Fuyi Li

According to our database1, Fuyi Li authored at least 57 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins.
Comput. Biol. Medicine, September, 2023

TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters.
Briefings Bioinform., July, 2023

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities.
Briefings Bioinform., July, 2023

ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species.
Briefings Bioinform., May, 2023

ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning.
Briefings Bioinform., March, 2023

VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants.
Briefings Bioinform., January, 2023

Prediction of Multiple Types of RNA Modifications via Biological Language Model.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

Towards Self-Interpretable Graph-Level Anomaly Detection.
CoRR, 2023

<i>iFeatureOmega: </i> an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets.
Nucleic Acids Res., 2022

PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations.
J. Chem. Inf. Model., 2022

PreAcrs: a machine learning framework for identifying anti-CRISPR proteins.
BMC Bioinform., 2022

DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions.
Bioinform., 2022

Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction.
Briefings Bioinform., 2022

ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning.
Briefings Bioinform., 2022

RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins.
Briefings Bioinform., 2022

Positive-unlabeled learning in bioinformatics and computational biology: a brief review.
Briefings Bioinform., 2022

Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations.
Briefings Bioinform., 2022

HEAL: an automated deep learning framework for cancer histopathology image analysis.
Bioinform., November, 2021

A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Formator: Predicting Lysine Formylation Sites Based on the Most Distant Undersampling and Safe-Level Synthetic Minority Oversampling.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data.
Frontiers Big Data, 2021

Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features.
Briefings Bioinform., 2021

Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.
Briefings Bioinform., 2021

Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I molecules.
Briefings Bioinform., 2021

DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.
Briefings Bioinform., 2021

Porpoise: a new approach for accurate prediction of RNA pseudouridine sites.
Briefings Bioinform., 2021

Computational prediction and interpretation of both general and specific types of promoters in Escherichia coli by exploiting a stacked ensemble-learning framework.
Briefings Bioinform., 2021

Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations.
Briefings Bioinform., 2021

Systematic evaluation of machine learning methods for identifying human-pathogen protein-protein interactions.
Briefings Bioinform., 2021

A data-driven bioinformatic investigation into protein post-translational modifications.
PhD thesis, 2020

Pippin: A random forest-based method for identifying presynaptic and postsynaptic neurotoxins.
J. Bioinform. Comput. Biol., 2020

PROSPECT: A web server for predicting protein histidine phosphorylation sites.
J. Bioinform. Comput. Biol., 2020

Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information.
Genom. Proteom. Bioinform., 2020

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.
Bioinform., 2020

PASSION: an ensemble neural network approach for identifying the binding sites of RBPs on circRNAs.
Bioinform., 2020

Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms.
Briefings Bioinform., 2020

A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction.
Briefings Bioinform., 2020

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.
Briefings Bioinform., 2020

Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences.
Briefings Bioinform., 2020

iLearn : an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.
Briefings Bioinform., 2020

Stability of synchronized steady state solution of diffusive Lotka-Volterra predator-prey model.
Appl. Math. Lett., 2020

SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models.
BMC Bioinform., 2019

Positive-unlabelled learning of glycosylation sites in the human proteome.
BMC Bioinform., 2019

MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters.
Bioinform., 2019

iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites.
Briefings Bioinform., 2019

Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods.
Briefings Bioinform., 2019

Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.
Briefings Bioinform., 2019

Existence of nontrivial solutions for Kirchhoff-type problems with jumping nonlinearities.
Appl. Math. Lett., 2019

PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.
Bioinform., 2018

Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.
Bioinform., 2018

iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences.
Bioinform., 2018

Global solutions and blow up solutions to a class of pseudo-parabolic equations with nonlocal term.
Appl. Math. Comput., 2018

GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.
Bioinform., 2015

Existence of multiple positive solutions to nonhomogeneous Schrödinger-Poisson system.
Appl. Math. Comput., 2015

Multiple sign-changing solutions to the Sturm-Liouville boundary value problem with resonance.
Appl. Math. Comput., 2012

Existence of positive periodic solutions to nonlinear second order differential equations.
Appl. Math. Lett., 2005

Multiple symmetric nonnegative solutions of second-order ordinary differential equations.
Appl. Math. Lett., 2004