Cargando…

Prediction of aptamer-protein interacting pairs using an ensemble classifier in combination with various protein sequence attributes

BACKGROUND: Aptamer-protein interacting pairs play a variety of physiological functions and therapeutic potentials in organisms. Rapidly and effectively predicting aptamer-protein interacting pairs is significant to design aptamers binding to certain interested proteins, which will give insight into...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zhang, Lina, Zhang, Chengjin, Gao, Rui, Yang, Runtao, Song, Qing
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2016
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4888498/ https://www.ncbi.nlm.nih.gov/pubmed/27245069 http://dx.doi.org/10.1186/s12859-016-1087-5

Ejemplares similares

An Effective Antifreeze Protein Predictor with Ensemble Classifiers and Comprehensive Sequence Descriptors
por: Yang, Runtao, et al.
Publicado: (2015)

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy
por: Zhang, Lina, et al.
Publicado: (2016)

An Ensemble Method to Distinguish Bacteriophage Virion from Non-Virion Proteins Based on Protein Sequence Characteristics
por: Zhang, Lina, et al.
Publicado: (2015)

An Ensemble Method with Hybrid Features to Identify Extracellular Matrix Proteins
por: Yang, Runtao, et al.
Publicado: (2015)

JPPRED: Prediction of Types of J-Proteins from Imbalanced Data Using an Ensemble Learning Method
por: Zhang, Lina, et al.
Publicado: (2015)

Using a Classifier Fusion Strategy to Identify Anti-angiogenic Peptides
por: Zhang, Lina, et al.
Publicado: (2018)

A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data
por: Yang, Runtao, et al.
Publicado: (2016)

iEnhancer-GAN: A Deep Learning Framework in Combination with Word Embedding and Sequence Generative Adversarial Net to Identify Enhancers and Their Strength
por: Yang, Runtao, et al.
Publicado: (2021)

Predicting aptamer sequences that interact with target proteins using an aptamer-protein interaction classifier and a Monte Carlo tree search approach
por: Lee, Gwangho, et al.
Publicado: (2021)

An Ensemble Classifier to Predict Protein–Protein Interactions by Combining PSSM-based Evolutionary Information with Local Binary Pattern Model
por: Li, Yang, et al.
Publicado: (2019)

A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers
por: Lyu, Yanfen, et al.
Publicado: (2020)

A deep learning framework combined with word embedding to identify DNA replication origins
por: Wu, Feng, et al.
Publicado: (2021)

A Two-Step Feature Selection Method to Predict Cancerlectins by Multiview Features and Synthetic Minority Oversampling Technique
por: Yang, Runtao, et al.
Publicado: (2018)

XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
por: Min, Hui, et al.
Publicado: (2022)

Recognition of protein/gene names from text using an ensemble of classifiers
por: Zhou, GuoDong, et al.
Publicado: (2005)

Protein ligand-specific binding residue predictions by an ensemble classifier
por: Hu, Xiuzhen, et al.
Publicado: (2016)

Performance of rotation forest ensemble classifier and feature extractor in predicting protein interactions using amino acid sequences
por: Bustamam, Alhadi, et al.
Publicado: (2019)

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble
por: Zhang, Bailing, et al.
Publicado: (2011)

Prediction of protein long-range contacts using an ensemble of genetic algorithm classifiers with sequence profile centers
por: Chen, Peng, et al.
Publicado: (2010)

Hierarchical Classification of Protein Folds Using a Novel Ensemble Classifier
por: Lin, Chen, et al.
Publicado: (2013)

Ensemble of Multiple Classifiers for Multilabel Classification of Plant Protein Subcellular Localization
por: Wattanapornprom, Warin, et al.
Publicado: (2021)

An Ensemble Learning-Based Method for Inferring Drug-Target Interactions Combining Protein Sequences and Drug Fingerprints
por: Zhao, Zheng-Yang, et al.
Publicado: (2021)

Combining classifiers for improved classification of proteins from sequence or structure
por: Melvin, Iain, et al.
Publicado: (2008)

Quantum ensembles of quantum classifiers
por: Schuld, Maria, et al.
Publicado: (2018)

KUPS: constructing datasets of interacting and non-interacting protein pairs with associated attributions
por: Chen, Xue-wen, et al.
Publicado: (2011)

Human Protein Subcellular Localization with Integrated Source and Multi-label Ensemble Classifier
por: Guo, Xiaotong, et al.
Publicado: (2016)

Ensemble of Template-Free and Template-Based Classifiers for Protein Secondary Structure Prediction
por: de Oliveira, Gabriel Bianchin, et al.
Publicado: (2021)

Stack-VTP: prediction of vesicle transport proteins based on stacked ensemble classifier and evolutionary information
por: Chen, Yu, et al.
Publicado: (2023)

iPPBS-Opt: A Sequence-Based Ensemble Classifier for Identifying Protein-Protein Binding Sites by Optimizing Imbalanced Training Datasets
por: Jia, Jianhua, et al.
Publicado: (2016)

Prediction of Aptamer-Target Interacting Pairs with Pseudo-Amino Acid Composition
por: Li, Bi-Qing, et al.
Publicado: (2014)

An ensemble machine learning model based on multiple filtering and supervised attribute clustering algorithm for classifying cancer samples
por: Bose, Shilpi, et al.
Publicado: (2021)

Carbon Nanofiber-Ionic Liquid Nanocomposite Modified Aptasensors Developed for Electrochemical Investigation of Interaction of Aptamer/Aptamer–Antisense Pair with Activated Protein C
por: Maral, Meltem, et al.
Publicado: (2023)

Protein DEK and DTA Aptamers: Insight Into the Interaction Mechanisms and the Computational Aptamer Design
por: Dai, Lijun, et al.
Publicado: (2022)

Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM
por: Gao, Zhen-Guo, et al.
Publicado: (2016)

An ensemble approach for large-scale identification of protein-protein interactions using the alignments of multiple sequences
por: Wang, Lei, et al.
Publicado: (2016)

Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains
por: Bulashevska, Alla, et al.
Publicado: (2006)

ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble Classifier
por: Chen, Daozheng, et al.
Publicado: (2016)

Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes
por: Pourreza Shahri, Morteza, et al.
Publicado: (2021)

Predicting Protein–Protein Interactions Based on Ensemble Learning-Based Model from Protein Sequence
por: Zhan, Xinke, et al.
Publicado: (2022)

An Ensemble Classifier for Eukaryotic Protein Subcellular Location Prediction Using Gene Ontology Categories and Amino Acid Hydrophobicity
por: Li, Liqi, et al.
Publicado: (2012)

Cannot write session to /tmp/vufind_sessions/sess_bqp767fle00b9kevb57clnu8hk