I am an Associate Professor in Bioinformatics at the Nottingham School of Veterinary Medicine and Science (since June, 2016). Previously, I was a research fellow at the Imperial College London (2011 - 2016). My research themes include the development of novel bioinformatics and machine learning solutions to understand and diagnose infectious diseases in humans and animals. I obtained my Ph.D. degree in Structural Biology and Bioinformatics from the University of Rome Tor Vergata.
My current interests are in the development of original methods and algorithms to gain deeper insight in biological problems related to human and animal health. To this purpose in my research I try to merge different disciplines and knowledge/skills, including bioinformatics and machine learning to develop predictive models and solve data mining tasks, in particular in scenarios involving large-scale data analysis from omics technologies (genomics, transcriptomics, proteomics, etc). My research themes include the development of novel solutions to understand and diagnose infectious diseases. I am particularly interested in the study of insurgence and propagation of antimicrobial resistance in humans and animals, at the molecular and population level.
PENG, Z., MACIEL-GUERRA, A., BAKER, M., ZHANG, X., HU, Y., WANG, W., RONG, J., ZHANG, J., XUE, N., BARROW, P., RENNEY, D., STEKEL, D., WILLIAMS, P., LIU, L., CHEN, J., LI, F. and DOTTORINI, T., 2022. Whole genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming: PLoS Comput Biol PLoS Comput Biol. 18(3), e1010018 WANG, W., HU, Y., BAKER, M., DOTTORINI, T., LI, H., DONG, Y., BAI, Y., FANNING, S. and LI, F., 2022. Novel SCCmec type XV (7A) and two pseudo-SCCmec variants in foodborne MRSA in China: J Antimicrob Chemother J Antimicrob Chemother. PEARCY, N., HU, Y., BAKER, M., MACIEL-GUERRA, A., XUE, N., WANG, W., KALER, J., PENG, Z., LI, F. and DOTTORINI, T., 2021. Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in Escherichia coli and Unravel the Underlying Metabolic Adaptation Mechanisms: mSystems mSystems. e0091320
MACIEL-GUERRA, A., ESENER, N., GIEBEL, K., LEA, D., GREEN, M. J., BRADLEY, A. J. and DOTTORINI, T., 2021. Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning: Sci Rep Sci Rep. 11(1), 7736
2021-2023 Towards Net Zero Dairy Farming through AI and Machine Vision (DAIRYVISION), Principal Investigator (PI), Funded by InnovateUK and Chinese Ministry of Science and Technology. Partners (China): NERCITA - Beijing Research Centre for Information Technology in Agriculture; HAMEI - Heilongjiang Agricultural Machinery Engineering Institute; CAU - China Agricultural University; TAH - Tianjin Jialihe Animal Husbandry Group Co. Ltd.; HDB - Harbin Wandashan Dairy Breeding Co. Ltd. Partners (UK): Peacock Technology Ltd, Harper Adams University
2020-2021 Fighting Covid-19 in Bangladeshi and Rohingya populations with endemic bacterial diarrhoea and antimicrobial resistance, Principal Investigator (PI), Funded by Research England and GCRF. Partners: North South University, IEDCR, UNICEF, ideSHi, University co Cambridge, University of Maryland (USA).
2019 - 2023 FARMWATCH: Fight AbR with Machine learning and a Wide Array of sensing TeCHnologies, Principal Investigator (PI), Funded by InnovateUK and Chinese Ministry of Science and Technology. UK partners: Nimrod Veterinary Products Ltd; Chinese partners: Key Laboratory of Food Safety Risk Assessment of Ministry of Health, China National Center for Food Safety Risk Assessment, New Hope Liuhe Limited Company, Dongwa Software Company)
2019-2020 CARE Bangladesh: Cholera Antibiotic REsistance in Bangladesh: big data mining and machine learning to improve diagnostics and treatment selection. Principal Investigator (PI), Funded by GCRF. Partners: North South University, Icddr,b UNICEF, BCSIR, University of Maryland (USA)
2018- 2020 Reducing, Refining and Monitoring the Impact of Antibiotic Use in the Control of Bovine Mastitis. Co-Investigator (Co-I). Funded by Innovate UK. Partners: QMMS
2017-2020 Y-Ware. "Young-stock Welfare & Performance - Decision Making Platform". Co-investigator (Co-I), Funded by Innovate UK. Partners: PrognostiX
2011-2015 EU-FP7-PEOPLE-IEF Senior Fellowship - VECTRAP. "Sex determination pathway in the malaria vector Anopheles gambiae". PI.
Current opportunities in my group: