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姓 名:李富义

职 称:教  授

办公室:信息工程学院414

邮 箱:fuyi.li@nwafu.edu.cn

 


最新消息

· 最新接收论文:Liu Q, Fang H, Wang M, Li S, Coin LJM, Li F*, Song J*. “DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions”. Bioinformatics. 2022, in press. (IF=6.937, Top期刊, JCR Q1, CCF B类),论文被AI in Graph公众号报道:https://mp.weixin.qq.com/s/vrEU7kjmWAWg_DelKK_Kog

· International Journal of Molecular Sciences杂志(SCI, IF 5.924)特刊“Bioinformatics of RNA: Recent Advance and Open Challenge”征稿,欢迎投稿

· Algorithm杂志(SCI, Q2)特刊“Machine Learning in Mathematical and Computational Biology”征稿,欢迎投稿


基本信息

李富义,男,博士,教授,博士生导师,澳大利亚墨尔本大学医学、牙医与健康科学学院(Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne)荣誉研究员(Honorary Fellow),中国计算机学会(CCF)会员,澳大利亚生物信息学和计算生物学学会(ABACBS)会员,澳大利亚生物化学和分子生物学学会(ASBMB)会员。2020年5月于澳大利亚蒙纳士大学(Monash University)生物医学发现研究所获得博士学位,博士期间师从国际生物信息学专家 Jiangning Song教授和澳大利亚科学院院士、蒙纳士大学抗菌素耐药性研究中心主任Trevor Lithgow教授,毕业后加入澳大利亚墨尔本大学(The University of Melbourne)Peter Doherty感染与免疫研究所担任生物信息学研究员(Level B)。2022年6月起任西北农林科技大学信息工程学院长聘教授。

主要研究方向为机器学习、数据挖掘和生物信息学等。近年来在Nature Communications, Nucleic Acid Research, Bioinformatics, Briefings in Bioinformatics, Genomics Proteomics & BioinformaticsMolecular Microbiology 等国际知名期刊上发表论文55篇(中科院大类一区26篇),其中有11篇文章被Clarivate评为高被引文章,2篇为热点文章,Google Scholar总引用次数达到2392次(H-index 36, i10-index 24, 2022年7月)。个人多篇一作文章受到澳大利亚科学院院士Trevor Lithgow教授,Monash数据未来研究所主任Geoff Webb教授(IEEE fellow),京都大学生物信息学中心Tatsuya Akutsu教授等相关领域权威专家的认可与肯定。近年来,研发了二十多款生物信息学数据库、软件和分析平台,这些工具在过去五年内得到了80多个国家和地区的国际用户超过120,000次的使用,这些生物信息学软件已经被发表在包括Cell, PNAS, Nature Chemical BiologyNucleic Acids Research等国际高水平期刊的研究工作引用1300余次,产生了较为广泛的影响力。


团队招生信息

课题组诚招具有责任心、学习积极主动和具有较强的自律性的博士后加盟,欢迎硕士和博士生推免报考!有意加盟团队的优秀学者学子,请与我电话、微信(15229251614同号)或邮件联系。


博士生招生专业方向:0828Z2 农业工程

硕士生招生专业方向:0812 计算机科学与技术(学硕)

                                    0854 电子信息(专硕): 包括计算机技术(085404)、人工智能(085410)

                                    095136 农业工程与信息技术(专硕)


团队和澳大利亚Monash大学、墨尔本大学、格里菲斯大学、迪肯大学,日本京都大学等国际一流高校保持长期合作开展科学研究,学术资源丰富,能为学生的成才和发展提供强有力的支持和帮助。


团队将为你提供:

· 前往国内外知名大学进行学术交流的资助和机会。团队与很多国际一流的研究团队保持长期合作交流,学生将有机会前往世界一流的大学,如Monash大学、Monash大学苏州校区、墨尔本大学和京都大学等一流研究环境访问交流,从事前沿研究项目,获得有关技术的宝贵经验。

· 团队氛围融洽,学生将会和来自海内外的师兄师姐一起进步。团队成员来自于Monash大学,墨尔本大学,大连海事大学等国内外一流高校,你将获得优秀师兄师姐的帮助,助你冲击顶刊顶会。

· 团队将会为优秀毕业生进一步深造和发展提供强力的支持和推荐,优秀毕业生将有机会获得Monash大学(QS世界排名59)、墨尔本大学(QS世界排名37)等世界一流高校的全额奖学金,或者加盟燃石医学(上海)、百图生科等一流的互联网生物制药公司的机会。


欢迎满足下列条件的同学报考:

(1)具有较强的编程能力;

(2)对数据挖掘、机器学习和软件设计有浓厚兴趣。

(3)具有较好的英语水平;


此外,团队接受优秀的本科生参与科研训练,有意者请邮箱或微信联系。


教育经历

· 2017年02月-2020年05月,澳大利亚蒙纳士大学,Biomedical Discovery Institute,生物信息学,博士

· 2013年09月-2016年06月,西北农林科技大学,信息工程学院,软件工程,工学硕士

· 2009年09月-2013年06月,西北农林科技大学,信息工程学院,软件工程,工学学士


工作经历

· 2022年06月-至今,西北农林科技大学,信息工程学院,教授

· 2020年09月-2022年06月,澳大利亚墨尔本大学,Peter Doherty感染与免疫研究所,生物信息学研究员

· 2020年05月-2020年09月,澳大利亚蒙纳士大学,生物医学发现研究所(BDI),博士后

· 2020年08月-2020年12月,澳大利亚蒙纳士大学,信息技术学院(FIT),数据科学助教

· 2018年10月-2020年05月,澳大利亚蒙纳士大学,生物医学发现研究所(BDI),生物信息学助研

· 2017年07月-2018年07月,澳大利亚蒙纳士大学,生物化学和分子生物学系,生物信息学助教


获奖情况

· 2021年,FAOBMB青年科学家奖(Young Scientist Programme award)

· 2020年,Monash大学发表论文奖(Postgraduate Publications Award)

· 2020年,第十届生物科学,生物化学和生物信息学国际会议最佳报告奖(Best presentation award)

· 2020年,国家优秀自费留学生奖学金(全球500名)

· 2016年,Monash大学全额奖学金


学术兼职

· 担任国际期刊Frontiers in Bioinformatics的编辑;

· 担任国际期刊BioMed Research International的编辑;

· 担任国际期刊Current Gene Therapy的编辑;

· 担任国际期刊Artificial Intelligence and Applications的编辑

· 担任国际期刊International Journal of Molecular Sciences的客座编辑;

· 担任国际期刊Algorithms的客座编辑;

· 曾担任第30届国际基因组信息学大会(GIW 2019)的程序委员会成员;

· 担任Bioinformatics, Briefings in Bioinformatics, BMC Bioinformatics, PLOS Computational Biology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information FusionPattern recognition等机器学习和生物信息学主流期刊的审稿人。


学术报告和国际会议

国际会议:

1. 第16届亚洲及大洋洲生物化学与分子生物学家联盟会议 (FAOBMB 2021),新西兰基督城 (在线会议),2021年11月22-25日,分组报告

2. 第十届生物科学,生物化学和生物信息学国际会议 (ICBBB 2020),日本京都,2020年1月19-22日,特邀报告: “Leveraging the Power of Data-Driven Machine Learning Techniques to Address Significant Biomedical Classification Problems”.

3. 第十届生物科学,生物化学和生物信息学国际会议 (ICBBB 2020),日本京都,2020年1月19-22日,分组报告

4. 第一届国际人工智能会议 (A2IC 2018),西班牙巴塞罗那,2018年11月21-23日,分组报告

5. 第12届创新计算、信息和控制国际会议,日本久留米,2017年8月28-30日,分组报告


学术交流:

1. 2020年1月23日,日本京都大学生物信息学中心,学术报告:“A data-driven bioinformatic investigation into protein post-translational modifications”.

2. 2017年9月1日,日本京都大学生物信息学中心,学术报告:“PROSPERous: integrative high-throughput prediction of the substrate cleavage sites for 90 proteases with improved accuracy”.


学术成果

学术论文 (*通讯作者,†并列一作)

(论文全文请前往ResearchGate: https://www.researchgate.net/profile/Fuyi-Li 查阅)


2022年:

1. Peng X, Wang X, Guo Y, Ge Z*, Li F*, Gao X*, Song J*. “RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins”. Briefings in Bioinformatics. 2022, bbac215. (IF=13.994, 中科院大类一区, Top期刊, CCF B类).

