An integration of deep learning with feature embedding for protein–protein interaction prediction

An Ensemble Classifier with Random Projection for Predicting Protein–Protein Interactions Using Sequence and Evolutionary Information

(2018) Xiao-Yu Song et al.   Applied Sciences-Basel

OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction

(2018) Fatima Zohra Smaili et al.   BIOINFORMATICS

PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein–Protein Interactions from Protein Sequences

(2017) Yanbin Wang et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

DeepPPI: Boosting Prediction of Protein–Protein Interactions with Deep Neural Networks

(2017) Xiuquan Du et al.   Journal of Chemical Information and Modeling

Detection of Interactions between Proteins by Using Legendre Moments Descriptor to Extract Discriminatory Information Embedded in PSSM

(2017) Yan-Bin Wang et al.   MOLECULES

Application of Artificial Neural Networks for Catalysis: A Review

(2017) Hao Li et al.   Catalysts

Predicting protein-protein interactions via multivariate mutual information of protein sequences

(2016) Yijie Ding et al.   BMC BIOINFORMATICS

Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence

(2015) Yu-An Huang et al.   Biomed Research International

Predicting Protein-Protein Interactions from Primary Protein Sequences Using a Novel Multi-Scale Local Feature Representation Scheme and the Random Forest

(2015) Zhu-Hong You et al.   PLoS One

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

(2015) Ehsaneddin Asgari et al.   PLoS One

repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects

(2014) Bin Liu et al.   BIOINFORMATICS

Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set

(2014) Zhu-Hong You et al.   BMC BIOINFORMATICS

Efficient prediction of human protein-protein interactions at a global scale

(2014) Andrew Schoenrock et al.   BMC BIOINFORMATICS

Sequence-based prediction of protein–protein interaction sites with L1-logreg classifier

(2014) Kaustubh Dhole et al.   JOURNAL OF THEORETICAL BIOLOGY

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

(2014) Masahito Ohue et al.   PROTEIN AND PEPTIDE LETTERS

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis

(2013) Zhu-Hong You et al.   BMC BIOINFORMATICS

Representation Learning: A Review and New Perspectives

(2013) Y. Bengio et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

(2013) Guilherme T. Valente et al.   PLoS One

A computational framework for boosting confidence in high-throughput protein-protein interaction datasets

(2013) Raghavendra Hosur et al.   GENOME BIOLOGY

Structure-based prediction of protein–protein interactions on a genome-wide scale

(2012) Qiangfeng Cliff Zhang et al.   NATURE

Flaws in evaluation schemes for pair-input computational predictions

(2012) Yungki Park et al.   NATURE METHODS

Templates are available to model nearly all complexes of structurally characterized proteins

(2012) P. J. Kundrotas et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Towards the prediction of protein interaction partners using physical docking

(2011) M. N. Wass et al.   Molecular Systems Biology

Applying the Naïve Bayes classifier with kernel density estimation to the prediction of protein–protein interaction sites

(2010) Yoichi Murakami et al.   BIOINFORMATICS

Large-scale prediction of protein-protein interactions from structures

(2010) Martial Hue et al.   BMC BIOINFORMATICS

iWRAP: An Interface Threading Approach with Application to Prediction of Cancer-Related Protein–Protein Interactions

(2010) Raghavendra Hosur et al.   JOURNAL OF MOLECULAR BIOLOGY

Prediction of Protein-Protein Interactions from Protein Sequence Using Local Descriptors

(2010) Lei Yang et al.   PROTEIN AND PEPTIDE LETTERS

Sequence-Based Prediction of Protein-Protein Interactions by Means of Rotation Forest and Autocorrelation Descriptor

(2009) Jun-Feng Xia et al.   PROTEIN AND PEPTIDE LETTERS

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

(2008) Lukas Burger et al.   Molecular Systems Biology

Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences

(2008) Yanzhi Guo et al.   NUCLEIC ACIDS RESEARCH