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Personal profile


Jiangning is an Associate Professor (effective from 1 Jan 2019) and Group Leader in the Cancer and Infection and Immunity Programs in the Monash Biomedicine Discovery Institute (BDI), and Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia. He received his Ph.D. degree in Computer Science from Monash University, supervised by Prof Geoffrey Webb, Director of the Monash Centre for Data Science and Artificial Intelligence, and co-supervised by Dr Reza Haffari, at the Faculty of Information Technology, Monash University. Trained as a bioinformatician and data-savvy scientist, he has a very strong specialty in Artificial Intelligence, Bioinformatics, Comparative Genomics, Cancer Genomics, Bacterial Genomics, Computational Biomedicine, Data Mining, Infection and Immunity, Machine Learning, Proteomics, and Biomedical Big Data Analytics, which are highly sought-after expertise and skill sets in the data-driven, paradigm-shifting biomedical research. Ranked as one of the top-performing young Australian bioinformaticians, he was awarded a four-year NHMRC Peter Doherty Biomedical Fellowship (2008-2012) with his supervisor ARC Federation Fellow and ARC Australian Laureate Fellow Prof James Whisstock, Director of the ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, and Scientific Head of EMBL Australia.


He is Head of the Bioinformatics and Computational Biomedicine Laboratory at the Biomedicine Discovery Institute (BDI) and also an Associate Investigator of the ARC Centre of Excellence in Advanced Molecular Imaging at Monash University. He is also a member of the Monash Centre for Data Science and the Monash Bioinformatics Platform. His main research interests are bioinformatics, heterogeneous data modelling, machine learning, and data analytics in the areas of infection and immunity, and cancer biology. Jiangning is currently an Academic Editor of BMC Bioinformatics (one of the three top-tier specialist journals in Bioinformatics) and Protein & Peptide Letters, an Advisory Board Member of Current Protein & Peptide Science, and a Guest Editor of Current Bioinformatics, BioMed Res International and Frontiers in Genetics.


Jiangning is a recipient of the prestigious NHMRC Peter Doherty Fellowship (undertaken at Monash University) and both JSPS Long-term and Short-term Fellowships (undertaken at Kyoto University). He is a Program Committee (PC) member for more than 20 international conferences on Bioinformatics, Computational Biology, and Systems Biology, including BIBM, IEEE e-Science, InCoB, ISB, ICPB, ICIC, IIBM, and GIW. He is an invited reviewer for >60 journals (on average 80-100 reviews per year) in bioinformatics, computational biology, machine learning, data mining, systems biology, and chemoinformatics, including top-tier journals Briefings in BioinformaticsBioinformaticsNucleic Acids ResPLoS Comput Biol, J Theor Biol, Pattern Recog, Neurocomputing, Mol Cell ProteomicsBMC Bioinformatics, IEEE/ACM Trans Comput Biol and Bioinform, J Comput Chem, J Chem Info Model, and BMC Syst Biol.


He has published a career total of around 170 scientific articles, 7 reviews, 4 editorials, and 4 book chapters in the field of bioinformatics and computational biology. Remarkably, he is one of the very few Australian bioinformaticians that have published more than 20 research papers to date in both top-tier journals Briefings in Bioinformatics and Bioinformatics (13 and 14 papers, respectively in each journal). His publications have received a total of 2370 citations with an H-index of 27 and i10-index of 62 (Google Scholar) as of 04/12/2018.  Since 2007, he has been awarded 30 grants ($11.0M, 20 as CIA/CIB) by the US NIH, Australian NHMRC/ARC, and other granting bodies (e.g. the Japan Society for the Promotion of Science [JSPS], the Ministry of Science and Technology of  China [MOST], the Chinese Academy of Sciences [CAS] and the National Natural Science Foundation of China [NSFC], Monash University, and Kyoto University). In particular, in 2014, he secured a major five-year NIH R01 project (CIB, AI111965, US$4.56 million) with the program lead, NHMRC Principal Research Fellow Professor Jian Li at Monash University and other US collaborators to develop cutting-edge systems pharmacology approaches for predicting and validating antibiotic/small-molecule non-antibiotic combinations for new targeted therapies for treating life-threatening infections caused by antibiotic-resistant bacterial 'superbugs'. His recent work with Prof Tatsuya Akutsu at Kyoto University on developing novel bioinformatic algorithms for identifying substrates of apoptotic caspases has been recognized and awarded a Collaborative Research grant by Kyoto University Japan.


