本人从事计算生物及生物信息学领域的研究，包括应用机器学习算法解决生物学中的难题，利用统计方法解释生物学中的有趣现象，重点研究蛋白质的结构及功能。至今已共发表SCI期刊论文32篇，包括发表在美国科学院院报PNAS (影响因子: 9.412)，生物学领域的Top期刊Nucleic Acids Research (影响因子: 11.501，3篇), Nature 出版集团旗下的期刊Cell Death & Differentiation（影响因子: 10.717），Science 子刊Science Signaling（Top期刊，影响因子: 7.359）等上的科研论文。根据web of science数据，论文共被引近两千次，单篇最高引用次数为200余次。作为课题负责人主持国家自然科学基金优秀青年基金、面上项目、青年基金各1项；作为骨干成员参与完成863项目1项；参与完成国家应急管理项目1项。

• 2010-9 — 2014-11
  加拿大阿尔伯塔大学
  软件工程与智能系统
  研究生(博士)毕业
• 2005-9 — 2008-6
  湘潭大学
  应用数学
  研究生(硕士)毕业
• 2001-9 — 2005-6
  衡阳师范学院
  数学与应用数学
  本科(学士)

• 2021-4 — 至今
   数学与交叉科学研究中心  山东大学 
• 2015-1 — 2021-3
   应用数学中心  天津大学 
• 2018-9 — 2019-9
   生物化学系  美国华盛顿大学 

1.生物信息学

(1) CLIP: Accurate prediction of disordered linear interacting peptides (LIPs) from protein sequences using co-evolutionary information.Briefings In Bioinformatics

(2) Du, Zongyang.Toward the assessment of predicted inter-residue distance.Bioinformatics.2022,38 (4):962

(3) Du, Zongyang.The trRosetta server for fast and accurate protein structure prediction.NATURE PROTOCOLS.2021,16 (12):5634

(4) Su, Hong.Improved Protein Structure Prediction Using a New Multi-Scale Network and Homologous Templates.ADVANCED SCIENCE.2021,8 (24)

(5) Ye, Lisha.Improved estimation of model quality using predicted inter-residue distance.Bioinformatics.2021,37 (21):3752

(6) Song, Ruiyang.Accurate Sequence-Based Prediction of Deleterious nsSNPs with Multiple Sequence Profiles and Putative Binding Residues.BIOMOLECULES.2021,11 (9)

(7) Protein contact prediction using metagenome sequence data and residual neural networks.Bioinformatics.2020,36 (1):41-48

(8) APOD: accurate sequence-based predictor of disordered flexible linkers.Bioinformatics.2020,36 (S2):754-761

(9) Improved protein structure prediction using predicted inter-residue orientations.PNAS.2020,117 (3):1496-1503

(10) Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins.Cellular & Molecular Life Science.2020,77 (1):149-160

(11) Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions.Computational & Structural Biotechnology Journal.2019,17 :454-462

(12) mTM-align: a server for fast protein structure database search and multiple protein structure alignment.Nucleic Acids Research.2018,46 :W380-W386

(13) COACH-D: improved protein-ligand binding site prediction with refined ligand-binding poses through molecular docking Nucleic.Nucleic Acids Research.2018,46 :W438-W442

(14) Improving sequence-based prediction of protein-peptide binding residues by introducing intrinsic disorder and a consensus method.Journal of Chemical Information & Modeling.2018,58 :1459-1468

(15) CoABind: a novel algorithm for Coenzyme A (CoA)- and CoA derivatives-binding.Bioinformatics.2018,34 :2598-2604

(16) Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in a thousand proteomes from all domains of life.Cellular & Molecular Life Science.2015,72 (1):137-151

(17) High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder.Nucleic Acids Research.2015,43 (18):e121

(18) A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome.Cellular & Molecular Life Science.2014,71 (8):1477-1504

(19) Interplay between PDIA6 and miR-322 controls adaptive response to disrupted endoplasmic reticulum calcium homeostasis.Science Signaling.2014,7 (329):ra54

(20) Resilience of death: intrinsic disorder in proteins involved in the programmed cell death.Cell Death & Differentiation.2013,20 :1257-1267

1. 生物信息学, 国家自然科学基金, 2022/08/05

2. 固有无序片段功能的系统分析及其预测算法研究, 国家自然科学基金, 2019/01/01-2022/12/31

3. 与RNA、DNA及蛋白质绑定的固有无序片段的分析及预测, 国家自然科学基金-2018/12/31, 结题

4. 计算生物和生物信息学-2018/12/31, 结题

5. 生物大数据开发与利用关键技术研究, 863计划-2017/12/31, 结题

6. 天津应用数学中心平台建设, 国家自然科学基金-2016/12/31, 结题

1. 高等数学（1）

1. Disordered RNA binding region prediction with DisoRDPbind

2. Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind