· [ml/dm] C. Huo, D. He, Y. Li, D. Jin, J. Dang, W. Pedrycz, L. Wu, and W. Zhang, Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning, ACM Trans. Intell. Syst. Technol, 2025, 16(1):1-21.
· [medImg] H. Guo, Y. Xiao, S. Dong, J. Yang, P. Zhao, T. Zhao, A. Cai, L. Tang, J. Liu, H. Wang, R. Hua, R. Liu, Y. Wei, D. Sun, Z. Liu, M. Xia, Y. He, Y. Wu, T. Si, F. Womer, F. Xu, Y. Tang, J. Wang, W. Zhang, X. Zhang & F. Wang , Bridging animal models and humans: neuroimaging as intermediate phenotypes linking genetic or stress factors to anhedonia. BMC medicine, 2025, 23(1):38.
· [ml/dm] Q. Zhao, C. Zhang, W. Zhang, dnaGrinder: a lightweight and high-capacity genomic foundation model, arXiv, 2024, https://arxiv.org/abs/2409.15697.
· [ml/dm] D. He, C. Liang, C. Huo, Z. Feng, D. Jin, L. Yang, and W. Zhang, Analyzing heterogeneous networks with missing attributes by unsupervised contrastive learning, IEEE Trans. Neural Networks and Learning Systems, 2024, 35(4):4438-50.
· [ml/dm] D. He, L. Shan, J. Zhao, H. Zhang, Z. Wang, W. Zhang, Exploitation of a latent mechanism in graph contrastive learning: Representation scattering, Proc 38-th Conf on Neural Information Processing Systems (NeurIPS 2024).
· [ml/dm] Y. Zhou, D. Jin, J. Wei, D. He, Z. Yu, and W. Zhang, Generalized taxonomy-guided graph neural networks, Proc 33-rd Intern. Joint Conf. on AI (IJCAI-24).
· [ml/dm] D. He, J. Zhao, R. Guo, Z. Feng, D. Jin, Y. Huang , Z. Wang and W. Zhang, Contrastive learning meets homophily: Two birds with one stone. Conf. on Machine Learning (ICML-2023)
· [medImg] Y. Xiao, FY. Womer, S. Dong, R.Zhu, R. Zhang, J. Yang, L. Zhang, J. Liu, W. Zhang, Z. Liu, X. Zhang, F. Wang, A neuroimaging-based precision medicine framework for depression,Asian J Psychiatr, 91:103803, 2023.
· [ml/dm] X. Wei, C. Pan, X. Zhang, W. Zhang, Total network controllability analysis discovers explainable drugs for Covid-19 treatment, Biology Direct, 18(1):55, 2023.
· [ml/dm] X. Zhang, C. Pan, X. Wei, M. Yu, S. Liu, J. An, J. Yang, B. Wei, W. Hao, Y. Yao, Y. Zhu, and W. Zhang*, Cancer-keeper genes as therapeutic targets, iScience, 26(8):107296, 2023.
· [ml/dm] D. Jin, Z. Yu, P. Jiao, S. Pan, D. He, J. Wu, P. Yu, W. Zhang, A survey of community detection approaches: From statistical modeling to deep learning, IEEE Trans. on Knowledge and Data Engineering, 35(2):1149-90, 2023.
· [PCMM] S. He, S. Qiu, M.Pan, J. P Palavicini, H. Wang, X. Li, A. Bhattacharjee, S. Barannikov, K. F Bieniek, J. L Dupree and X. Han, Marked reduction of spinal cord lipids causes neurogenic bladder in late Alzheimer’s disease, Clin. Transl. Med., 2023 accepted.
· [PCMM] S. Qiu, S. He, J. Wang, H. Wang, A. Bhattacharjee, X. Li, M. Saeed, J. L. Dupree, X. Han, Adult-onset CNS sulfatide deficiency causes sex-dependent metabolic disruption in aging, Int J Mol Sci, 24(13), 2023.
· [PCMM] S. Qiu, J. P. Palavicini, X. Han, Myelin lipid deficiency: a new key driver of Alzheimer’s disease, Neural Regen Res, 18:121-122, 2023.
· [PCMM] Dustin, E., E. Suarez-Pozos, C. Stotesberry,S. Qiu, J. P. Palavicini, X. Han and J. L. Dupree, Compromised Myelin and Axonal Molecular Organization Following Adult-Onset Sulfatide Depletion, Biomedicines, 11(5), 2023.
· [ml/dm] D. Jin, R. Wang, M. Ge, H. He, X. Li, W. Lin and W. Zhang, RAW-GNN: Random Walk Aggregation based graph neural network, Proc 31-st Intern. Joint Conf. on AI(IJCAI-22).
· [ml/dm] D. He, C. Liang, C. Huo, Z. Feng, D. Jin, L. Yang, and W. Zhang, Analyzing heterogeneous networks with missing attributes by unsupervised contrastive learning, IEEE Trans. On Neural Networks and Learning Systems, IEEE Transactions on Neural Networks and Learning Systems, published online March 2022.