Jiangning is motivated to investigate, develop and deploy cutting-edge bioinformatics methodologies to better understand and address a range of open and challenging problems in genomics, molecular biology, and systems biology. To date, he and his team members have developed 60+ bioinformatics toolkits/webservers/software to serve the wider research community, including CISPEP, Disulfide, Cascleave, Cascleave 2.0, APIS, PRORATE, Pred-PFR, Prodepth, PROSPER, SSPKA, hCKSAAP_UbSite, PredPPCrys, Crysalis, Crysf, DephosSite, Periscope, GlycoMine, GlycoMinestruct, SecretEPDB, ProtVecDMPROSPERous, Bastion4, Bastion6, Bastion3, PhosphoPredict, PhosContext2Vec, POSSUM, iFeature, iProt-SubQuokka, Kmal-sp, SIMLIN, Muscadel, RNATargetsite, iLearn, Deep-S2D, and DeepCleave. Many of these tools have been highlighted as useful bioinformatic tools and have been widely used by the international research community.


For instance, PROSPER (https://prosper.erc.monash.edu/, a bioinformatic tool for predicting target substrates and their specific cleavage sites for 23 proteases, delivered as a representative outcome of the support of the NHMRC Program Grant on Protease Systems Biology headed by Prof James Whisstock at Monash University), has attracted more than 30,000 unique users worldwide and processed >80,000 job submissions since its inception in the end of 2012. The PROSPER paper has been highlighted as among the top 10% most cited PLoS ONE articles in 2017 (being cited 118 times to date). This tool, together with Cascleave (http://sunflower.kuicr.kyoto-u.ac.jp/sjn/Cascleave/ (being cited 116 times to date), a bioinformatic tool for predicting substrates of cell apoptosis caspases, enzymes that play essential roles in programmed cell death and inflammation), has been highlighted as two powerful bioinformatic tools by the International Proteolysis Society (IPS). An ultrafast and high-throughput tool PROSPERous (published in Feb 2018, cited 29 times to date) has been recently published in Bioinformatics for predicting the target substrates and cleavage sites for 90 different proteases and can be freely accessible at http://prosperous.erc.monash.edu/. The high impact of these tools signifies how biomedical knowledge discovery can indeed be alternatively catalyzed by data-driven computational techniques.


A career is a journey. Over the past 13 years since 2005, Jiangning has received substantial training in three world-leading universities - The University of Queensland, Kyoto University and Monash University, in the cutting-edge, cross-disciplinary bioinformatics, computational biomedicine, high-performance computing, mathematical modelling, machine learning and biomedical big data analytics. Some of the challenges encountered are part of his fast-paced, continuous learning curve, as a function of an incomplete knowledge in the new Era of 'Data Science and Analytics'.  Jiangning is always on the road to search for new knowledge, just like Monash University's motto quotes - "Ancora Imparo" ("I am still learning").  He is seen as a 'rare bird' as he has been extremely fortunate to work with and have three ARC Australian Federation/Laureate Fellows Prof Kevin Burrage (The University of Queensland & University of Oxford, now at Queensland University of Technology), Prof James Whisstock (Monash) and Prof Trevor Lithgow (FAA, Monash), Prof Tatsuya Akutsu (Kyoto University, Japan), IEEE Fellow Prof Geoffrey Webb (Monash), Prof Jian Li (NHMRC PRF, Monash), Prof Roger Daly (NHMRC PRF, Monash) and Prof Ian Smith (Vice-Provost of Monash University, Research and Research Infrastructure) as his collaborators and supervisors  throughout his academic career. Down the track along the journey, he has received substantial training in fermentation engineering, applied microbiology, protein engineering, applied mathematics, high-performance computing, computer science, statistics, bioinformatics, algorithms, structural biology, machine learning, data mining and integrative systems biology. Such a rare but critical 'blend' of caliber, expertise and skill sets places him in a privileged position to tackle and address inter-disciplinary research projects in the context of large-scale heterogeneous biomedical data analysis and modeling in the new era of Data Science and Analytics.


