TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection

DeepFusion: A deep learning based multi-scale feature fusion method for predicting drug-target interactions

(2022) Tao Song et al.   METHODS

Modality-DTA: Multimodality Fusion Strategy for Drug–Target Affinity Prediction

(2022) Xixi Yang et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

PreDTIs: prediction of drug–target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques

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Prediction of drug–target binding affinity using similarity-based convolutional neural network

(2021) Jooyong Shim et al.   Scientific Reports

SGANRDA: semi-supervised generative adversarial networks for predicting circRNA–disease associations

(2021) Lei Wang et al.   BRIEFINGS IN BIOINFORMATICS

DNN-DTIs: Improved drug-target interactions prediction using XGBoost feature selection and deep neural network

(2021) Cheng Chen et al.   COMPUTERS IN BIOLOGY AND MEDICINE

NMFCDA: Combining randomization-based neural network with non-negative matrix factorization for predicting CircRNA-disease association

(2021) Lei Wang et al.   APPLIED SOFT COMPUTING

Deep learning in retrosynthesis planning: datasets, models and tools

(2021) Jingxin Dong et al.   BRIEFINGS IN BIOINFORMATICS

Biomedical data and computational models for drug repositioning: a comprehensive review

(2020) Huimin Luo et al.   BRIEFINGS IN BIOINFORMATICS

GANsDTA: Predicting Drug-Target Binding Affinity Using GANs

(2020) Lingling Zhao et al.   Frontiers in Genetics

A deep learning-based method for drug-target interaction prediction based on long short-term memory neural network

(2020) Yan-Bin Wang et al.   BMC Medical Informatics and Decision Making

A novel fusion based on the evolutionary features for protein fold recognition using support vector machines

(2020) Mohammad Saleh Refahi et al.   Scientific Reports

DeepACTION: A deep learning-based method for predicting novel drug-target interactions

(2020) S.M. Hasan Mahmud et al.   ANALYTICAL BIOCHEMISTRY

DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks

(2019) Mostafa Karimi et al.   BIOINFORMATICS

Binding affinity in drug design: experimental and computational techniques

(2019) Visvaldas Kairys et al.   Expert Opinion on Drug Discovery

Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold

(2019) Martin Steinegger et al.   NATURE METHODS

Predicting Protein-Protein Interactions from Matrix-Based Protein Sequence Using Convolution Neural Network and Feature-Selective Rotation Forest

(2019) Lei Wang et al.   Scientific Reports

Gradient Boosting Decision Tree-Based Method for Predicting Interactions Between Target Genes and Drugs

(2019) Ping Xuan et al.   Frontiers in Genetics

Prediction of drug-target interaction based on protein features using undersampling and feature selection techniques with boosting

(2019) S.M. Hasan Mahmud et al.   ANALYTICAL BIOCHEMISTRY

OUP accepted manuscript

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Multimodal Machine Learning: A Survey and Taxonomy

(2018) Tadas Baltrusaitis et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

(2018) Sabrina Jaeger et al.   Journal of Chemical Information and Modeling

1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

(2018) Osama Abdeljaber et al.   NEUROCOMPUTING

Clustering huge protein sequence sets in linear time

(2018) Martin Steinegger et al.   Nature Communications

Machine Learning on Human Muscle Transcriptomic Data for Biomarker Discovery and Tissue-Specific Drug Target Identification

(2018) Polina Mamoshina et al.   Frontiers in Genetics

Prediction of Drug–Gene Interaction by Using Metapath2vec

(2018) Siyi Zhu et al.   Frontiers in Genetics

Predicting tumor cell line response to drug pairs with deep learning

(2018) Fangfang Xia et al.   BMC BIOINFORMATICS

Deep-Learning-Based Drug–Target Interaction Prediction

(2017) Ming Wen et al.   JOURNAL OF PROTEOME RESEARCH

SimBoost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines

(2017) Tong He et al.   Journal of Cheminformatics

Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks

(2016) Serkan Kiranyaz et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

An ensemble approach for large-scale identification of protein- protein interactions using the alignments of multiple sequences

(2016) Lei Wang et al.   Oncotarget

Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

(2015) Junshui Ma et al.   Journal of Chemical Information and Modeling

Deep learning

(2015) Yann LeCun et al.   NATURE

ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation

(2015) Jie Dong et al.   Journal of Cheminformatics

Toward more realistic drug-target interaction predictions

(2014) T. Pahikkala et al.   BRIEFINGS IN BIOINFORMATICS

Making Sense of Large-Scale Kinase Inhibitor Bioactivity Data Sets: A Comparative and Integrative Analysis

(2014) Jing Tang et al.   Journal of Chemical Information and Modeling

Some case studies on application of “rm2” metrics for judging quality of quantitative structure-activity relationship predictions: Emphasis on scaling of response data

(2013) Kunal Roy et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Chapter 4: Protein Interactions and Disease

(2012) Mileidy W. Gonzalez et al.   PLoS Computational Biology

Comprehensive analysis of kinase inhibitor selectivity

(2011) Mindy I Davis et al.   NATURE BIOTECHNOLOGY

Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile

(2010) Taigang Liu et al.   BIOCHIMIE

PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints

(2010) Chun Wei Yap   JOURNAL OF COMPUTATIONAL CHEMISTRY

How to improve R&D productivity: the pharmaceutical industry's grand challenge

(2010) Steven M. Paul et al.   NATURE REVIEWS DRUG DISCOVERY

A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation

(2009) Qiwen Dong et al.   BIOINFORMATICS

pGenTHREADER and pDomTHREADER: new methods for improved protein fold recognition and superfamily discrimination

(2009) Anna Lobley et al.   BIOINFORMATICS

On Two Novel Parameters for Validation of Predictive QSAR Models

(2009) Partha Pratim Roy et al.   MOLECULES