Liangjiang Wang

Publication Activity (10 Years)

Years Active: 2003-2022
Publications (10 Years): 11

Top Topics

Gene Expression

Arabidopsis Thaliana

Top Venues

J. Comput. Biol.

Publications

Anqi Wei, Liangjiang Wang
Deep sequence representation learning for predicting human proteins with liquid-liquid phase separation propensity and synaptic functions. BCB (2022)
Shuzhen Kuang, Liangjiang Wang
Deep Learning of Sequence Patterns for CCCTC-Binding Factor-Mediated Chromatin Loop Formation. J. Comput. Biol. 28 (2) (2021)
Shuzhen Kuang, Yanzhang Wei, Liangjiang Wang
Expression-based prediction of human essential genes and candidate lncRNAs in cancer cells. Bioinform. 37 (3) (2021)
Jun Wang, Liangjiang Wang
Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features. BMC Bioinform. 21 (1) (2020)
Shuzhen Kuang, Liangjiang Wang
Deep Learning of CTCF-Mediated Chromatin Loops in 3D Genome Organization. ICCABS (2019)
Jun Wang, Liangjiang Wang
Deep learning of the back-splicing code for circular RNA formation. Bioinform. 35 (24) (2019)
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) (2018)
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 (2017)
Jun Wang, Liangjiang Wang
Prediction of back-splicing sites reveals sequence compositional features of human circular RNAs. ICCABS (2017)
Brian L. Gudenas, Liangjiang Wang
A Genetic Algorithm for Finding Discriminative Functional Motifs in Long Non-coding RNAs. ISBRA (2017)
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) (2016)
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) (2014)
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) (2014)
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) (2010)
Liangjiang Wang
Computational Identification of Human Tissue-Specific Genes Using Public Microarray Expression Data. BIOCOMP (2010)
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) (2010)
Shaolei Teng, Hong Luo, Liangjiang Wang
Random forest-based prediction of protein sumoylation sites from sequence features. BCB (2010)
Shaolei Teng, Anand K. Srivastava, Liangjiang Wang
Biological Features for Sequence-Based Prediction of Protein Stability Changes upon Amino Acid Substitutions. IJCBS (2009)
Liangjiang Wang, Caiyan Huang
New Descriptors of Evolutionary Information for Accurate Prediction of DNA and RNA-Binding Residues in Protein Sequences. IJCBS (2009)
Liangjiang Wang
BindN+ for Improved Prediction of DNA or RNA Binding Residues in Protein Sequences Using Evolutionary Information. BIOCOMP (2008)
Liangjiang Wang
Random Forests for Prediction of DNA-Binding Residues in Protein Sequences Using Evolutionary Information. FGCN (3: BSBT) (2008)
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) (2008)
Stephanie Jimenez Irausquin, Liangjiang Wang
A Machine Learning Approach for Prediction of Lipid-Interacting Residues in Amino Acid Sequences. BIBE (2007)
Liangjiang Wang, Suzhi Wang, Yonghua Li, Martin S. R. Paradesi, Susan J. Brown
. Nucleic Acids Res. 35 (Database-Issue) (2007)
Liangjiang Wang
A Semi-Supervised Learning Approach for Prediction of DNA-Binding Residues in Protein Sequences. BIOCOMP (2007)
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) (2006)
Liangjiang Wang, Susan J. Brown
Prediction of Dna-binding Residues from Sequence Features. J. Bioinform. Comput. Biol. 4 (6) (2006)
Liangjiang Wang, Susan J. Brown
Prediction of RNA-Binding Residues in Protein Sequences Using Support Vector Machines. EMBC (2006)
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) (2005)
Anthony L. Duran, Jian Yang, Liangjiang Wang, Lloyd W. Sumner
Metabolomics spectral formatting, alignment and conversion tools (MSFACTs). Bioinform. 19 (17) (2003)