· [ncRNA] P. Xuan*, L. Zhan, H. Cui, T. Zhang, T. Nakaguchi, W. Zhang, Graph Triple-Attention Network for Disease-Related LncRNA Prediction, IEEE J Biomedical and Health Informatics, 26(6):2839-49, 2022.
· [PCMM] Palavicini, J. P., L. Ding, M. Pan, S. Qiu, H. Wang, Q. Shen, J. L. Dupree and X. Han, Sulfatide Deficiency, an Early Alzheimer’s Lipidomic Signature, Causes Brain Ventricular Enlargement in the Absence of Classical Neuropathological Hallmarks, Int J Mol Sci, 24(1), 2022.
· [genom] M. Chang, F. Womer, X. Gong, X. Chen, L. Tang, R. Feng, S. Dong, J. Duan, Y. Chen, R. Zhang, Y. Wang, S. Ren, Y. Wang, J. Kang, Z. Yin, Y. Wei, S. Wei, X. Jian, K. Xu, B. Cao, Y. Zhang, W. Zhang, Y. Tang, X. Zhang, F. Wang, Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning, Molecular Psychiatry, 26(7):2991-3002, 2021.
· [genom] L. Chen, J. Zhou, T. Li, Z. Fang, L. Li, G. Huang, L. Gao, X. Zhu, X. Zhou, H. Xiao, J. Zhang, Q. Xiong, J. Zhang, A. Ma, W. Zhai, W. Zhang, and H. Peng, GmoDetector: An accurate and efficient GMO identification approach and its application, Food Research Intern, 149:110662, 2021.
· [ncRNA] X. Liu, J. Frost, A. Bowcock, W. Zhang, Canonical and interior circular RNAs function as competing endogenous RNAs in psoriatic skin, Intern. J. Molecular Sciences, 22(10), 5182, 2021.
· [medImg] Z. Zhang, T. Zhao, H. Gay,W. Zhang* , B. Sun, Weaving attention U-net: A novel hybrid CNN and attention-based method for organs-at-risk segmentation in head and neck CT images, Medical Physics, 48(11):7052-62, 2021.
· [medImg] Z. Zhang, T. Zhao, H. Gay,W. Zhang, B. Sun, ARPM-net: A novel CNN-based adversarial method with Markov Random Field enhancement for prostate and organs at risk segmentation in pelvic CT images, Medical Physics, 48(1):227-37, 2021.
· [medImg] Z. Zhang, T. Zhao, H. Gay, W. Zhang, B. Sun*, Semi-supervised semantic segmentation of prostate and organs-at-risk on 3D pelvic CT images Biomedical Physics Engineering Express. 7(6), 2021
· [ml/dm] D. Jin, X. Wang, D. He, J. Dang, W. Zhang, Robust detection of link communities with summary description in social networks, IEEE Transactions on Knowledge and Data Engineering, 33(6):2737-49, 2021.
· [PCMM] S. Qiu, J. P. Palavicini, J. Wang, N. S. Gonzalez, S. He, E. Dustin, C. Zou, L. Ding, A. Bhattacharjee, C. E. Van Skike, V. Galvan, J. L. Dupree, X. Han. Adult-onset CNS myelin sulfatide deficiency is sufficient to cause Alzheimer’s disease-like neuroinflammation and cognitive impairment. Mol Neurodegener 16:64, 2021.
· [ml/dm] D. He, Y. Song, D. Jin, Z. Feng, B. Zhang, Z. Yu and W. Zhang, Community-centric graph Convolutional Network for unsupervised community detection, Proc 29-th Intern. Joint Conf. on AI (IJCAI-20).
· [AI] X. Zhang, J. Gao, Y. Lv and W. Zhang, Early and efficient identification of useless constraint propagation for alldifferent constraints, Proc 29-th Intern. Joint Conf. on AI (IJCAI-20).
· [genom] L. Li, H. Peng, S. Tan, J. Zhou, Z. Fang, Z. Hu, L. Gao, T. Li, W. Zhang, and L. Chen, Effects of early cold stress on gene expression in Chlamydomonas reinhardtii, Genomics, 112(2):1128-38, 2020.
· [ncRNA] X. Liu, Z. Hu, J. Zhou, C. Tian, G. Tian, M. He, L. Gao, L. Chen, T. Li, P. Peng, W. Zhang*, Interior circular RNA, RNA Biology, 17(1):87-97, 2020.
· [ml/dm] M. Li, D. Jin, D. He, and W. Zhang, Modeling with node popularities for autonomous overlapping community detection, ACM Transactions on Information Systems, 11(3):27, 2020.
· [ml/dm] D. Jin, B. Li, P. Jiao, D. He and W. Zhang, Network-specific variational Auto-Encoder for embedding of attribute networks, Proc 28-th Intern. Joint Conf. on AI (IJCAI-19).
· [ml/dm] D. Jin, Z. Liu, W. Li, D. He and W. Zhang, Graph convolutional networks meet Markov Random Fields: Semi-supervised community detection in attribute networks, Proc 33-th AAAI Conf on AI (AAAI-19).
· [medlmg] D. Lam, X. Zhang, H. Li, Y. Deshan, B. Schott, T. Zhao, W. Zhang, S. Mutic, and B. Sun*, Predicting gamma passing rates for portal dosimetry-based IMRT QA using machine learning, Medical Physics, 46(10):4666-75, 2019.
