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) 

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. (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)