Cargando…

Unsupervised and Supervised Learning over the Energy Landscape for Protein Decoy Selection

The energy landscape that organizes microstates of a molecular system and governs the underlying molecular dynamics exposes the relationship between molecular form/structure, changes to form, and biological activity or function in the cell. However, several challenges stand in the way of leveraging...

Descripción completa

Detalles Bibliográficos
Autores principales:	Akhter, Nasrin, Chennupati, Gopinath, Kabir, Kazi Lutful, Djidjev, Hristo, Shehu, Amarda
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2019
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843838/ https://www.ncbi.nlm.nih.gov/pubmed/31615116 http://dx.doi.org/10.3390/biom9100607

Ejemplares similares

Decoy selection for protein structure prediction via extreme gradient boosting and ranking
por: Akhter, Nasrin, et al.
Publicado: (2020)

Graph-Based Community Detection for Decoy Selection in Template-Free Protein Structure Prediction
por: Kabir, Kazi Lutful, et al.
Publicado: (2019)

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction
por: Akhter, Nasrin, et al.
Publicado: (2018)

Evaluating Autoencoder-Based Featurization and Supervised Learning for Protein Decoy Selection
por: Alam, Fardina Fathmiul, et al.
Publicado: (2020)

Fewer Dimensions, More Structures for Improved Discrete Models of Dynamics of Free versus Antigen-Bound Antibody
por: Kabir, Kazi Lutful, et al.
Publicado: (2022)

From mutations to mechanisms and dysfunction via computation and mining of protein energy landscapes
por: Qiao, Wanli, et al.
Publicado: (2018)

HopDock: a probabilistic search algorithm for decoy sampling in protein-protein docking
por: Hashmi, Irina, et al.
Publicado: (2013)

Balancing multiple objectives in conformation sampling to control decoy diversity in template-free protein structure prediction
por: Zaman, Ahmed Bin, et al.
Publicado: (2019)

Attenuating dependence on structural data in computing protein energy landscapes
por: Morris, David, et al.
Publicado: (2019)

Computing energy landscape maps and structural excursions of proteins
por: Sapin, Emmanuel, et al.
Publicado: (2016)

GOProFormer: A Multi-Modal Transformer Method for Gene Ontology Protein Function Prediction
por: Kabir, Anowarul, et al.
Publicado: (2022)

An Estimate of the Numbers and Density of Low-Energy Structures (or Decoys) in the Conformational Landscape of Proteins
por: Vadivel, Kanagasabai, et al.
Publicado: (2009)

Supervised, semi-supervised and unsupervised inference of gene regulatory networks
por: Maetschke, Stefan R., et al.
Publicado: (2014)

Supervised and unsupervised learning for data science
por: Berry, Michael W, et al.
Publicado: (2020)

Sampling techniques for supervised or unsupervised tasks
por: Ros, édéric, et al.
Publicado: (2019)

Evolutionary-inspired probabilistic search for enhancing sampling of local minima in the protein energy surface
por: Olson, Brian S, et al.
Publicado: (2012)

Rapid sampling of local minima in protein energy surface and effective reduction through a multi-objective filter
por: Olson, Brian S, et al.
Publicado: (2013)

Parallel quantum annealing
por: Pelofske, Elijah, et al.
Publicado: (2022)

Quantitative neuronal morphometry by supervised and unsupervised learning
por: Bijari, Kayvan, et al.
Publicado: (2021)

Embedding Algorithms for Quantum Annealers with Chimera and Pegasus Connection Topologies
por: Zbinden, Stefanie, et al.
Publicado: (2020)

Semi-supervised and unsupervised machine learning: novel strategies
por: Albalate, Amparo, et al.
Publicado: (2011)

Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior
por: Gris, Katsiaryna V., et al.
Publicado: (2017)

Comparing supervised and unsupervised approaches to multimodal emotion recognition
por: Fernández Carbonell, Marcos, et al.
Publicado: (2021)

Supervised versus unsupervised approaches to classification of accelerometry data
por: Sur, Maitreyi, et al.
Publicado: (2023)

Effective Automated Feature Construction and Selection for Classification of Biological Sequences
por: Kamath, Uday, et al.
Publicado: (2014)

Towards an Optimized Ensemble Feature Selection for DDoS Detection Using Both Supervised and Unsupervised Method †
por: Saha, Sajal, et al.
Publicado: (2022)

Exploring supervised and unsupervised methods to detect topics in biomedical text
por: Lee, Minsuk, et al.
Publicado: (2006)

Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation
por: Khaligh-Razavi, Seyed-Mahdi, et al.
Publicado: (2014)

Effects of supervised and unsupervised physical activity programmes for weight loss
por: Creasy, S. A., et al.
Publicado: (2017)

Combining Supervised and Unsupervised Learning Algorithms for Human Activity Recognition
por: Budisteanu, Elena-Alexandra, et al.
Publicado: (2021)

Dissecting the Roles of Supervised and Unsupervised Learning in Perceptual Discrimination Judgments
por: Loewenstein, Yonatan, et al.
Publicado: (2021)

Integrating Deep Supervised, Self-Supervised and Unsupervised Learning for Single-Cell RNA-seq Clustering and Annotation
por: Chen, Liang, et al.
Publicado: (2020)

Decoys Selection in Benchmarking Datasets: Overview and Perspectives
por: Réau, Manon, et al.
Publicado: (2018)

Unsupervised Few-Shot Feature Learning via Self-Supervised Training
por: Ji, Zilong, et al.
Publicado: (2020)

Supervised and unsupervised language modelling in Chest X-Ray radiological reports
por: Drozdov, Ignat, et al.
Publicado: (2020)

Combining Unsupervised and Supervised Learning for Sample Efficient Continuous Language Grounding
por: Roesler, Oliver
Publicado: (2022)

Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection
por: Akrami, Haleh, et al.
Publicado: (2022)

DOES - A multimodal dataset for supervised and unsupervised analysis of steel scrap
por: Schäfer, Michael, et al.
Publicado: (2023)

Quantum annealing algorithms for Boolean tensor networks
por: Pelofske, Elijah, et al.
Publicado: (2022)

DecoyFinder, a tool for finding decoy molecules
por: Adrià, Cereto Massagué, et al.
Publicado: (2012)

Cannot write session to /tmp/vufind_sessions/sess_98utd7mjm7r1svuu8e75327a4f