· [ml/dm] L. Yang, Y. Wang, J. Gu, X. Cao, X. Wang, D. Jin, G. Ding, J. Han, and W. Zhang, Autonomous semantic community detection via adaptively weighted low-rank approximation, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 15(3s), 2019.
· [PCMM] S. Qiu, T. Liu, C. Piao, Y. Wang, K. Wang, Y. Zhou, L. Cai, S. Zheng, F. Lan, J. Du. AMPKalpha2 knockout enhances tumour inflammation through exacerbated liver injury and energy deprivation-associated AMPKalpha1 activation. J Cell Mol Med, 23:1687-1697, 2019.
· [ml/dm] G. Meng, D. Jin and W. Zhang, Integrative network embedding via deep joint reconstruction, Proc 27-th Intern. Joint Conf. on AI (IJCAI-18).
· [AI] X. Zhang and W. Zhang, A fast algorithm for generalized arc consistency of the alldifferent constraint, Proc 27-th Intern. Joint Conf. on AI (IJCAI-18)
· [ml/dm] D. He, X. You, Z. Feng, D. Jin, X. Yang and W. Zhang, A network-specific Markov Random Field approach to community detection, Proc 32-nd AAAI Conf on AI (AAAI-18).
· [ml/dm] D. Jin, X. Wang, R. He, D. He and W. Zhang, Robust detection of link communities in large social networks by exploiting link semantics, Proc 32-nd AAAI Conf on AI (AAAI-18).
· [genom] L. Li, G. Tian, H. Peng, D. Meng, L. Wang, X. Hu, C. Tian, M. He, J. Zhou, L. Chen, C. Fu, W. Zhang* and Z. Hu, New class of transcription factors controls flagellar assembly by recruiting RNA polymerase II in Chlamydomonas, Proc of National Academy of Sciences of the USA (PNAS), 115(17):4435-4440, 2018.
· [ncRNA] Y. Zhong, P. Xuan, X. Wang, T. Zhang, J. Li, Y. Liu and W. Zhang, A non-negative matrix factorization based method for predicting disease-associated miRNAs in miRNA-disease bilayer network, Bioinformatics, 34(2):267-77, 2018.
· [PCMM] W. Ren, Y. Liu, X. Wang, C. Piao, Y. Ma, S. Qiu, L. Jia, B. Chen, Y. Wang, W. Jiang, S. Zheng, C. Liu, N. Dai, F. Lan, H. Zhang, W. C. Song, J. Du. The Complement C3a-C3aR Axis Promotes Development of Thoracic Aortic Dissection via Regulation of MMP2 Expression. J Immunol, 200:1829-1838, 2018.
· [ml/dm] D. He, D. Jin and W. Zhang, Joint identification of network communities and semantics via integrative modeling of network topologies and node contents, Proc 31-st AAAI Conf on AI (AAAI-17).
· [genom] L. Li, Z. Fang, J. Zhou, H. Chen, Z. Hu, L. Gao, L. Chen, S. Ren, H. Ma, L. Lu, W. Zhang* and H. Peng, An accurate and efficient method for large-scale SSR genotyping and applications, Nucleic Acids Research, 45(10):e88, 2017.
· [genom] T.P. Michael, D. Bryant, R. Gutierrez, N. Borisjuk, P. Chu, H. Zhang, J. Xia, J. Zhou, H. Peng, M.E. Baidouri, B. ten Hallers, AR. Hastie, T. Liang, K. Acosta, S. Gilbert, C. McEntee, SA. Jackson, TC. Mockler, W. Zhang and E. Lam, Comprehensive definition of genome features in Spirodela polyrhiza by high-depth physical mapping and short-read DNA sequencing strategies, The Plant Journal, 89(3):617-35, 2017.
· [ncRNA] J. Xia, L. Li, T. Li, Z. Fang, K. Zhang, J. Zhou, H. Peng, and W. Zhang, Detecting and characterizing microRNAs of diverse genomic origins via miRvial, Nucleic Acids Research, 45(21):e176, 2017.
· [ml/dm] X. Zhang, J. Han and W. Zhang, An efficient algorithm for finding all possible input nodes for controlling complex networks, Scientific Reports, 7(1):10677, 2017.
· [ml/dm] J. Fu, W. Zhang and J. Wu*, Identification of leader and self-organizing communities in complex networks, Scientific Reports, 7(1):704, 2017.
