Jiangning Song
Orcid: 0000-0001-8031-9086
According to our database1,
Jiangning Song
authored at least 142 papers
between 2006 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
BMC Bioinform., December, 2024
PLANNER: A Multi-Scale Deep Language Model for the Origins of Replication Site Prediction.
IEEE J. Biomed. Health Informatics, April, 2024
Improving Cancer Survival Prediction via Graph Convolutional Neural Network Learning on Protein-Protein Interaction Networks.
IEEE J. Biomed. Health Informatics, February, 2024
TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion.
J. Chem. Inf. Model., February, 2024
PmxPred: A data-driven approach for the identification of active polymyxin analogues against gram-negative bacteria.
Comput. Biol. Medicine, January, 2024
GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference.
Briefings Bioinform., January, 2024
Histo-Genomic Knowledge Distillation For Cancer Prognosis From Histopathology Whole Slide Images.
CoRR, 2024
2023
Genetic algorithm-based feature selection with manifold learning for cancer classification using microarray data.
BMC Bioinform., December, 2023
Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues.
Bioinform., December, 2023
Surformer: An interpretable pattern-perceptive survival transformer for cancer survival prediction from histopathology whole slide images.
Comput. Methods Programs Biomed., November, 2023
Deep domain adversarial neural network for the deconvolution of cell type mixtures in tissue proteome profiling.
Nat. Mac. Intell., October, 2023
Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins.
Comput. Biol. Medicine, September, 2023
MULGA, a unified multi-view graph autoencoder-based approach for identifying drug-protein interaction and drug repositioning.
Bioinform., 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
TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level.
Briefings Bioinform., May, 2023
ATTIC is an integrated approach for predicting A-to-I RNA editing sites in three species.
Briefings Bioinform., May, 2023
Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification.
Bioinform., March, 2023
PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships.
Bioinform., March, 2023
ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning.
Briefings Bioinform., March, 2023
PScL-2LSAESM: bioimage-based prediction of protein subcellular localization by integrating heterogeneous features with the two-level SAE-SM and mean ensemble method.
Bioinform., January, 2023
Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire.
Briefings Bioinform., January, 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
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
Multi-modality data-driven analysis of diagnosis and treatment of psoriatic arthritis.
npj Digit. Medicine, 2023
2022
MSNet-4mC: learning effective multi-scale representations for identifying DNA N4-methylcytosine sites.
Bioinform., November, 2022
csORF-finder: an effective ensemble learning framework for accurate identification of multi-species coding short open reading frames.
Briefings Bioinform., November, 2022
Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent.
IEEE J. Biomed. Health Informatics, 2022
<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
Enhancing Characteristic Gene Selection and Tumor Classification by the Robust Laplacian Supervised Discriminative Sparse PCA.
J. Chem. Inf. Model., 2022
PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations.
J. Chem. Inf. Model., 2022
Multiplex-detection Based Multiple Instance Learning Network for Whole Slide Image Classification.
CoRR, 2022
Multi-channel deep convolutional neural networks for multi-classifying thyroid disease.
CoRR, 2022
A multi-channel deep convolutional neural network for multi-classifying thyroid diseases.
Comput. Biol. Medicine, 2022
BMC Bioinform., 2022
DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images.
Bioinform., 2022
PScL-DDCFPred: an ensemble deep learning-based approach for characterizing multiclass subcellular localization of human proteins from bioimage data.
Bioinform., 2022
DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions.
Bioinform., 2022
T4SEfinder: a bioinformatics tool for genome-scale prediction of bacterial type IV secreted effectors using pre-trained protein language model.
Briefings 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
PCfun: a hybrid computational framework for systematic characterization of protein complex function.
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
MAResNet: predicting transcription factor binding sites by combining multi-scale bottom-up and top-down attention and residual network.
Briefings Bioinform., 2022
Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion.
Briefings Bioinform., 2022
Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations.
Briefings Bioinform., 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
Bioinform., November, 2021
Computational identification of eukaryotic promoters based on cascaded deep capsule neural networks.
Briefings Bioinform., July, 2021
Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.
Briefings Bioinform., July, 2021
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
BastionHub: a universal platform for integrating and analyzing substrates secreted by Gram-negative bacteria.
Nucleic Acids Res., 2021
BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data.
Frontiers Big Data, 2021
BMC Bioinform., 2021
Bioinform., 2021
Bioinform., 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
DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.
Briefings Bioinform., 2021
PScL-HDeep: image-based prediction of protein subcellular location in human tissue using ensemble learning of handcrafted and deep learned features with two-layer feature selection.
Briefings Bioinform., 2021
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
Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.
Briefings Bioinform., 2021
Briefings Bioinform., 2021
DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.
Briefings Bioinform., 2021
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
nhKcr: a new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning.