2. Wang X, Li F*, Xu J, Rong J, Webb GI, Ge Z*, Li J, Song J*. “ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning”. Briefings in Bioinformatics. 2022, 23(2), bbac031.(IF=13.994, 中科院大类一区, Top期刊, CCF B类).

3. Zhang M†, Jia C†, Li F†, Li C†, Zhu Y, Akutsu T, Webb GI, Zou Q, Coin JML, Song J. “Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction”. Briefings in Bioinformatics. 2022, bbab551. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

4. Li F, Dong S, Leier A, Han M, Guo X, Xu J, Wang X, Pan S, Jia C, Zhang Y, Webb GI, Coin LJM, Li C, Song J. “Positive-unlabeled learning in bioinformatics and computational biology: a brief review”. Briefings in Bioinformatics. 2021, 23(1), bbab461. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

5. Li F, Guo X, Xiang D, Pitt EM, Bainomugisa A, Coin LJM. “Computational analysis and prediction of PE_PGRS proteins using machine learning”. Computational and Structural Biotechnology Journal. 2022. 20, 662-674. (IF=7.271, 中科院大类二区, JCR Q1).

6. Liu Q, Fang H, Wang M, Li S, Coin LJM, Li F*, Song J*. “DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions”. Bioinformatics. 2022, in press. (IF=6.937, 中科院大类二区(小类一区), Top期刊, JCR Q1, CCF B类)

7. Chen Z, Liu X, Zhao P, Li C, Wang Y, Li F, Akutsu T, Bain C, Gasser RB, Li J, Yang Z, Gao X, Kurgan L, Song J. “iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets”. Nucleic Acids Research. 2022, gkac351. (IF=19.16, 中科院大类一区, Top期刊, JCR Q1).

8. Wang M†, Li F†, Wu H, Liu Q, Li S. “PredPromoter-MF (2L): A Novel Approach of Promoter Prediction Based on Multi-source Feature Fusion and Deep Forest”. Interdisciplinary Sciences: Computational Life Sciences. 2022, doi:10.1007/s12539-022-00520-4. (IF=3.492, 中科院大类二区,  JCR Q2)

9. Chen J†, Li F†, Wang M, Li J, Marquez-Lago TT, Leier A, Revote J, Li S, Liu Q, Song J. “BigFiRSt: a software program using big data technique for mining simple sequence repeats from large-scale sequencing data”. Frontiers in Big Data. 2022, 4, 727216.

10. Packiam KAR, Ooi CW, Li F, Mei S, Tey BT, Ong HF, Song J, Ramanan RN. “PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in Escherichia coli”. Computational and Structural Biotechnology Journal. 2022, 20, 2909-2920. (IF=7.271, 中科院大类一区, JCR Q1)



2021年

1. Li F, Guo X, Jin P, Chen J, Xiang D, Song J, Coin LJM. “Porpoise: a new approach for accurate prediction of RNA pseudouridine sites”. Briefings in Bioinformatics. 2021, 22(6), bbab245. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

2. Li F, Chen J, Ge Z, Wen Y, Yue Y, Hayashida M, Baggag A, Bensmail H, Song J. “Computational prediction and interpretation of both general and specific types of promoters in Escherichia coli by exploiting a stacked ensemble-learning framework”. Briefings in Bioinformatics. 2021, 22(2), 2126-2140. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).

3. Liu Q, Chen J, Wang Y, Li S, Jia C*, Song J*, Li F*. “DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites”. Briefings in Bioinformatics. 2021, 22(3), bbaa124. (IF=13.994, 中科院大类一区, Top期刊, CCF B类) (Clarivate高被引论文).

4. Jia C, Zhang M, Fan C, Li F*, Song J*. “Formator: predicting lysine formylation sites based on the most distant undersampling and safe-level synthetic minority oversampling”. IEEE/ACM transactions on computational biology and bioinformatics. 2021 18(5), 1937-1945. (IF=3.71, 中科院三区(小类二区), JCR Q1, CCF B类).

5. Mei S†, Li F†, Xiang D, Ayala R, Faridi P, Webb GI, Illing PT, Rossjohn J, Akutsu T, Croft NP, Purcell AW, Song J. “Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I molecules”. Briefings in Bioinformatics. 2021, 22(5), bbaa415. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

6. Liang X†, Li F†, Chen J, Li J, Wu H, Li S, Song J, Liu Q. “Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification”. Briefings in Bioinformatics. 2021, 22(4), bbaa312. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

7. Wang Y, Coudray N, Zhao Y, Li F, Hu C, Zhang YZ, Imoto S, Tsirigos A, Webb GI, Daly RJ, Song J. “HEAL: an automated deep learning framework for cancer histopathology image analysis”. Bioinformatics. 2021, 37(22), 4291-4295. (IF=6.937, 中科院二区(小类一区), Top期刊, JCR Q1, CCF B类).

