Cargando…

Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction

Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The...

Descripción completa

Detalles Bibliográficos
Autores principales:	Khatun, Mst. Shamima, Shoombuatong, Watshara, Hasan, Md. Mehedi, Kurata, Hiroyuki
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Bentham Science Publishers 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536797/ https://www.ncbi.nlm.nih.gov/pubmed/33093807 http://dx.doi.org/10.2174/1389202921999200625103936

Ejemplares similares

i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes
por: Hasan, Md. Mehedi, et al.
Publicado: (2020)

Large-Scale Assessment of Bioinformatics Tools for Lysine Succinylation Sites
por: Hasan, Md. Mehedi, et al.
Publicado: (2019)

iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features
por: Hasan, Md. Mehedi, et al.
Publicado: (2020)

PUP-Fuse: Prediction of Protein Pupylation Sites by Integrating Multiple Sequence Representations
por: Auliah, Firda Nurul, et al.
Publicado: (2021)

PreAIP: Computational Prediction of Anti-inflammatory Peptides by Integrating Multiple Complementary Features
por: Khatun, Mst. Shamima, et al.
Publicado: (2019)

Computational identification of microbial phosphorylation sites by the enhanced characteristics of sequence information
por: Hasan, Md. Mehedi, et al.
Publicado: (2019)

PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features
por: Nilamyani, Andi Nur, et al.
Publicado: (2021)

NTyroSite: Computational Identification of Protein Nitrotyrosine Sites Using Sequence Evolutionary Features
por: Hasan, Md. Mehedi, et al.
Publicado: (2018)

Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins
por: Charoenkwan, Phasit, et al.
Publicado: (2022)

A systematic identification of species-specific protein succinylation sites using joint element features information
por: Hasan, Md Mehedi, et al.
Publicado: (2017)

SCORPION is a stacking-based ensemble learning framework for accurate prediction of phage virion proteins
por: Ahmad, Saeed, et al.
Publicado: (2022)

LSTM-PHV: prediction of human-virus protein–protein interactions by LSTM with word2vec
por: Tsukiyama, Sho, et al.
Publicado: (2021)

iBitter-Fuse: A Novel Sequence-Based Bitter Peptide Predictor by Fusing Multi-View Features
por: Charoenkwan, Phasit, et al.
Publicado: (2021)

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning
por: Charoenkwan, Phasit, et al.
Publicado: (2021)

Improved prediction and characterization of anticancer activities of peptides using a novel flexible scoring card method
por: Charoenkwan, Phasit, et al.
Publicado: (2021)

TargetAntiAngio: A Sequence-Based Tool for the Prediction and Analysis of Anti-Angiogenic Peptides
por: Laengsri, Vishuda, et al.
Publicado: (2019)

GPSuc: Global Prediction of Generic and Species-specific Succinylation Sites by aggregating multiple sequence features
por: Hasan, Md. Mehedi, et al.
Publicado: (2018)

ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides
por: Schaduangrat, Nalini, et al.
Publicado: (2019)

iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou’s 5-Steps Rule and Informative Physicochemical Properties
por: Charoenkwan, Phasit, et al.
Publicado: (2019)

Empirical comparison and analysis of machine learning-based approaches for druggable protein identification
por: Shoombuatong, Watshara, et al.
Publicado: (2023)

Prediction of serine phosphorylation sites mapping on Schizosaccharomyces Pombe by fusing three encoding schemes with the random forest classifier
por: Tasmia, Samme Amena, et al.
Publicado: (2022)

A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides
por: Charoenkwan, Phasit, et al.
Publicado: (2021)

CNN6mA: Interpretable neural network model based on position-specific CNN and cross-interactive network for 6mA site prediction
por: Tsukiyama, Sho, et al.
Publicado: (2022)

Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation
por: Schaduangrat, Nalini, et al.
Publicado: (2019)

PVPred-SCM: Improved Prediction and Analysis of Phage Virion Proteins Using a Scoring Card Method
por: Charoenkwan, Phasit, et al.
Publicado: (2020)

Correction: Shoombuatong, W., et al. iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou’s 5-Steps Rule and Informative Physicochemical Properties. Int. J. Mol. Sci. 2020, 21, 75
por: Charoenkwan, Phasit, et al.
Publicado: (2020)

Recent development of machine learning-based methods for the prediction of defensin family and subfamily
por: Charoenkwan, Phasit, et al.
Publicado: (2022)

Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework
por: Charoenkwan, Phasit, et al.
Publicado: (2022)

osFP: a web server for predicting the oligomeric states of fluorescent proteins
por: Simeon, Saw, et al.
Publicado: (2016)

Large-scale comparative review and assessment of computational methods for phage virion proteins identification
por: Kabir, Muhammad, et al.
Publicado: (2022)

AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking
por: Wisitponchai, Tanchanok, et al.
Publicado: (2017)

DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists
por: Schaduangrat, Nalini, et al.
Publicado: (2023)

Evolutionary trend of bovine β-defensin proteins toward functionality prediction: A domain-based bioinformatics study
por: Islam, Saiful, et al.
Publicado: (2023)

Prediction of aromatase inhibitory activity using the efficient linear method (ELM)
por: Shoombuatong, Watshara, et al.
Publicado: (2015)

TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus
por: Charoenkwan, Phasit, et al.
Publicado: (2023)

AMYPred-FRL is a novel approach for accurate prediction of amyloid proteins by using feature representation learning
por: Charoenkwan, Phasit, et al.
Publicado: (2022)

SCMCRYS: Predicting Protein Crystallization Using an Ensemble Scoring Card Method with Estimating Propensity Scores of P-Collocated Amino Acid Pairs
por: Charoenkwan, Phasit, et al.
Publicado: (2013)

Classification of P-glycoprotein-interacting compounds using machine learning methods
por: Prachayasittikul, Veda, et al.
Publicado: (2015)

The MicroRNA Interaction Network of Lipid Diseases
por: Kandhro, Abdul H., et al.
Publicado: (2017)

StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens
por: Charoenkwan, Phasit, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_o5i6dv54vcvrjdt3olor0i1tfg