Cargando…

GTB-PPI: Predict Protein–protein Interactions Based on L1-regularized Logistic Regression and Gradient Tree Boosting

Protein–protein interactions (PPIs) are of great importance to understand genetic mechanisms, delineate disease pathogenesis, and guide drug design. With the increase of PPI data and development of machine learning technologies, prediction and identification of PPIs have become a research hotspot in...

Descripción completa

Detalles Bibliográficos
Autores principales:	Yu, Bin, Chen, Cheng, Zhou, Hongyan, Liu, Bingqiang, Ma, Qin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2020
Materias:	Method
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377384/ https://www.ncbi.nlm.nih.gov/pubmed/33515750 http://dx.doi.org/10.1016/j.gpb.2021.01.001

Ejemplares similares

Gradient boosted trees with individual explanations: An alternative to logistic regression for viability prediction in the first trimester of pregnancy
por: Vaulet, Thibaut, et al.
Publicado: (2022)

GTB – an online genome tolerance browser
por: Shihab, Hashem A., et al.
Publicado: (2017)

RGBM: regularized gradient boosting machines for identification of the transcriptional regulators of discrete glioma subtypes
por: Mall, Raghvendra, et al.
Publicado: (2018)

Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data
por: Seto, Hiroe, et al.
Publicado: (2022)

PredRSA: a gradient boosted regression trees approach for predicting protein solvent accessibility
por: Fan, Chao, et al.
Publicado: (2016)

PredPRBA: Prediction of Protein-RNA Binding Affinity Using Gradient Boosted Regression Trees
por: Deng, Lei, et al.
Publicado: (2019)

Author Correction: Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data
por: Seto, Hiroe, et al.
Publicado: (2022)

Primer on binary logistic regression
por: Harris, Jenine K
Publicado: (2021)

Supporting Regularized Logistic Regression Privately and Efficiently
por: Li, Wenfa, et al.
Publicado: (2016)

Multi-label ℓ(2)-regularized logistic regression for predicting activation/inhibition relationships in human protein-protein interaction networks
por: Mei, Suyu, et al.
Publicado: (2016)

Identification of cyclin protein using gradient boost decision tree algorithm
por: Zulfiqar, Hasan, et al.
Publicado: (2021)

Logistic regression with image covariates via the combination of L(1) and Sobolev regularizations
por: An, Baiguo, et al.
Publicado: (2020)

Adaptive group-regularized logistic elastic net regression
por: Münch, Magnus M, et al.
Publicado: (2019)

Continuous outcome logistic regression for analyzing body mass index distributions
por: Lohse, Tina, et al.
Publicado: (2017)

Regularized sequence-context mutational trees capture variation in mutation rates across the human genome
por: Adams, Christopher J., et al.
Publicado: (2023)

A computational framework for boosting confidence in high-throughput protein-protein interaction datasets
por: Hosur, Raghavendra, et al.
Publicado: (2012)

Early prediction of clinical scores for left ventricular reverse remodeling using extreme gradient random forest, boosting, and logistic regression algorithm representations
por: Liu, Lu, et al.
Publicado: (2022)

Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
por: Hafemeister, Christoph, et al.
Publicado: (2019)

CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model
por: Wang, Liguo, et al.
Publicado: (2013)

Comprehensible Predictive Modeling Using Regularized Logistic Regression and Comorbidity Based Features
por: Stiglic, Gregor, et al.
Publicado: (2015)

Development and Validation of Models to Predict Lymph Node Metastasis in Early Gastric Cancer Using Logistic Regression and Gradient Boosting Machine Methods
por: Lee, Hae Dong, et al.
Publicado: (2023)

Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L(1/2 +2) Regularization
por: Huang, Hai-Hui, et al.
Publicado: (2016)

Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method
por: Wang, Fen, et al.
Publicado: (2023)

Identification of miRNA biomarkers for breast cancer by combining ensemble regularized multinomial logistic regression and Cox regression
por: Li, Juntao, et al.
Publicado: (2022)

Regularized logistic regression with network-based pairwise interaction for biomarker identification in breast cancer
por: Wu, Meng-Yun, et al.
Publicado: (2016)

Computing Leapfrog Regularization Paths with Applications to Large-Scale K-mer Logistic Regression
por: Benner, Philipp
Publicado: (2021)

How common is patient and public involvement (PPI)? Cross-sectional analysis of frequency of PPI reporting in health research papers and associations with methods, funding sources and other factors
por: Lang, Iain, et al.
Publicado: (2022)

Logistic Model and Gradient Boosting Machine Model for Physical Therapy of Lumbar Disc Herniation
por: Zhao, Ping, et al.
Publicado: (2022)

ShapeGTB: the role of local DNA shape in prioritization of functional variants in human promoters with machine learning
por: Malkowska, Maja, et al.
Publicado: (2018)

Predicting β-Turns in Protein Using Kernel Logistic Regression
por: Elbashir, Murtada Khalafallah, et al.
Publicado: (2013)

Stable variable ranking and selection in regularized logistic regression for severely imbalanced big binary data
por: Nadeem, Khurram, et al.
Publicado: (2023)

Logistic regression trees for initial selection of interesting loci in case-control studies
por: Nickolov, Radoslav Z, et al.
Publicado: (2007)

The Bradley–Terry Regression Trunk approach for Modeling Preference Data with Small Trees
por: Baldassarre, Alessio, et al.
Publicado: (2022)

Protein functional properties prediction in sparsely-label PPI networks through regularized non-negative matrix factorization
por: Wu, Qingyao, et al.
Publicado: (2015)

Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree
por: Zhou, Chang, et al.
Publicado: (2017)

Applied logistic regression
por: Hosmer, David W, et al.
Publicado: (2013)

Applied logistic regression /
por: Hosmer, David W.
Publicado: (2000)

Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
por: Nhu, Viet-Ha, et al.
Publicado: (2020)

Biomarker discovery for predicting spontaneous preterm birth from gene expression data by regularized logistic regression
por: Li, Lingyu, et al.
Publicado: (2020)

Integrating PPI datasets with the PPI data from biomedical literature for protein complex detection
por: Yang, Zhi Hao, et al.
Publicado: (2014)

Cannot write session to /tmp/vufind_sessions/sess_gl1of3bjmeur6k3g3rdleo44f8