Hao Lin
Orcid: 0000-0001-6265-2862Affiliations:
- University of Electronic Science and Technology of China, Chengdu, China
According to our database1,
Hao Lin
authored at least 54 papers
between 2007 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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on orcid.org
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Bibliography
2024
E-MuLA: An Ensemble Multi-Localized Attention Feature Extraction Network for Viral Protein Subcellular Localization.
Inf., March, 2024
Comput. Biol. Medicine, February, 2024
Detecting key genes relative expression orderings as biomarkers for machine learning-based intelligent screening and analysis of type 2 diabetes mellitus.
Expert Syst. Appl., 2024
2023
Identification of Key DNA methylation sites related to differentially expressed genes in Lung squamous cell carcinoma.
Comput. Biol. Medicine, December, 2023
iPADD: A Computational Tool for Predicting Potential Antidiabetic Drugs Using Machine Learning Algorithms.
J. Chem. Inf. Model., August, 2023
Briefings Bioinform., March, 2023
A gender specific risk assessment of coronary heart disease based on physical examination data.
npj Digit. Medicine, 2023
2022
RNALocate v2.0: an updated resource for RNA subcellular localization with increased coverage and annotation.
Nucleic Acids Res., 2022
Frontiers Comput. Sci., 2022
Comput. Biol. Medicine, 2022
A deep learning model to identify gene expression level using cobinding transcription factor signals.
Briefings Bioinform., 2022
iLoc-miRNA: extracellular/intracellular miRNA prediction using deep BiLSTM with attention mechanism.
Briefings Bioinform., 2022
PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization.
Briefings Bioinform., 2022
iRice-MS: An integrated XGBoost model for detecting multitype post-translational modification sites in rice.
Briefings Bioinform., 2022
Detection of transcription factors binding to methylated DNA by deep recurrent neural network.
Briefings Bioinform., 2022
2021
Risk Prediction of Diabetes: Big data mining with fusion of multifarious physical examination indicators.
Inf. Fusion, 2021
iCarPS: a computational tool for identifying protein carbonylation sites by novel encoded features.
Bioinform., 2021
Briefings Bioinform., 2021
Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method.
Briefings Bioinform., 2021
Briefings Bioinform., 2021
Briefings Bioinform., 2021
iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network.
Briefings Bioinform., 2021
2020
VisFeature: a stand-alone program for visualizing and analyzing statistical features of biological sequences.
Bioinform., 2020
DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species.
Bioinform., 2020
A comparison and assessment of computational method for identifying recombination hotspots in Saccharomyces cerevisiae.
Briefings Bioinform., 2020
Evaluation of different computational methods on 5-methylcytosine sites identification.
Briefings Bioinform., 2020
2019
IEEE ACM Trans. Comput. Biol. Bioinform., 2019
Predicting protein structural classes for low-similarity sequences by evaluating different features.
Knowl. Based Syst., 2019
Bioinform., 2019
Bioinform., 2019
iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators.
Bioinform., 2019
Identify origin of replication in Saccharomyces cerevisiae using two-step feature selection technique.
Bioinform., 2019
Bioinform., 2019
2018
iRNA-2OM: A Sequence-Based Predictor for Identifying 2′-O-Methylation Sites in <i>Homo sapiens</i>.
J. Comput. Biol., 2018
iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC.
Bioinform., 2018
2017
iDNA4mC: identifying DNA N4-methylcytosine sites based on nucleotide chemical properties.
Bioinform., 2017
Identify and analysis crotonylation sites in histone by using support vector machines.
Artif. Intell. Medicine, 2017
2016
Predicting bacteriophage proteins located in host cell with feature selection technique.
Comput. Biol. Medicine, 2016
2015
PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions.
Bioinform., 2015
2014
Phd7faster: Predicting Clones Propagating Faster from the pH.D.-7 phage Display peptide Library.
J. Bioinform. Comput. Biol., 2014
iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition.
Bioinform., 2014
2013
Theory Biosci., 2013
Comput. Math. Methods Medicine, 2013
Comput. Math. Methods Medicine, 2013
2012
Identification of voltage-gated potassium channel subfamilies from sequence information using support vector machine.
Comput. Biol. Medicine, 2012
2011
Theory Biosci., 2011
2009
Int. J. Bioinform. Res. Appl., 2009
2007
Using pseudo amino acid composition to predict protein structural class: Approached by incorporating 400 dipeptide components.
J. Comput. Chem., 2007