· [ml/dm] L. Yang, X. Cao, D. He, W. Zhang, Modularity based community detection with deep learning, Proc 25-th Intern. Joint Conf. on AI (IJCAI-16), Buenos Aires, July 25-31, 2016
· [ml/dm] D. Jin, H. Wang, J. Dang, D. He and W. Zhang, Detect overlapping communities via ranking node popularities, Proc 30-th AAAI Conf on AI (AAAI-16)
· [ml/dm] X. Wang, D. Jin, X. Cao, L. Yang and W. Zhang, Semantic community identification in large attribute networks, Proc 30-th AAAI Conf on AI(AAAI-16)
· [genom] D. Tiosano, L. Audi, S. Climer, W. Zhang, A.R. Templeton*, M. Fernandez-Cancio, R. Gershoni-Baruch, J.M. Sanchez-Muro, M.E. Kholy, Z. Hochberg, Latitudinal Clines of the human Vitamin D receptor and skin color-genes, Genes, Genomes, Genetics, 6(5):1251-66, 2016. (Based on the work receiving the Henning Anderson Price at the European Society for Paediatric Endocrinology 51st Annual Meeting)
· [ml/dm] Z. Chen, M. Chen, K. Weinberger and W. Zhang, Marginalized denoising for link prediction and multi-label learning, Proc. 29th AAAI Conf on Artificial Intelligence (AAAI-15)
· [ml/dm] D. Jin, Z. Chen, D. He and W. Zhang, Modeling with node degree preservation can accurately find communities, Proc. 29th AAAI Conf on Artificial Intelligence (AAAI-15)
· [ml/dm] D. He, D. Liu, D. Jin and W. Zhang, A stochastic model for the detection of heterogeneous link communities in complex networks, Proc. 29th AAAI Conf on Artificial Intelligence (AAAI-15)
· [genom] S. Climer, A. Templeton and W. Zhang, Human gephyrin is encompassed within giant functional noncoding yin-yang sequences, Nature Communications, 6:6534, 2015.
· [ncRNA] D. Nie, J. Xia, C. Jiang, B. Qi, X. Ling, S. Lin, W. Zhang, J. Guo, H. Jin and H. Zhao, Bacillus cereus AR156 primes induced systemic resistance by suppressing miR825/825* and activating defense related genes in Arabidopsis, J. Integrative Plant Biology, 58(4):426-39, 2015.
· [ml/dm] D. He, D. Jin, Z. Chen and W. Zhang*, Identification of hybrid node and link communities in complex networks, Scientific Reports, 5:8638, 2015.
· [PCMM] J. Wang, S. Qiu, S. Chen, C. Xiong, H. Liu, J. Wang, N. Zhang, J. Hou, Q. He, Z. Nie. MALDI-TOF MS imaging of metabolites with a N-(1-naphthyl) ethylenediamine dihydrochloride matrix and its application to colorectal cancer liver metastasis. Anal Chem, 87:422-430, 2015.
· [PCMM] S. Qiu, Z. Xiao, C. Piao, J. Zhang, Y. Dong, W. Cui, X. Liu, Y. Zhang, J. Du. AMPKalpha2 reduces renal epithelial transdifferentiation and inflammation after injury through interaction with CK2beta. J Pathol, 237:330-342, 2015.
· [PCMM] C. Piao, L. Cai, S. Qiu, L. Jia, W. Song, J. Du. Complement 5a Enhances Hepatic Metastases of Colon Cancer via Monocyte Chemoattractant Protein-1-mediated Inflammatory Cell Infiltration. J Biol Chem, 290:10667-10676, 2015.
· [ml/dm] Z. Chen and W. Zhang (2014) A marginalized denoising method for link prediction in relational data, Proc. SIAM Intern. Conf. on Data Mining (SDM-14)
· [genom] W. Wang, B. Feng, J. Xiao, Z. Xia, X. Zhou, P. Li, W. Zhang, et al., Cassava genome from a wild ancestor to cultivated varieties, Nature Communications, 5:5110, 2014.
· [genom] S. Climer, A. Templeton andW. Zhang* , Allele-specific network reveals combinatorial interactions that transcends small effects in psoriasis GWAS, PLOS Computational Biology, 10(9):e1003766, 2014.
· [ncRNA] J. Xia and W. Zhang, MicroRNAs in normal and psoriatic skin, Physiological Genomics, 46(4):113-22, 2014, invited review.
· [ncRNA] J. Xia and W. Zhang, A meta-analysis revealed insights into the sources, conservation and impact of microRNA 5’-isoforms in four model species, Nucleic Acids Research, 42(3):1427-41, 2014.
· [PCMM] S. Qiu, Z. C. Xiao, C. M. Piao, Y. L. Xian, L. X. Jia, Y. F. Qi, J. H. Han, Y. Y. Zhang, J. Du. AMP-activated protein kinase alpha2 protects against liver injury from metastasized tumors via reduced glucose deprivation-induced oxidative stress. J Biol Chem 289:9449-9459, 2014.
· [ml/dm] Z. Chen and W. Zhang (2013) Domain adaptation with topical correspondence learning, Proc. 23rd Intern. Joint Conf. on Artificial Intelligence (IJCAI-13)
· [genom] Z. Chen and W. Zhang, Integrative analysis using module-guided Random Forests reveals correlated genetic factors related to mouse weight, PLOS Computational Biology, 9(3):e1002956, 2013.
· [ncRNA] J. Xia, C.E. Joyce, A.M. Bowcock andW. Zhang* , Noncanonical microRNAs and endogenous siRNAs in normal and psoriatic human skin, Human Molecular Genetics, 22(4):737-48, 2013.
· [AI] Q. Lu, R. Huang, Y. Chen, Y. Xu, W. Zhang, G. Sun and G. Chen, A SAT-based approach to cost sensitive temporally expressive planning, ACM Transactions on Intelligent Systems and Technology, 5(1):18, 2013.