8. Iqbal S, Li F, Akutsu T, Ascher DB, Webb GI, Song J. “Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations”. Briefings in Bioinformatics. 2021, 22(6), bbab184. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

9. Chai D, Jia C*, Zheng J, Zou Q, Li F*. “Staem5: a novel computational approach for accurate prediction of m5C site”. Molecular Therapy-Nucleic Acids. 2021, 26, 1027-1034. (IF=8.886, 中科院大类二区, JCR Q1).

10. Xu J, Li F, Leier A, Xiang D, Shen HH, Marquez-Lago TT, Li J, Yu DJ, Song J. “Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides”. Briefings in Bioinformatics. 2021, 22(5), bbab083. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

11. Wang Y, Li F, Bharathwaj M, Rosas NC, Leier A, Akutsu T, Webb GI, Marquez-Lago TT, Li J, Lithgow T, Song J. “DeepBL: a deep learning-based approach for in silico discovery of beta-lactamases”. Briefings in Bioinformatics. 2021, 22(4), bbaa301. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1).

12. Yan Zhu†, Li F†, Xiang D, Akutsu T, Song J, Jia C. “Computational identification of eukaryotic promoters based on cascaded deep capsule neural networks”. Briefings in Bioinformatics. 2021, 22(4), bbaa299. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

13. Chen Z, Zhao P, Li C, Li F, Xiang D, Chen YZ, Akutsu T, Daly RJ, Webb GI, Zhao Q, Kurgan L, Song J. “iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization”. Nucleic Acids Research. 2021, 49(10), e60. (IF=19.16, 中科院大类一区, Top期刊, JCR Q1).

14. Chen H, Li F, Wang L, Jin Y, Chi CH, Lukasz K, Song J, Shen J. “Systematic evaluation of machine learning methods for identifying human–pathogen protein–protein interactions”. Briefings in Bioinformatics. 2021, 22(3), bbaa068. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

15. Zhu YH, Hu J, Ge Fang, Li F, Song J, Zhang Y, Yu DJ. “Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features”. Briefings in Bioinformatics. 2021, 22(3), bbaa076. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

16. Ozols M, Eckersley A, Platt CI, Stewart C, Hibbert SA, Revote J, Li F, Griffiths C, Watson R, Song J, Bell M, Sherratt MJ. “Predicting Proteolysis in Complex Proteomes Using Deep Learning”. International journal of molecular sciences. 2021, 22(6), 3071. (IF=6.208, 中科院大类二区, JCR Q1).



2020年:

1. Li F, Chen J, Leier A, Marquez-Lago TT, Liu Q, Wang Y, Revote J, Smith AI, Akutsu T, Webb GI, Kurgan L, Song J. “DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites”. Bioinformatics. 2020, 36(4), 1057-1065. (IF=6.937, 中科院大类二区(小类一区), Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).

2. Li F, Fan C, Marquez-Lago TT, Leier A, Revote J, Jia C, Zhu Y, Smith AI, Webb GI, Liu Q, Wei L, Li J, Song J. “PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact”. Briefings in Bioinformatics. 2020, 21(3), 1069-1079. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

3. Li F, Leier A, Liu Q, Wang Y, Xiang D, Akutsu T, Webb GI, Smith AI, Marquez-Lago TT, Li J, Song J. “Procleave: Predicting Protease-Specific Substrate Cleavage Sites by Combining Sequence and Structural Information”. Genomics, Proteomics & Bioinformatics. 2020, 18(1), 52-64. (IF=7.691, 中科院大类一区, Top期刊, JCR Q1).

4. Jia C, Bi Y, Chen J, Leier A, Li F*, Song J*. “PASSION: an ensemble neural network approach for identifying the binding sites of RBPs on circRNAs”. Bioinformatics. 2020, 36(15), 4276-4282. (IF=6.937, 中科院二区(小类一区), Top期刊, JCR Q1, CCF B类).

