Prof. Andreas L. Lopata is a molecular immunologist and leads the Molecular Allergy Research Laboratory in Tropical Futures Institute at James Cook University-Singapore. His research team uses cutting-edge molecular approaches in characterizing the interactions of immunogenic proteins from different food sources with the human immune system. Prof Lopata is working with BII scientists on the molecular and immunological cross-reactivity of allergens and food safety implications of alternative food proteins.
Dr Jinmiao Chen is a Principal Investigator at Singapore Immunology Network (SIgN), A * STAR, Singapore, running a lab that spans both wet lab experiments and dry lab analyses. Her research interest is single-cell and spatial omics integrated with AI for precision immunology. Her dry lab specializes in AI algorithm and omics database development. She was identified as a Highly Cited Researcher in 2020, 2021, and 2022. She collaborates with BII on spatial omics analysis and biological data integration.
Principal Investigator IMCB, A*STAR, My long-term research interest is focused on the integration of the cell biology, immunology with quantitative mass spectrometry-based proteomics. It includes Multi-Omics approaches in precision medicine for personalized therapies, antigen identification pipelines development, body fluid biomarker discovery, clinical proteomics, mass spectrometry based diagnostics approaches, novel drug target deconvolution and chemical proteomics for patient- tailored therapies.
Dr Daniel Ting is the Associate Professor with Duke-NUS Medical School, senior consultant vitreo-retinal surgeon and Chief Data and Digital Officer of Singapore National Eye Center, Head of AI and Digital Innovation in the Singapore Eye Research Institute (SERI), Director of Singapore Health Service AI Office, and the innovation mentor at Byers Eye Institute, Stanford University. He was also the 2017/2018 USASEAN Fulbright Scholar visiting Johns Hopkins University to exchange expertise in AI and big data for medicine. To date, he has published >200 peer reviewed publications in high-impact journals, such as JAMA, NEJM, Lancet, Nature Medicine in areas related to machine learning, deep learning, privacy preserving technology such as blockchain technology, federated machine learning and generative adversarial network, satellite technology (4G and 5G), conversational AI chatbot using natural language processing and cybersecurity (e.g., adversarial attack) in health. He is the EXCO of American Academy of Ophthalmology AI committee, STARD-AI, QUADAS-AI and DECIDE-AI, International Agency for Prevention of Blindness (IAPB) technology taskforce. In 2021 and 2022, he was also ranked 1st for deep learning, and top 10 for AI and machine learning in the world across all domains (>55K researchers) for the past 10 years (2010-2021) by the ExpertScape.
Dr. Yang Zhang is a Professor in the Department of Computer Science, the School of Computing, National University of Singapore (NUS). He also serves as a Professor in the Cancer Science Institute of Singapore, and the Department of Biochemistry at the Yong Loo Lin School of Medicine, NUS. Prior to joining NUS, Dr. Zhang worked as a Professor in the Department of Computational Medicine & Bioinformatics, the Department of Biological Chemistry, and the Department of Macromolecular Science & Engineering, University of Michigan. The research interests of the Zhang Lab are in artificial intelligence and deep neural network learning, protein folding and structure prediction, and protein design and engineering. The I-TASSER algorithm (https://zhanggroup.org/I-TASSER/) developed in his laboratory was ranked as the No. 1 most accurate method for automated protein structure prediction in the community-wide CASP experiments nine times in a row since 2006. Among the honors that Dr. Zhang received include the Alfred P Sloan Award, the ASBMB DeLano Award, the US National Science Foundation Career Award, and the University of Michigan Basic Science Research Award. He was selected as the Thomson Reuters/Clarivate Analytics Highly Cited Researcher for six times since 2015.
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My research focus is on computer vision and biomedical image analysis. I have been fortunate to collaborate with our BII colleagues over the years, including the recent collaborative project with Dr. FAN Hao on AI-guided protein-ligand interaction prediction.
My group is focused on developing liquid biopsies for oral cancer screening and prognosis. We are currently assessing the utility of salivary exosomal miRNAs for predicting tumour aggressiveness and development of chemoresistance in Oral Squamous Cell Carcinoma. The group is particularly interested in unravelling the mechanism of action of candidate miRNAs like miR1307 in the development of chemoresistance. In addition, we are also assessing the utility of cell free DNA as biomolecules for liquid biopsies. My group also tries to understand the link between miRNA expression, cellular signalling and cell differentiation. We have used these approaches successfully in the past for studying differentiation of stem cells like mesenchymal stromal cells and embryonic stem cells as well as other systems like zebrafish, wound healing etc.
Prof. Dr. Gerhard Grüber’s research translates understanding of key enzymes of drug resistant microorganisms into identification of novel inhibitor targets for the design of new antimycobacterial lead compounds. He successfully collaborates with the BII, A*STAR members Dr. Peter J. Bond, and Dr. Alexander Krah on multiscale simulation and modeling of compound-bound mycobacterial F1FO ATP synthase.