· [ncRNA] X. Zhang, X. Jin, Y. Lii, B.E. Barrera-Figueroa, X. Zhou, S. Gao, L. Lu, D. Nie, Z. Chen, C. Leung, T. Wong, H. Zhang, J. Guo, Y. Li, R. Liu, W. Liang, J-K. Zhu, W. Zhang, H. Jin, Genome-wide analysis of plant nat-siRNAs reveals insights into their distribution, biogenesis and function, Genome Biology, 13:R20, 2012.
· [ncRNA] Y. Zheng*, Y-F. Li, R. Sunkar and W. Zhang, SeqTar: An effective method for identifying microRNA guided cleavage sites from degradome of polyadenylated transcripts in plants, Nucleic Acids Research, 40(4):e28, 2012.
· [AI] R. Huang, Y. Chen and W. Zhang (2012) SAS+ planning as Satisfiability, J. Artificial Intelligence Research, 43:293-328, 2012 (the AAAI-2010 Outstanding Paper Award).
· [PCMM] M. Yang, J. Zheng, Y. Miao, Y. Wang, W. Cui, J. Guo, S. Qiu, Y. Han, L. Jia, H. Li, J. Cheng, J. Du. Serum-glucocorticoid regulated kinase 1 regulates alternatively activated macrophage polarization contributing to angiotensin II-induced inflammation and cardiac fibrosis. Arterioscler Thromb Vasc Biol 32, 1675-1686, 2012.
· [ml/dm] X. Zhou, J. Ruan and W. Zhang (2010) Promoter prediction based on a multiple instance learning scheme, ACM Intern. Conf. on Bioinformatics and Computational Biology, Aug. 2-4, 2010
· [ml/dm] S. Climer, A. Templeton and W. Zhang (2010) SplittingHeirs: Inferring haplotypes by optimizing resultant dense graphs, ACM Intern. Conf. on Bioinformatics and Computational Biology, 2010
· [AI] R. Huang, Y. Chen and W. Zhang (2010) A novel transition based encoding scheme for planning as Satisfiability, Proc. 24th AAAI Conf on Artificial Intelligence (AAAI-10).Outstanding Paper Award.
· [ncRNA] C.E. Joyce, X. Zhou, J. Xia, C. Ryan, B. Thrash, A. Menter, W. Zhang* and A.M. Bowcock, Deep sequencing of small RNAs from human skin reveals major alterations in the psoriasis miRNAome, Human Molecular Genetics, 20(20):4025- 40, 2011.
2010
· [ncRNA] W. Zhang, S. Guo, J. Xia, X. Zhou, P. Chellappan, X. Zhou, X. Zhang and H. Jin, Multiple distinct small RNAs originated from the same microRNA precursors, Genome Biology, 11:R81, 2010.
· [ncRNA] P. Chellappan, J. Xia, X. Zhou, S. Gao, X. Zhang, G. Coutino, F. Vazquez, W. Zhang and H. Jin, siRNAs from miRNA sites mediate DNA methylation of target genes, Nucleic Acids Research, 38(20):6883-94, 2010.
· [ncRNA] C. Zeng, W. Wang, Y. Zheng, X. Chen, X. Bo, S. Song, W. Zhang, M. Peng, Conservation and divergence of microRNAs and their functions in Euphorbiaceous plants, Nucleic Acids Research, 38(3):981- 95, 2010.
· [ncRNA] T.A. Reese, J. Xia, L.S. Johnson, X. Zhou, W. Zhang and H.W. Virgin, Identification of novel microRNA-like molecules generated from herpesvirus and host tRNA transcripts, J. Virology, 84(19):10344-53, 2010.
· [ncRNA] Y-F. Li, Y. Zheng, C. Addo-Quaye, L. Zhang, A. Saini, G. Jagadeeswaran, M. Axtell, W. Zhang, R. Sunkar, Transcriptome-wide identification of microRNA targets in rice, The Plant Journal, 62(5):742-59, 2010.
· [AI] G. Jaeger and W. Zhang, An efficient algorithm for and phase transitions of the directed Hamiltonian cycle problem, J. Artificial Intelligence Research, 39:663-87, 2010.
· [PCMM] X. Wu, J. Cheng, P. Li, M. Yang, S. Qiu, P. Liu, J. Du. Mechano-sensitive transcriptional factor Egr-1 regulates insulin-like growth factor-1 receptor expression and contributes to neointima formation in vein grafts. Arterioscler Thromb Vasc Biol 30:471-476, 2010.
· [AI] R. Huang, Y. Chen and W. Zhang (2009) An optimal temporally expressive planner: Initial results and application to P2P network optimization, Proc. 19th Intern. Conf. on Automated Planning and Scheduling (ICAPS-09)
· [genom] J.A. Webster, J.R. Cibbs, J. Clarke, M. Ray, W. Zhang, P. Holmans, K. Rohrer, A. Zhao, L. Marlowe, M. Kaleem, D.S. McCorquodale III, C. Cuello, D. Leung, L. Bryden, P. Nath, V.L. Zisman, K. Joshipura, M.J. Huentelman, D. H Lince, K.D. Coon, D.W. Craig, J.V. Pearson, C.B. Heward, E.M. Reiman, D. Stephan, J. Hardy, A.J. Myers, Genetic control of human brain transcript expression in Alzheimer’s disease, American J. of Human Genetics, 84:445-58, 2009.