5. Bi Y, Xiang D, Ge Z, Li F*, Jia C*, Song J*. “An interpretable prediction model for identifying N7-methylguanosine sites based on XGBoost and SHAP”. Molecular Therapy-Nucleic Acids. 2020, 22, 362-372. (IF=8.886, 中科院大类二区, JCR Q1).

6. Li P, Zhang H, Zhao X, Li F*, Song J*. “Pippin: A Random Forest-based method for identifying presynaptic and postsynaptic neurotoxins”. Journal of Bioinformatics and Computational Biology. 2020, 18(2), 2050008. (IF=1.122, JCR Q3).

7. Zhu Y, Jia C, Li F*, Song J*. “Inspector: A lysine succinylation predictor based on edited nearest-neighbor undersampling and adaptive synthetic oversampling”. Analytical Biochemistry. 2020, 593, 113592. (IF=3.365, JCR Q2).

8. Chen Z, Zhao P, Li F, Wang Y, Smith AI, Webb GI, Akutsu T, Baggag A, Bensmail H, Song J. “Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences”. Briefings in Bioinformatics. 2020, 21(5), 1676-1696. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

9. Chen Z, Zhao P, Li F, Marquez-Lago TT, Leier A, Revote J, Zhu Y, Powell DR, Akutsu T, Webb GI, Chou KC, Smith AI, Daly RJ, Li J, Song J. “iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modelling of DNA, RNA and protein sequence data”. Briefings in Bioinformatics. 2020, 21(3), 1047-1057. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).

10. Li M, Wang Y, Li F, Zhao Y, Liu M, Zhang S, Bin Y, Smith AI, Webb GI, Li J, Song J, Xia J. “A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction”. IEEE/ACM transactions on computational biology and bioinformatics. 2020, doi:10.1109/TCBB.2020.3017386. (IF=3.71, 中科院大类三区(小类二区), JCR Q1, CCF C类).

11. Chen Z, Zhao P, Li F, Leier A, Marquez-Lago TT, Webb IG, Baggag A, Bensmail H, Song J. “PROSPECT: a web server for predicting protein histidine phosphorylation sites”. Journal of Bioinformatics and Computational Biology. 2020, 18(4), 2050018. (IF=1.122, JCR Q3).

12. Wei L, Hu J, Li F, Song J, Su R, Zou Q. “Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms”. Briefings in Bioinformatics. 2020, 21(1), 106-119. (IF=13.994, 中科院大类一区, Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).




2019年:

1. Li F, Wang Y, Li C, Marquez-Lago TT, Leier A, Rawlings ND, Haffari G, Revote J, Akutsu T, Chou KC, Purcell AW, Pike RN, Webb GI, Smith AI, Lithgow T, Daly RJ, Whisstock JC, Song J. “Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods”. Briefings in Bioinformatics. 2019, 20(6), 2150-2166. (IF=11.622, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

2. Zhang M†, Li F†, Marquez-Lago TT, Leier A, Fan C, Chou KC, Song J, Jia C. “MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters”. Bioinformatics. 2019, 35(17), 2957-2965. (IF=6.937, 中科院大类二区, Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).

3. Li F, Zhang Y, Purcell AW, Webb GI, Chou KC, Lithgow T, Li C, Song J. “Positive-unlabelled learning of glycosylation sites in the human proteome”. BMC Bioinformatics. 2019, 20, 112. (IF=3.169, 中科院大类三区(小类二区),  JCR Q1, CCF C类).

4. Ma X, Zhang L, Song J, Nguyen E, Lee SR, Rodgers SJ, Li F, Huang C, Schittenhelm RB, Chan H, Chheang C, Wu J, Brown KK, Mitchell CA, Simpson KJ, Daly RJ. “Characterization of the Src-regulated kinome identifies SGK1 as a key mediator of Src-induced transformation”. Nature Communications. 2019, 10, 296. (IF=14.919, 中科院大类一区, JCR Q1).

5. Wang X, Li C, Li F, Sharma VS, Song J, Webb GI. “SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in human proteome based on multi-stage ensemble-learning models”. BMC Bioinformatics. 2019, 20(1), 602. (IF=3.169, 中科院大类三区(小类二区), JCR Q1, CCF C类).