Briefings Bioinform., 2021
Systematic evaluation of machine learning methods for identifying human-pathogen protein-protein interactions.
Briefings Bioinform., 2021
Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites.
Briefings Bioinform., 2021
2020
Pippin: A random forest-based method for identifying presynaptic and postsynaptic neurotoxins.
J. Bioinform. Comput. Biol., 2020
J. Bioinform. Comput. Biol., 2020
J. Ambient Intell. Humaniz. Comput., 2020
Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information.
Genom. Proteom. Bioinform., 2020
PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.
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
PhosTransfer: A Deep Transfer Learning Framework for Kinase-Specific Phosphorylation Site Prediction in Hierarchy.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020
Prediction of secondary structure population and intrinsic disorder of proteins using multitask deep learning.
Proceedings of the AMIA 2020, 2020
2019
Deep learning with evolutionary and genomic profiles for identifying cancer subtypes.
J. Bioinform. Comput. Biol., 2019
SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models.
BMC Bioinform., 2019
BMC Bioinform., 2019
MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters.
Bioinform., 2019
Bioinform., 2019
Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework.
Briefings Bioinform., 2019
Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches.
Briefings 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
Toward more accurate prediction of caspase cleavage sites: a comprehensive review of current methods, tools and features.
Briefings Bioinform., 2019
2018
Predicting functional sites in proteins using intelligent machine learning and data mining techniques.
PhD thesis, 2018
IEEE ACM Trans. Comput. Biol. Bioinform., 2018
ProBAPred: Inferring protein-protein binding affinity by incorporating protein sequence and structural features.
J. Bioinform. Comput. Biol., 2018
ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides.
Bioinform., 2018
Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors.
Bioinform., 2018
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
Comprehensive assessment and performance improvement of effector protein predictors for bacterial secretion systems III, IV and VI.
Briefings Bioinform., 2018
Structural Principles Analysis of Host-Pathogen Protein-Protein Interactions: A Structural Bioinformatics Survey.
IEEE Access, 2018
2017
Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.
BMC Genom., 2017
POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles.
Bioinform., 2017
Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity.
Briefings Bioinform., 2017
Collaborative data analytics towards prediction on pathogen-host protein-protein interactions.
Proceedings of the 21st IEEE International Conference on Computer Supported Cooperative Work in Design, 2017
Leveraging Stacked Denoising Autoencoder in Prediction of Pathogen-Host Protein-Protein Interactions.
Proceedings of the 2017 IEEE International Congress on Big Data, 2017
Towards Elucidating the Structural Principles of Host-Pathogen Protein-Protein Interaction Networks: A Bioinformatics Survey.
Proceedings of the 2017 IEEE International Congress on Big Data, 2017
2016
Database J. Biol. Databases Curation, 2016
Database J. Biol. Databases Curation, 2016
KinetochoreDB: a comprehensive online resource for the kinetochore and its related proteins.
Database J. Biol. Databases Curation, 2016
Critical evaluation of <i>in silico</i> methods for prediction of coiled-coil domains in proteins.
Briefings Bioinform., 2016
Proceedings of the 2016 IEEE International Congress on Big Data, San Francisco, CA, USA, June 27, 2016
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
Host-Pathogen Protein Interaction Prediction Based on Local Topology Structures of a Protein Interaction Network.
Proceedings of the 16th IEEE International Conference on Bioinformatics and Bioengineering, 2016
2015
Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model.
J. Comput. Biol., 2015
GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.
Bioinform., 2015
Towards more accurate prediction of ubiquitination sites: a comprehensive review of current methods, tools and features.
Briefings Bioinform., 2015
Towards more accurate prediction of protein folding rates: a review of the existing web-based bioinformatics approaches.
Briefings Bioinform., 2015
2014
Bioinform., 2014
Bioinformatics approaches for improved recombinant protein production in <i>Escherichia coli: </i> protein solubility prediction.
Briefings Bioinform., 2014
2013
Prediction of protein-RNA residue-base contacts using two-dimensional conditional random field with the lasso.
BMC Syst. Biol., 2013
2012
Predicting protein-RNA residue-base contacts using two-dimensional conditional random field.
Proceedings of the 6th IEEE International Conference on Systems Biology, 2012
2011
J. Bioinform. Comput. Biol., 2011
Conditional random field approach to prediction of protein-protein interactions using domain information.
BMC Syst. Biol., 2011
2010
J. Comput. Chem., 2010
APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.
BMC Bioinform., 2010
Bioinform., 2010
EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes.
Bioinform., 2010
2008
2007
Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.
Bioinform., 2007
2006
Prediction of <i>cis</i>/<i>trans </i>isomerization in proteins using PSI-BLAST profiles and secondary structure information.
BMC Bioinform., 2006
BMC Bioinform., 2006