· [genom] S. Climer, G. Jaegerg, A. Templeton and W. Zhang, How frugal is mother nature with haplotypes? Bioinformatics, 25(1):68-74, 2009.
· [ncRNA] X. Zhou, R. Sunkar, H. Jin, J-K. Zhu and W. Zhang, Genome-wide identification and analysis of small RNAs originated from natural antisense transcripts in Oryza sativa, Genome Research, 19:70-8, 2009.
· [ncRNA] G. Jagadeeswaran, Y. Zheng, Y-f. Li, L.I. Shukla, J. Matts, P. Hoyt, S.L. Macmil, G.B. Wiley, B.A. Roe, W. Zhang, R. Sunkar, Cloning and characterization of small RNAs from Medicago truncatula reveals novel legume-specific and candidate microRNAs, New Phytologist, 184(1):85-98, 2009.
· [AI] Y. Chen, R. Huang, Z. Xing and W. Zhang, Long-distance mutual exclusion for planning, Artificial Intelligence, 173:365-91, 2009.
· [PCMM] S. Qiu, J. Wang, C. Yu, D. He. CENP-K and CENP-H may form coiled-coils in the kinetochores.Sci China Life Sci 52:352-359, 2009.
· [AI] Y. Chen, R. Huang and W. Zhang(2008) Fast planning by search in domain transition graphs, Proc. 23rd AAAI Conf on Artificial Intelligence(AAAI-2008)
· [genom] M. Ray J. Ruan and W. Zhang, Variations in the transcriptome of Alzheimer’s disease reveal molecular networks involved in cardiovascular diseases, Genome Biology, 9(10):R148, 2008.
· [ncRNA] Y. Xu, X. Zhou and W. Zhang, MicroRNA prediction with a novel ranking algorithm based on random walks, Bioinformatics, 24:i50-8, 2008.
· [ml/dm] J. Ruan and W. Zhang (2007) An efficient spectral algorithm for network community discovery and its applications to biological and social networks, Proc. IEEE Intern. Conf. on Data Mining (ICDM-2007), 2007.
· [AI] Z. Xing, Y. Chen and W. Zhang (2007) Long-distance mutual exclusion for propositional planning, Proc. 20th Intern. Joint Conf. on Artificial Intelligence (IJCAI-2007)
· [genom] M. Ray, S. Dharmarajan, J. Freudenberg, W. Zhang* and G.A. Patterson, Use of gene expression profiling and machine learning to understand primary graft dysfunction, American J. of Transplantation, 7:2396-405, 2007.
· [genom] X. Zhou, J. Ruan, G. Wang and W. Zhang, Characterization and identification of microRNA core promoters in four model species, PLoS Computational Biology, 3(3):e37, 2007.
· [genom] H. Zeng, L. Luo, W. Zhang, J. Zhou, Z. Li, H. Liu, T. Zhu, X. Feng and Y. Zhong, PlantQTL-GE: A database for searching candidate genes by gene expression and QTL information, Nucleic Acids Research, 35:D879-D882, 2007.
· [ncRNA] X. Zhou, G. Wang and W. Zhang, UV-B light responsive microRNA genes in Arabidopsis thaliana, Molecular Systems Biology, 3:103, 2007.
· [ml/dm] J. Ruan and W. Zhang (2006) Identification and evaluation of weak community structures in networks, Proc. 21st National Conf. on Artificial Intelligence, (AAAI-2006)
· [AI] Z. Xing, Y. Chen and W. Zhang (2006) An efficient hybrid strategy for temporal planning, Proc. 3rd Intern. Conf. on Integration of AI and OR Techniques for Constraint Programming for Combinatorial Optimization Problems (CP-AI-OR 2006)
· [AI] Z. Xing, Y. Chen and W. Zhang (2006) Optimal STRIPS planning by maximum satisfiability and accumulative learning, Proc. Intern. Conf. on Automated Planning and Scheduling (ICAPS-2006)
· [AI] Z. Xing, Y. Chen and W. Zhang (2006) MaxPlan: Optimal planning by decomposed satisfiability and backward reduction, Proc. 5-th Intern. Planning Competition, Intern. Conf. on Automated Planning and Scheduling (ICAPS-2006) (First Place Award, Optimal Planning Track)
· [genom] G. Wang and W. Zhang, A steganalysis-based approach to comprehensive identification and characterization of functional regulatory elements, Genome Biology, 7(6):R49, 2006.
· [genom] J.Ruan and W. Zhang, A two-dimensional regression tree approach to the modeling of gene expression regulations, Bioinformatics, 22(3):332-40, 2006.
· [ml/dm] S. Climer and W. Zhang, Rearrangement clustering: Pitfalls, remedies and applications, J. Machine Learning Research, 7:919-43, 2006.
