国家健康医疗大数据研究院 生物信息大数据中心
山东大学青年学者未来计划
中华预防医学会肾脏病预防与控制专业委员会 专委
联系方式：邮箱 houqingzhen@sdu.edu.cn；手机 18853 122360
个人网站：https://faculty.sdu.edu.cn/houqingzhen/
研究方向和领域
生物信息学；蛋白质功能与结构预测；机器学习/深度学习方法分析解决生物学医学问题；单细胞转录组分析
主要致力于挖掘生物医学大数据的生物学意义，分析生物大分子结构和功能的关联。研究方向包括利用机器学习以及深度学习的方法，发展预测蛋白质结构功能的算法及工具；整合表观基因组学，转录组学和蛋白组学进行跨组学分析，探索疾病的分子机制；聚焦单细胞转录组测序数据分析，寻找细胞间异质性和差异表达基因等。近年来在生物信息学领域国际期刊发表论文多篇，其中在计算生物学一区TOP期刊Bioinformatics上发表第一作者论文5篇，同时担任Bioinformatics, PeerJ, Computational Biology and Chemistry 等多个杂志审稿人。
教育经历
2009.06-2011.06 发育生物学 武汉大学 硕士 导师：赵洁教授
2012.01-2016.12 生物信息学 荷兰阿姆斯特丹自由大学（Vrije Universiteit Amsterdam）博士
导师：Prof. Jaap Heringa; K. Anton Feenstra
工作经历
2017.01-2019.12 结构生物信息学 比利时布鲁塞尔自由大学（Université libre de Bruxelles）博士后
导师：Prof. Marianne Rooman
2020.03- 山东大学公共卫生学院 副研究员
近五年代表性著作（截至2021年7月）：
1. Hou, Q., Stringer, B., Waury, K., Capel, H., Haydarlou, R., Xue, F., Abeln, S., Heringa, J., & Feenstra, A., (2021). SeRenDIP-CE: Sequence-based Interface Prediction for Conformational Epitopes. Bioinformatics(Accepted). [数学与计算生物学1区，TOP期刊]
2. Hou, Q., Pucci, F., Ancien, F., Kwasigroch, J. M., Bourgeas, R., & Rooman, M. (2021). SWOTein: A structure-based approach to predict stability Strengths and Weaknesses of prOTEINs. Bioinformatics, btab034.[数学与计算生物学1区，TOP期刊]
3. Hou, Q., Kwasigroch, J. M., Rooman, M., & Pucci, F. (2020). SOLart: a structure-based method to predict protein solubility and aggregation.Bioinformatics,36(5), 1445-1452.[数学与计算生物学1区，TOP期刊]
4. Hou, Q., De Geest, P. F., Griffioen, C. J., Abeln, S., Heringa, J., & Feenstra, K. A. (2019). SeRenDIP: SEquential REmasteriNg to DerIve profiles for fast and accurate predictions of PPI interface positions. Bioinformatics, 35(22), 4794-4796.[数学与计算生物学1区，TOP期刊]
5. Hou, Q., De Geest, P. F., Vranken, W. F., Heringa, J., & Feenstra, K. A. (2017). Seeing the trees through the forest: sequence-based homo-and heteromeric protein-protein interaction sites prediction using random forest. Bioinformatics, 33(10), 1479-1487.[数学与计算生物学1区，TOP期刊]
6. Hou, Q., Dutilh, B. E., Huynen, M. A., Heringa, J., & Feenstra, K. A. (2015). Sequence specificity between interacting and non-interacting homologs identifies interface residues–a homodimer and monomer use case. BMC bioinformatics, 16(1), 1-12.[数学与计算生物学2区]
7. Hou, Q., Lensink, M. F., Heringa, J., & Feenstra, K. A. (2016). Club-martini: selecting favourable interactions amongst available candidates, a coarse-grained simulation approach to scoring docking decoys. PloS one,11(5), e0155251.[综合性期刊3区]
8. Hou, Q., Bourgeas, R., Pucci, F., & Rooman, M. (2018). Computational analysis of the amino acid interactions that promote or decrease protein solubility. Scientific reports,8(1), 1-13.[综合性期刊3区]
9. Mbaye, M. N*., Hou, Q.*, Basu, S., Teheux, F., Pucci, F., & Rooman, M. (2019). A comprehensive computational study of amino acid interactions in membrane proteins. Scientific reports,9(1), 1-14.* shared first author [综合性期刊3区]
参加国际会议(部分)：
1. Mapping the Protein-protein Interaction Free Energy Landscape: Energy-based approach to scoring docking decoys. NSBM Spring meeting 2015, Bioinformatics and System Biology (BioSB), the Netherlands (2015)，Oral presentation
2. CLUB-MARTINI: Selecting Favorable Interactions amongst available candidates: a coarse-grained simulation approach to scoring docking decoys. Benelux Bioinformatics Conference (BBC), Belgium (2015), Oral presentation
3. SOLart: a structure-based method to predict protein solubility and aggregation. Bioinformatics Italian Society (2019), Oral presentation
4. Predicting Protein Interactions: Sequence Analysis of Homodimers. European Conference on Computational Biology (ECCB)(2012)
5. Coarse-grained simulation: fast and accurate calculation of Protein Binding Affinity. The Netherlands Bioinformatics Centre (NBIC)(2013)
6. Mapping the Protein-protein Interaction Free Energy Landscape. ECCB (2014)
7. Mapping the Protein-protein Interaction Free Energy Landscape: Energy-based approach to scoring docking decoy. BioSB (2015)
8. Computational analysis of the amino acid interactions that promote or decrease protein solubility. ECCB (2018)
9. SOLart: a structure-based method to predict protein solubility and aggregation.ISMB (2019)
教学活动:
协助指导硕士本科生(Daily supervisor):
·Predicting Protein Interaction Specificity using Sequence Harmony with Neighbour Support (Margriet Wassenaar)
·Calculating correlated mutations at the protein interface: free energies of pairwise mutants (Helen Kruize)
·Mutational analysis of the MP1-p14 protein complex: Comparing evolutionary likelihood of mutations with difference in binding energy (Viktor Tsjebanov)
·A computational saturated mutation analysis with the MARTINI coarse-grained force field (Jochem Bijlard)
·Clustering docking decoys based on RMSD matrices (Matthieu Beukers)
·Protein Dynamics and Sequence Specificity in Interface Prediction (Paul De Geest)
·Selecting docking conformations based on predicted interface and interaction strength (Sije van der Veen)
·Contribution to the supervision of PhD thesis of Mame Ndew Mbaye (Analyse bioinformatique des interactions intra-protéine et protéine-ligand. Application aux protéines membranaires et à la résistance aux ß-lactames, September 2019)