6. Chen Z, Liu X, Li F, Li C, Marquez-Lago TT, Leier A, Akutsu T, Webb GI, Xu D, Smith AI, Li L, Chou KC, Song J. “Large-scale comparative assessment of computational predictors for lysine post-translational modification sites”. Briefings in Bioinformatics. 2019, 20(6), 2267-2290. (IF=11.622, 中科院大类一区, Top期刊, JCR Q1, CCF B类).

7. Dunstan R, Pickard D, Dougan S, Goulding D, Cormie C, Hardy J, Li F, Grinter R, Harcourt K, Yu L, Song J, Schreiber F, Choudhary J, Clare S, Coulibaly F, Strugnell RA, Dougan G, Lithgow T. “The flagellotropic bacteriophage YSD1 targets Salmonella Typhi with a Chi-like protein tail-fibre”. Molecular Microbiology. 2019, 112(6), 1831-1846. (IF=3.816, 中科院大类二区, JCR Q1).

8. Song J, Wang Y, Li F, Akutsu T, Rawlings ND, Webb GI, Chou KC. “iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites”. Briefings in Bioinformatics. 2018, 20(2), 638-658. (IF=11.622, 中科院大类一区, Top期刊, JCR Q1, CCF B类) (Clarivate热点论文和高被引论文).



2018年以前:

1. Li F, Li C, Marquez-Lago TT, Leier A, Akutsu T, Purcell AW, Smith AI, Lithgow T, Daly RJ, Song J, Chou KC. “Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome”. Bioinformatics. 2018, 34(24), 4223-4231. (IF=6.937, 中科院大类二区(小类一区), Top期刊, JCR Q1, CCF B类).

2. Li F, Li C, Wang M, Webb GI, Zhang Y, Whisstock JC, Song J. “GlycoMine: a machine learning-based approach for predicting N-, C-, and O-linked glycosylation in the human proteome”. Bioinformatics. 2015, 31(9), 1411-1419. (IF=6.937, 中科院大类二区(小类一区), Top期刊, JCR Q1, CCF B类).

3. Li F, Li C, Revote J, Zhang Y, Webb GI, Li J, Song J, Lithgow T. “GlycoMinestruct: a new bioinformatics tool for highly accurate mapping of the human N-linked and O-linked glycoproteomes by incorporating structural features”. Scientific reports. 2016, 6, 34595. (IF=4.379, 中科院大类三区, JCR Q1).

4. Song J†, Li F†, Leier A, Marquez-Lago TT, Akutsu T, Haffari G, Chou KC, Webb GI, Pike RN. “PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy”. Bioinformatics. 2017, 34(4), 684-687. (IF=6.937, 中科院大类二区(小类一区), Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).

5. Li F, Song J, Li C, Akutsu T, Zhang Y. “PAnDE: Averaged n-Dependence Estimators for Positive unlabeled learning”. ICIC express letters. Part B, Applications. 2017, 8(9), 1287-1297. (EI, 6次引用).

6. Song J, Li F, Takemoto K, Haffari G, Akutsu T, Chou KC, Webb GI. “PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework”. Journal of Theoretical Biology. 2018, 443, 125-137. (IF=1.833, 中科院大类三区, JCR Q1) (Clarivate热点论文和高被引论文).

7. Chen Z, Zhao P, Li F, Leier A, Marquez-Lago TT, Wang Y, Webb GI, Smith AI, Daly RJ, Chou KC, Song J. “iFeature: a python package and web server for features extraction and selection from protein and peptide sequences”. Bioinformatics. 2018, 31(14), 2499-2502. (IF=6.937, 中科院大类二区(小类一区), Top期刊, JCR Q1, CCF B类) (Clarivate高被引论文).


课题组成员

博士生:

Yue Bi (博士一年级),Monash University,合作指导

Xiaoyu Wang (博士一年级),Monash University,合作指导


硕士生:

Ruyi Chen (硕士二年级),The University of Melbourne,主导师


已毕业硕士生:

张萌(协助大连海事大学贾藏芝教授指导,现于南京航空航天大学攻读博士学位)

朱燕(协助大连海事大学贾藏芝教授指导,现于哈尔滨工业大学攻读博士学位)

Xiaolan Tan(与澳大利亚格里菲斯大学潘世瑞教授共同指导,现于Monash大学攻读博士学位)

向东旭(2020届信息工程学院毕业生,邀请赴Monash访问学习一年,现于墨尔本大学攻读硕士学位)


其他主页

Google Scholar: https://scholar.google.com.au/citations?user=vrADwVUAAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Fuyi-Li


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