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PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features

Scientific reports, 2023-11, Vol.13 (1), p.20882-20882, Article 20882

2023

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CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks

Gene, 2023-02, Vol.853, p.147045-147045, Article 147045

2023

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A convolutional neural network based tool for predicting protein AMPylation sites from binary profile representation

Scientific reports, 2022-07, Vol.12 (1), p.11451-11451, Article 11451

2022

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Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer

BMC bioinformatics, 2022-04, Vol.23 (1), p.138-138, Article 138

2022

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Pan-cancer integrative analysis of whole-genome De novo somatic point mutations reveals 17 cancer types

BMC bioinformatics, 2022-07, Vol.23 (1), p.1-298, Article 298

2022

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New Multi-View Feature Learning Method for Accurate Antifungal Peptide Detection

Algorithms, 2024-06, Vol.17 (6), p.247

2024

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Accurate brain tumor detection using deep convolutional neural network

Computational and structural biotechnology journal, 2022-01, Vol.20, p.4733-4745

2022

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Interocular Symmetry Analysis of Corneal Elevation Using the Fellow Eye as the Reference Surface and Machine Learning

Healthcare (Basel), 2021-12, Vol.9 (12), p.1738

2021

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Bioionic Liquids: Enabling a Paradigm Shift Toward Advanced and Smart Biomedical Applications

Advanced intelligent systems, 2023-05, Vol.5 (5), p.n/a

2023

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Programmable bio-ionic liquid functionalized hydrogels for in situ 3D bioprinting of electronics at the tissue interface

Materials today advances, 2023-03, Vol.17, p.100352, Article 100352

2023

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Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

Informatics in medicine unlocked, 2023, Vol.42, p.101348, Article 101348

2023

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Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods

Informatics in medicine unlocked, 2023, Vol.40, p.101286, Article 101286

2023

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A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Frontiers in public health, 2022-06, Vol.10, p.869238-869238

2022

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Predicting lysine methylation sites using a convolutional neural network

Methods (San Diego, Calif.), 2024-06, Vol.226, p.127-132

2024

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DeepPhoPred : Accurate Deep Learning Model to Predict Microbial Phosphorylation

Proteins, structure, function, and bioinformatics, 2024-09

2024

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iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features

Methods in molecular biology (Clifton, N.J.), 2022, Vol.2499, p.125

2022

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Correction to: SleepBoost: a multi‑level tree‑based ensemble model for automatic sleep stage classification

Medical & biological engineering & computing, 2024-09, Vol.62 (9), p.2785-2785

2024

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SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classification

Medical & biological engineering & computing, 2024-09, Vol.62 (9), p.2769-2783

2024

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Accurately predicting microbial phosphorylation sites using evolutionary and structural features

Gene, 2023-01, Vol.851, p.146993-146993, Article 146993

2023

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Accurately predicting nitrosylated tyrosine sites using probabilistic sequence information

Gene, 2022-06, Vol.826, p.146445-146445, Article 146445

2022

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A critical review of the impact of candidate copy number variants on autism spectrum disorder

Mutation research. Reviews in mutation research, 2024-07, Vol.794, p.108509, Article 108509

2024

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Explainable Machine Learning Model to Accurately Predict Protein-Binding Peptides

Algorithms, 2024-09, Vol.17 (9), p.409

2024

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MethEvo: an accurate evolutionary information-based methylation site predictor

Neural computing & applications, 2024, Vol.36 (1), p.201-212

2024

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Multimodal and Explainable Android Adware Classification Techniques

The International FLAIRS Conference Proceedings, 2024-05, Vol.37

2024

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Predicting Phosphoglycerylation with Transformer Features and Deep Learning

2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), 2023, p.1-6

2023

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PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features

CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks

A convolutional neural network based tool for predicting protein AMPylation sites from binary profile representation

Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer

Pan-cancer integrative analysis of whole-genome De novo somatic point mutations reveals 17 cancer types

New Multi-View Feature Learning Method for Accurate Antifungal Peptide Detection

Accurate brain tumor detection using deep convolutional neural network

Interocular Symmetry Analysis of Corneal Elevation Using the Fellow Eye as the Reference Surface and Machine Learning

Bioionic Liquids: Enabling a Paradigm Shift Toward Advanced and Smart Biomedical Applications

Programmable bio-ionic liquid functionalized hydrogels for in situ 3D bioprinting of electronics at the tissue interface

Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Predicting lysine methylation sites using a convolutional neural network

DeepPhoPred : Accurate Deep Learning Model to Predict Microbial Phosphorylation

iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features

Correction to: SleepBoost: a multi‑level tree‑based ensemble model for automatic sleep stage classification

SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classification

Accurately predicting microbial phosphorylation sites using evolutionary and structural features

Accurately predicting nitrosylated tyrosine sites using probabilistic sequence information

A critical review of the impact of candidate copy number variants on autism spectrum disorder

Explainable Machine Learning Model to Accurately Predict Protein-Binding Peptides

MethEvo: an accurate evolutionary information-based methylation site predictor

Multimodal and Explainable Android Adware Classification Techniques

Predicting Phosphoglycerylation with Transformer Features and Deep Learning

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