In his spare time, Jiangning enjoys his family time with his two adorable daughters Evelyn and Eleanor, watching movies, listening to music, and indulging himself in meandering the villages and discovering the heart of the beautiful Dandenong Ranges and Mornington Peninsula.


If you are interested in his research, you might want to read the following Monash BDI featured stories that report on his team's recent bioinformatics research:





If you would like to find out more about his research or inquire about potential collaboration opportunities, please contact Jiangning.Song@monash.edu.  Prospective postgraduate students in Australia or overseas who wish to pursue a Ph.D. career path with Jiangning at Monash University are also welcome to contact.


  • Artificial intelligence
  • Bioinformatics
  • Computer science
  • Computational biomedicine
  • Computational biology
  • Machine learning
  • Data Mining
  • Big Data Analytics
  • From Genotype to Phenotype
  • Infectious Diseases
  • Cancer
  • Functional genomics
  • Sequence analysis
  • Feature engineering
  • Multimodal data
  • Protein post-translational modification
  • Pattern recognition
  • Structural biology
  • Antimicrobial resistance
  • Antibiotic resistance
  • Data-driven knowledge discovery
  • Bioinformatics software
  • Multi-variable data modeling
  • Heterogeneous data analysis
  • Computational pipeline
  • Host-pathogen interaction
  • High-throughput screening

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2007 2023

Research Output 2004 2018

ACPred-FL: A sequence-based predictor based on effective feature representation to improve the prediction of anti-cancer peptides

Wei, L., Zhou, C., Chen, H., Song, J. & Su, R., 1 Jun 2018, (Accepted/In press) In : Bioinformatics. 9 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access

A subset of HLA-I peptides are not genomically templated: Evidence for cis- and trans-spliced peptide ligands

Faridi, P., Li, C., Ramarathinam, S. H., Vivian, J. P., Illing, P. T., Mifsud, N. A., Ayala, R., Song, J., Gearing, L. J., Hertzog, P. J., Ternette, N., Rossjohn, J., Croft, N. P. & Purcell, A. W., 12 Oct 2018, In : Science Immunology. 3, 28, 12 p., eaar3947.

Research output: Contribution to journalArticleResearchpeer-review

Bastion3: A two-layer ensemble predictor of type III secreted effectors

Wang, J., Li, J., Yang, B., Xie, R., Marquez-Lago, T. T., Leier, A., Hayashida, M., Akutsu, T., Zhang, Y., Chou, K-C., Selkrig, J., Zhou, T., Song, J. & Lithgow, T., 2 Nov 2018, (Accepted/In press) In : Bioinformatics. 9 p., bty914.

Research output: Contribution to journalArticleResearchpeer-review

Bastion6: A bioinformatics approach for accurate prediction of type VI secreted effectors

Wang, J., Yang, B., Leier, A., Marquez-Lago, T., Hayashida, M., Rocker, A., Zhang, Y., Akutsu, T., Chou, K-C., Strugnell, R. A., Song, J. & Lithgow, T., 1 Jan 2018, In : Bioinformatics. 34, 15, p. 2546-2555 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Characteristic and mechanism of immobilization effect of Staphylococcus aureus on human spermatozoa

Li, J., Li, B., Song, J., Liu, H., Bi, W., Dong, G. & Zhou, T., 1 Jun 2018, In : Microbial Pathogenesis. 119, p. 28-34 7 p.

Research output: Contribution to journalArticleResearchpeer-review