· [AI] S. Climer and W. Zhang, Cut-and-solve: A linear search strategy for combinatorial optimization problems, Artificial Intelligence, 170(8-9):714-38, 2006.
· [ml/dm] G. Wang and W. Zhang* (2005) Build a dictionary, learn a grammar, decipher stegoscripts, and discover genomic regulatory elements,Proc. of 1st Annual RECOMB Satellite Workshop on Systems Biology and the Second Annual RECOMB Satellite Workshop on Regulatory Genomics, 2005.
· [ml/dm] X. Zhou, J. Ruan, G. Wang and W. Zhang* (2005) Computational characterization and identification of core promoters of microRNA genes in C. elegans, H. sapiens and A. thaliana, Proc. of 1st Annual RECOMB Satellite Workshop on Systems Biology and the Second Annual RECOMB Satellite Workshop on Regulatory Genomics, 2005.
· [AI] W. Zhangand M. Looks (2005) A novel local search algorithm for the Traveling Salesman Problem that exploits backbones, Proc. 19th Intern. Joint Conf. on Artificial Intelligence (IJCAI-2005)
· [genom] W. Zhang, J.Ruan, T-h. D.Ho, Y. You, T. Yu and R.S. Quatrano, Cis-regulatory element based targeted gene finding: Genome-wide identification of ABA and abiotic stress responsive genes in Arabidopsis thaliana, Bioinformatics, 21(14):3074-81, 2005.
· [genom] G. Wang, T. Yu and W. Zhang, WordSpy: Identify transcription factor biding motifsby building a dictionary and learning a grammar, Nucleic Acids Research, 33:W4126, 2005.
· [AI] R. Korf, W. Zhang, I. Thayer and H. Hohwald Frontier search, J. ACM, 52(5):71548, 2005.
· [AI] Z. Xing and W. Zhang, MaxSolver: An efficient exact algorithm for maximum satisfiability, Artificial Intelligence, 164(1-2):47-80, 2005.
· [AI] W. Zhang, G. Wang, Z. Xing and L. Wittenberg, Distributed stochastic search and distributed breakout: Properties, comparison and applications to constraint optimization problems in sensor networks, Artificial Intelligence, 161(1-2):55-87, 2005.
· [ml/dm] S. Climer and W. Zhang (2004) Take a walk and cluster genes: A TSP-based approach to optimal rearrangement clustering, Proc. Intern. Conf. on Machine Learning (ICML-2004)
· [ml/dm] J. Buhler, R. Souvenir, W. Zhang and R. Mitra (2004) Design of a high-throughput assay for alternative splicing using polymerase colonies, Proc. Pacific Symposium on Biocomputing, (PSB-2004), 2004
· [AI] Z. Xing and W. Zhang (2004) Efficient strategies for (weighted) maximum satisfiability, Proc. 10th Intern. Conf. on Principles and Practice of Constraint Programming (CP-2004)
· [AI] S. Climer and W. Zhang (2004) A linear search strategy with bounds, Proc. 14th Intern. Conf. on Automated Planning and Scheduling(ICAPS-2004)
· [AI] X. Zhang and W. Zhang (2004) An improved integer local search for complex scheduling problems, Proc. 14-th Intern. Conf. on Automated Planning and Scheduling(ICAPS-2004)
· [genom] J. Ruan, G. Stormo and W. Zhang, ILM: A web server for predicting RNA secondary structures with pseudoknots, Nucleic Acids Research, 32:W146-9, 2004.
· [genom] J. Ruan, G. Stormo and W. Zhang, An iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots, Bioinformatics, 20(1):58-66, 2004.
· [AI] W. Zhang, Configuration landscape analysis and backbone guided local search: Part I: satisfiability and maximum satisfiability, Artificial Intelligence, 158(1):1-26, 2004.
· [AI] A. K. Sen, A. Bagchi and W. Zhang, Average-case analysis of best-first search in directed acyclic graphs, Artificial Intelligence, 155(1-2):183-206, 2004.
· [AI] W. Zhang, Phase transitions and backbones of the asymmetric Traveling Salesman Problem, J. Artificial Intelligence Research, 20:471-97, 2004.
· [ml/dm] R. Souvenir, J. Buhler, G. Stormo and W. Zhang*(2003) Selecting degenerate multiplex PCR primers, Proc. Workshop on Algorithms in Bioinformatics (WABI-2003), 2003.
· [AI] W. Zhang (2003) Phase transitions of the asymmetric Traveling Salesman, Proc. 18th Intern. Joint Conf. on AI (IJCAI-2003)
· [AI] W. Zhang, A. Rangan and M. Looks (2003) Backbone guided local search for maximum satisfiability, Proc. 18-th Intern. Joint Conf. on AI (IJCAI-2003)
· [AI] W. Zhang, Z. Xing, G. Wang and L. Wittenburg (2003) An analysis and application of distributed constraint satisfaction and optimization algorithms in sensor networks, Proc. 2nd Intern. Joint Conf. on Autonomous Agents and Multi Agent Systems (AAMAS-2003), 2003
· [AI] W. Zhang and L. Wittenburg (2002) Distributed implicit coordination in sensor networks, in Proc of 1st Intern. Joint Conf on Autonomous Agents and Multi-Agent Systems(AAMAS-2002)
· [AI] W. Zhang and L. Wittenburg (2002) Distributed breakout revisited, in Proc of 18th National Conf on Artificial Intelligence (AAAI-2002)
· [AI] S. Climer and W. Zhang (2002) Search for backbones and fat: A limiting-crossing approach with applications, in Proc of 18th National Conf on Artificial Intelligence(AAAI-2002)
· [AI] A. K. Sen, A. Bagchi and W. Zhang (2002) An Average-case analysis of graph search, in Proc. 18th National Conf on Artificial Intelligence(AAAI-2002)
· [AI] W. Zhang, Iterative state-space reduction for flexible computation, Artificial Intelligence, 126(1-2):109-38, 2001.
