葡京娱乐

聚焦于设计和开发人工智能算法对大规模生物医学数据进行处理、挖掘和分析，探索疾病的机理，为加速新药研发提供重要研究方案，主要包括：

一、疾病发现

随着高通量测序技术的不断发展，积累了大量DNA序列，高效且更准确的DNA序列数据处理和分析对疾病发现有着至关重要的作用。以构建高完整性、高质量、高分辨率的基因组序列为目标，研究内容包括序列匹配、序列纠错、单倍型基因组组装等。

二、药物设计

药物设计是一门涵盖生物学、化学、药理学等多学科领域的综合性研究过程，旨在寻找并开发可用于治疗特定疾病的药物。这一过程是建立在疾病发现基础之上，是实现“精准医疗”的核心内容。研究内容包括药物靶点预测、药物性质预测、分子生成等。

国家自然科学基金面上项目，面向多肽药物设计的深度学习方法研究（62372159），2024-2027。

国家自然科学基金青年项目，高通量测序的序列数据压缩算法研究（62102140），2022-2024。

每年招收硕士研究生3名

2024级：**箫、**正、**玲、**晨（博士生；研究方向：第三代测序数据的处理与分析）

已毕业学生及毕业后第一份工作

2021级：陶**（研究生国奖，发表CCF B BIB和一区BMC Biology论文，澳洲八大阿德莱德读博）、周**（发表Information Sciences一区论文，联想）

主要论文 (^*为通讯作者) 

Xixi Yang, Yanjing Duan, Zhixiang Cheng, Kun Li, Yuansheng Liu^*, Xiangxiang Zeng, and Dongsheng Cao^*, MPCD: A multi-task graph Transformer for molecular property prediction by integrating common and domain knowledge. Journal of Medicinal Chemistry, 2024.  (药物化学顶级期刊、中科院一区)

Yuansheng Liu, Yichen Li, Enlian Chen, Jialu Xu, Wenhai Zhang, Xiangxiang Zeng, Xiao Luo^*, Repeat and haplotype aware error correction in nanopore sequencing reads with DeChat. Communications Biology. 2024. (Nature旗下期刊、中科院一区)

Wen Tao, Xuan Lin, Yuansheng Liu^*, Li Zeng, Tengfei Ma, Ning Cheng, Jing Jiang, Xiangxiang Zeng, Sisi Yuan^*, Bridging chemical structure and conceptual knowledge enables accurate prediction of compound-protein interaction. BMC Biology, 2024, 22, 248. (中科院一区)

Tao Tang, Tianyang Li, Weizhuo Li, Xiaofeng Cao, Yuansheng Liu^*, Xiangxiang Zeng, Anti-symmetric-based framework for balanced learning of protein–protein interaction. Bioinformatics, 2024, 40(10): btae603.

Yuansheng Liu, Zhenran Zhou, Xiaofeng Cao^*, Dongsheng Cao, Xiangxiang Zeng^*, Effective drug-target affinity prediction via generative active learning. Information Sciences, 2024, 679, 121135. (中科院一区)

Xiangzhen Shen, Zimeng Li, Yuansheng Liu^*, Bosheng Song, Xiangxiang Zeng, PEB-DDI: A Task-Specific Dual-View Substructural Learning Framework for Drug-Drug Interaction Prediction. IEEE Journal of Biomedical and Health Informatics, 2024, 28(1): 569-579. (中科院一区)

Yuansheng Liu, Xiangzhen Shen, Yongshun Gong, Yiping Liu, Bosheng Song, Xiangxiang Zeng, Sequence Alignment/Map format: A comprehensive review of approaches and applications. Briefings in Bioinformatics, 2023, 24(5): bbad320. 

Wen Tao, Yuansheng Liu^*, Xuan Lin, Bosheng Song, Xiangxiang Zeng, Prediction of multi-relational drug-gene interaction via Dynamic hyperGraph Contrastive Learning. Briefings in Bioinformatics, 2023, 24(5): bbad371.

Xixi Yang, Li Fu, Yafeng Deng, Yuansheng Liu^*, Dongsheng Cao^*, Xiangxiang Zeng^*,  GPMO: Gradient perturbation-based contrastive learning for molecule optimization. IJCAI, 2023: 4940-4948. (CCF A类会议)

Xiangxiang Zeng, Xinqi Tu, Yuansheng Liu^*, Xiangzheng Fu, Yansen Su. Toward better drug discovery with knowledge graph, Current Opinion in Structural Biology, 2022, 72, 114-126. (中科院二区) ESI高被引论文，ESI热点论文

Yuansheng Liu, Jinyan Li. Hamming-Shifting graph of genomic short reads: efficient construction and its application for compression. PLOS Computational Biology, 2021, 17 (7), e1009229. (生物信息学顶刊，中科院小类一区)

Yuansheng Liu, Xiaocai Zhang, Quan Zou, Xiangxiang Zeng. Minirmd: accurate and fast duplicate removal tool for short reads via multiple minimizers. Bioinformatics, 2021, 37 (11), 1604-1606. (生物信息学顶刊，中科院小类一区)

Yuansheng Liu, Limsoon Wong, Jinyan Li. Allowing mutations in maximal matches boosts genome compression performance. Bioinformatics, 2020, 36(18): 4675-4681. (生物信息学顶刊，中科院小类一区)