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2020 – today
- 2022
[c13]Anqi Wei, Liangjiang Wang:
Deep sequence representation learning for predicting human proteins with liquid-liquid phase separation propensity and synaptic functions. BCB 2022: 41:1-41:8- 2021
- [j17]Shuzhen Kuang, Yanzhang Wei, Liangjiang Wang
:
Expression-based prediction of human essential genes and candidate lncRNAs in cancer cells. Bioinform. 37(3): 396-403 (2021) - [j16]Shuzhen Kuang, Liangjiang Wang:
Deep Learning of Sequence Patterns for CCCTC-Binding Factor-Mediated Chromatin Loop Formation. J. Comput. Biol. 28(2): 133-145 (2021) - 2020
- [j15]Jun Wang, Liangjiang Wang:
Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features. BMC Bioinform. 21(1): 505 (2020)
2010 – 2019
- 2019
- [j14]Jun Wang, Liangjiang Wang:
Deep learning of the back-splicing code for circular RNA formation. Bioinform. 35(24): 5235-5242 (2019) - [c12]Shuzhen Kuang, Liangjiang Wang:
Deep Learning of CTCF-Mediated Chromatin Loops in 3D Genome Organization. ICCABS 2019: 77-89 - 2018
- [j13]Steven B. Cogill, Anand K. Srivastava, Mary Qu Yang, Liangjiang Wang:
Co-expression of long non-coding RNAs and autism risk genes in the developing human brain. BMC Syst. Biol. 12(7): 65-73 (2018) - 2017
- [j12]Yi Huang, Tingyun Wang, Chuanlu Deng, Xiaobei Zhang, Fufei Pang, Xuekun Bai, Weilong Dong, Liangjiang Wang, Zhenyi Chen:
A Highly Sensitive Intensity-Modulated Optical Fiber Magnetic Field Sensor Based on the Magnetic Fluid and Multimode Interference. J. Sensors 2017: 9573061:1-9573061:7 (2017) - [c11]Jun Wang, Liangjiang Wang:
Prediction of back-splicing sites reveals sequence compositional features of human circular RNAs. ICCABS 2017: 1-6 - [c10]Brian L. Gudenas, Liangjiang Wang:
A Genetic Algorithm for Finding Discriminative Functional Motifs in Long Non-coding RNAs. ISBRA 2017: 408-413 - 2016
- [j11]Steven B. Cogill, Liangjiang Wang:
Support vector machine model of developmental brain gene expression data for prioritization of Autism risk gene candidates. Bioinform. 32(23): 3611-3618 (2016) - 2014
- [j10]Jack Y. Yang, A. Keith Dunker, Jun S. Liu, Xiang Qin, Hamid R. Arabnia, William Yang, Andrzej Niemierko, Zhongxue Chen, Zuojie Luo, Liangjiang Wang, Yunlong Liu, Dong Xu, Youping Deng, Weida Tong, Mary Qu Yang:
Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms. BMC Bioinform. 15(S-17): I1 (2014) - [j9]William Yang, Kenji Yoshigoe, Xiang Qin, Jun S. Liu, Jack Y. Yang, Andrzej Niemierko, Youping Deng, Yunlong Liu, A. Keith Dunker, Zhongxue Chen, Liangjiang Wang, Dong Xu, Hamid R. Arabnia, Weida Tong, Mary Qu Yang:
Identification of genes and pathways involved in kidney renal clear cell carcinoma. BMC Bioinform. 15(S-17): S2 (2014) - 2010
- [j8]Liangjiang Wang, Caiyan Huang, Mary Qu Yang, Jack Y. Yang:
BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features. BMC Syst. Biol. 4(S-1): S3 (2010) - [j7]Shaolei Teng, Anand K. Srivastava, Charles E. Schwartz, Emil Alexov, Liangjiang Wang:
Structural assessment of the effects of Amino Acid Substitutions on protein stability and protein-protein interaction. Int. J. Comput. Biol. Drug Des. 3(4): 334-349 (2010) - [c9]Shaolei Teng, Hong Luo, Liangjiang Wang:
Random forest-based prediction of protein sumoylation sites from sequence features. BCB 2010: 120-126 - [c8]Liangjiang Wang:
Computational Identification of Human Tissue-Specific Genes Using Public Microarray Expression Data. BIOCOMP 2010: 120-126
2000 – 2009
- 2009
- [c7]Shaolei Teng, Anand K. Srivastava, Liangjiang Wang:
Biological Features for Sequence-Based Prediction of Protein Stability Changes upon Amino Acid Substitutions. IJCBS 2009: 201-206 - [c6]Liangjiang Wang, Caiyan Huang:
New Descriptors of Evolutionary Information for Accurate Prediction of DNA and RNA-Binding Residues in Protein Sequences. IJCBS 2009: 246-250 - 2008
- [j6]Liangjiang Wang, Stephanie Jimenez Irausquin, Jack Y. Yang:
Prediction of lipid-interacting amino acid residues from sequence features. Int. J. Comput. Biol. Drug Des. 1(1): 14-25 (2008) - [c5]Liangjiang Wang:
BindN+ for Improved Prediction of DNA or RNA Binding Residues in Protein Sequences Using Evolutionary Information. BIOCOMP 2008: 961-964 - [c4]Liangjiang Wang:
Random Forests for Prediction of DNA-Binding Residues in Protein Sequences Using Evolutionary Information. FGCN (3: BSBT) 2008: 24-29 - 2007
- [j5]Liangjiang Wang, Suzhi Wang, Yonghua Li, Martin S. R. Paradesi, Susan J. Brown:
BeetleBase: the model organism database for Tribolium castaneum. Nucleic Acids Res. 35(Database-Issue): 476-479 (2007) - [c3]Stephanie Jimenez Irausquin, Liangjiang Wang:
A Machine Learning Approach for Prediction of Lipid-Interacting Residues in Amino Acid Sequences. BIBE 2007: 315-319 - [c2]Liangjiang Wang:
A Semi-Supervised Learning Approach for Prediction of DNA-Binding Residues in Protein Sequences. BIOCOMP 2007: 421-426 - 2006
- [j4]Liangjiang Wang, Susan J. Brown:
Prediction of Dna-binding Residues from Sequence Features. J. Bioinform. Comput. Biol. 4(6): 1141-1158 (2006) - [j3]Liangjiang Wang, Susan J. Brown:
BindN: a web-based tool for efficient prediction of DNA and RNA binding sites in amino acid sequences. Nucleic Acids Res. 34(Web-Server-Issue): 243-248 (2006) - [c1]Liangjiang Wang, Susan J. Brown:
Prediction of RNA-Binding Residues in Protein Sequences Using Support Vector Machines. EMBC 2006: 5830-5833 - 2005
- [j2]Liangjiang Wang, Aidong Zhang, Murali Ramanathan:
BioStar models of clinical and genomic data for biomedical data warehouse design. Int. J. Bioinform. Res. Appl. 1(1): 63-80 (2005) - 2003
- [j1]Anthony L. Duran, Jian Yang, Liangjiang Wang, Lloyd W. Sumner:
Metabolomics spectral formatting, alignment and conversion tools (MSFACTs). Bioinform. 19(17): 2283-2293 (2003)
Coauthor Index
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