· [AI] W. Zhang (2001) Phase transitions and backbones of 3-SAT and MAX3-SAT, in Proc. 7th Intern. Conf on Principles and Practice of Constraint Programming (CP-2001)
· [AI] J. Cirasella, D.S. Johnson, L. A. McGeoch and W. Zhang (2001) The asymmetric Traveling Salesman Problem: Algorithms, instance generators, and tests, in Proc 3rd Workshop on Algorithm Engineering and Experiments (ALENEX-2001)
· [ml/dm] W. Zhang (2000) Association-based multiple imputation in multivariate datasets: A summary, Proc of 16th Intern. Conf on Data Engineering (ICDE-2000), 2000
· [AI] W. Zhang (2000) Depth-first branch-and-bound vs. local search: A case study, Proc of 17th National Conf on Artificial Intelligence (AAAI-2000)
· [AI] R. E. Korf and W. Zhang (2000) Divide-and-conquer frontier search applied to multiple sequence alignment, Proc of 17th National Conf on Artificial Intelligence (AAAI-2000)
· [AI] H. Jung, M. Tambe, W. Zhang, and W-M. Shen (2000) Towards large-scale conflict resolution: Initial results, Proc of Intern. Conf on Multi-Agent Systems (ICMAS-2000)
· [AI] W. Zhang and R.Hill (2000) A template-based and pattern-driven approach to situation awareness and assessment in virtual humans, Proc of 4th Intern. Conf on Autonomous Agents (Agents 2000)
· [AI] M. Tambe and W. Zhang, Towards flexible team work in persistent teams: Extended report, Autonomous Agents and Multi-Agent Systems, 3(2):159-83, 2000. (Best of ICMAS-98).
· [AI] K.S. Tso, G.K. Tharp, W. Zhang and A.T. Tai (1999) A multi-agent operator Interface for unmanned aerial vehicles, Proc of 18th Digital Avionics Systems Conf. Best paper award
· [AI] W. Zhang, State-Space Search: Algorithms, Complexity, Extensions, and Applications, Springer-Verlag, New York, NY, 1999.
· [AI] W. Zhang (1998) Complete Anytime Beam Search, Proc 15th National Conf on Artificial Intelligence (AAAI-1998).
· [AI] W. Zhang (1998) Flexible and approximate computation through state-space reduction, Proc of 14th Annual Conf on Uncertainty in Artificial Intelligence (UAI-1998)
· [AI] M. Tambe and W. Zhang (1998) Towards flexible teamwork in persistent teams, Proc of Intern. Conf on Multi-Agent Systems (ICMAS-1998). Selected as the Best of ICMAS-98.
· [AI] Y. Arens, W. Zhang, Y. Lee, J. Dukes-Schlossberg, and Marc Zev (1998) Warfighter’s information package, Proc of 10th Innovative Applications of Artificial Intelligence Conf (AAAI/IAAI-1998).
· [AI] W. Zhang (1996) Forward estimation for game-tree search, Proc of 13th National Conf on Artificial Intelligence (AAAI-1996)
· [AI] W. Zhang and R. E. Korf, A study of complexity transitions on the asymmetric Traveling Salesman Problem, Artificial Intelligence, 81(1-2):223-39, 1996.
· [AI] J. C. Pemberton and W. Zhang, Epsilon-transformation: Exploiting phase transitions to solve combinatorial optimization problems, Artificial Intelligence, 81(1-2):297-325, 1996.
· [AI] W. Zhang and R.E.Korf, Performance of linear-space search algorithms,Artificial Intelligence , 79(2):241-92, 1995.
· [AI] W. Zhang and J.C. Pemberton (1994) Epsilon-transformation: Exploiting complexity transitions to solve combinatorial optimization problems -Initial results, Proc of 12th National Conf on Artificial Intelligence (AAAI-1994)
· [AI] W. Zhang and R.E. Korf (1993) Depth-first vs. best-first search: New results, Proc of 11th National Conf on Artificial Intelligence (AAAI-1993)
· [AI] W. Zhang and R.E. Korf (1992) An average-case analysis of branch-and-bound with applications: Summary of results, Proc of 10th National Conf on Artificial Intelligence (AAAI-1992)
· [AI] W. ZhangRepresentation of assembly and automatic robot planning by Petri net, IEEE Trans. on Systems, Man and Cybernetics, 19(2):418-22, 1989.