales:	Jain, Swati, Jou, Jonathan D., Georgiev, Ivelin S., Donald, Bruce R.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2017
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391103/ https://www.ncbi.nlm.nih.gov/pubmed/28358804 http://dx.doi.org/10.1371/journal.pcbi.1005346

Ejemplares similares

Graph theory and sparse matrix computation
por: George, Alan, et al.
Publicado: (1993)

Algorithm for backrub motions in protein design
por: Georgiev, Ivelin, et al.
Publicado: (2008)

The Role of Local Backrub Motions in Evolved and Designed Mutations
por: Keedy, Daniel A., et al.
Publicado: (2012)

Fast Generation of Sparse Random Kernel Graphs
por: Hagberg, Aric, et al.
Publicado: (2015)

Sparse graphs using exchangeable random measures
por: Caron, François, et al.
Publicado: (2017)

Faster algorithms for counting subgraphs in sparse graphs
por: Bressan, Marco
Publicado: (2021)

Symposium on Sparse Matrix Computations
por: Bunch, James R, et al.
Publicado: (1976)

Cohesive subgraph computation over large sparse graphs: algorithms, data structures, and programming techniques
por: Chang, Lijun, et al.
Publicado: (2018)

Sparse Binary Relation Representations for Genome Graph Annotation
por: Karasikov, Mikhail, et al.
Publicado: (2020)

Fluctuations of extreme eigenvalues of sparse Erdős–Rényi graphs
por: He, Yukun, et al.
Publicado: (2021)

A residual dense network assisted sparse view reconstruction for breast computed tomography
por: Fu, Zhiyang, et al.
Publicado: (2020)

Exploiting ontology graph for predicting sparsely annotated gene function
por: Wang, Sheng, et al.
Publicado: (2015)

Mandala Networks: ultra-small-world and highly sparse graphs
por: Sampaio Filho, Cesar I. N., et al.
Publicado: (2015)

Graph Regularized Deep Sparse Representation for Unsupervised Anomaly Detection
por: Li, Shicheng, et al.
Publicado: (2021)

MBG: Minimizer-based sparse de Bruijn Graph construction
por: Rautiainen, Mikko, et al.
Publicado: (2021)

Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface
por: Lowegard, Anna U., et al.
Publicado: (2020)

GraphCPIs: A novel graph-based computational model for potential compound-protein interactions
por: Chen, Zhan-Heng, et al.
Publicado: (2023)

Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks
por: Pandey, Mohit, et al.
Publicado: (2022)

On the Sparse Beamformer Design
por: Gao, Mingjie, et al.
Publicado: (2018)

Structured sparse CCA for brain imaging genetics via graph OSCAR
por: Du, Lei, et al.
Publicado: (2016)

Ordering a Sparse Graph to Minimize the Sum of Right Ends of Edges
por: Damaschke, Peter
Publicado: (2020)

(p,q)-biclique counting and enumeration for large sparse bipartite graphs
por: Yang, Jianye, et al.
Publicado: (2023)

Iterated Clique Reductions in Vertex Weighted Coloring for Large Sparse Graphs
por: Fan, Yi, et al.
Publicado: (2023)

Deep fake detection using a sparse auto encoder with a graph capsule dual graph CNN
por: Kandasamy, Venkatachalam, et al.
Publicado: (2022)

GSAMDA: a computational model for predicting potential microbe–drug associations based on graph attention network and sparse autoencoder
por: Tan, Yaqin, et al.
Publicado: (2022)

Block-Diagonal Constrained Low-Rank and Sparse Graph for Discriminant Analysis of Image Data
por: Guo, Tan, et al.
Publicado: (2017)

Symposium on Sparse Matrix Computations
por: Duff, Iain S, et al.
Publicado: (1979)

Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics
por: Kansal, Raghav, et al.
Publicado: (2020)

Sparse Spatial-Temporal Emotion Graph Convolutional Network for Video Emotion Recognition
por: Liu, Xiaodong, et al.
Publicado: (2022)

Comparison of Graph Fitting and Sparse Deep Learning Model for Robot Pose Estimation
por: Rodziewicz-Bielewicz, Jan, et al.
Publicado: (2022)

Computing paths and cycles in biological interaction graphs
por: Klamt, Steffen, et al.
Publicado: (2009)

Identification of hot-spot residues in protein-protein interactions by computational docking
por: Grosdidier, Solène, et al.
Publicado: (2008)

Guiding protein design choices by per-residue energy breakdown analysis with an interactive web application
por: Engelberger, Felipe, et al.
Publicado: (2023)

Graph-based prediction of Protein-protein interactions with attributed signed graph embedding
por: Yang, Fang, et al.
Publicado: (2020)

Computational methods for general sparse matrices
por: Zlatev, Zahari
Publicado: (1991)

Interactive Art Design and Color Perception Based on the Sparse Network and the VR System
por: Wang, Lie, et al.
Publicado: (2022)

Hierarchical graph learning for protein–protein interaction
por: Gao, Ziqi, et al.
Publicado: (2023)

Accurate positioning of functional residues with robotics-inspired computational protein design
por: Krivacic, Cody, et al.
Publicado: (2022)

Prediction of Protein–Protein Interactions with Clustered Amino Acids and Weighted Sparse Representation
por: Huang, Qiaoying, et al.
Publicado: (2015)

Predicting residue‐specific qualities of individual protein models using residual neural networks and graph neural networks
por: Zhao, Chenguang, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_7so8amn9tsf0u67nu2pb4tft63