Hongde Liu

Orcid: 0000-0001-8768-764X

Affiliations:
  • Southeast University, School of Biology Science and Medical Engineering, State Key Laboratory of Bioelectronics, Nanjing, China


According to our database1, Hongde Liu authored at least 14 papers between 2007 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.
Briefings Bioinform., May, 2023

2022
Predicting hormone receptors and PAM50 subtypes of breast cancer from multi-scale lesion images of DCE-MRI with transfer learning technique.
Comput. Biol. Medicine, 2022

2021
DeepSSV: detecting somatic small variants in paired tumor and normal sequencing data with convolutional neural network.
Briefings Bioinform., 2021

2019
DNMHMM: An approach to identify the differential nucleosome regions in multiple cell types based on a Hidden Markov Model.
Biosyst., 2019

2018
Nucleosome Positioning of Intronless Genes in the Human Genome.
IEEE ACM Trans. Comput. Biol. Bioinform., 2018

2017
Histone modifications influence skipped exons inclusion.
J. Bioinform. Comput. Biol., 2017

2012
Sequence-Based Prediction of DNA-Binding Residues in Proteins with Conservation and Correlation Information.
IEEE ACM Trans. Comput. Biol. Bioinform., 2012

Nucleosome organization in sequences of alternative events in human genome.
Biosyst., 2012

Next-generation sequencing data processing: Analysis of unmapped reads and extremely high mapped peaks.
Proceedings of the 5th International Conference on BioMedical Engineering and Informatics, 2012

2011
Role of 10-11 bp periodicities of eukaryotic DNA sequence in nucleosome positioning.
Biosyst., 2011

2010
Nucleosomes Are Well Positioned at Both Ends of Exons.
Proceedings of the Life System Modeling and Intelligent Computing, 2010

2009
Prediction of DNA-binding residues in proteins from amino acid sequences using a random forest model with a hybrid feature.
Bioinform., 2009

SVM-Based Approach for Predicting DNA-Binding Residues in Proteins from Amino Acid Sequences.
Proceedings of the International Joint Conferences on Bioinformatics, 2009

2007
Support Vector Machine for Prediction of DNA-Binding Domains in Protein-DNA Complexes.
Proceedings of the Life System Modeling and Simulation, International Conference, 2007


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