Current position: Working as a postdoctoral researcher in Heinrich Pette Institute, Hamburg, Germany.
Research Interests: Machine Learning, Cryo-EM, and Bioinformatics
Research: I developed Deep Learning techniques which I applied to several problems in the protein structural and functional space, including protein secondary structure, solvent accessibility and subcellular localisation prediction. Each of these problems is important, and webservers for predicting these properties process hundreds of thousands of queries from all over the world, helping advance research in molecular evolution, the study of protein-protein interaction networks, and computational drug design.
Education:
· 2020 – PhD School of Computer Science and Informatics, University College Dublin, Supervisor: Dr. Gianluca Pollastri and Dr. Catherine Mooney
· 2014 – BSc in Computer Science, University College Dublin
Publications:
“Porter 5: fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes”, bioRxiv, (2018) M. Torrisi, M. Kaleel, and G. Pollastri DOI: 10.1101/289033
“PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning”, Amino Acids, (2019). M. Kaleel, M. Torrisi, C. Mooney, and G. Pollastri DOI: 10.1007/s00726-019-02767-6
“Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction, Scientific Reports”, (2019) M. Torrisi, M. Kaleel, and G. Pollastri DOI: 10.1038/s41598-019-48786-x
“SCLpred-EMS: subcellular localization prediction of endomembrane system and secretory pathway proteins by Deep N-to-1 Convolutional Neural Networks”, Bioinformatics, (2020). M. Kaleel, G. Pollastri, and C. Mooney DOI:10.1093/bioinformatics/btaa156
“SCLpred-MEM: membrane protein subcellular localization prediction by Deep N-to-1 neural networks”, M.Kaleel, L.Liam, C.Lalor, G.Pollastri and C.Mooney
Posters in national and international conferences
“Brewery: state-of-the-art ab initio prediction of 1D protein structure annotations” M.Torrisi, M.Kaleel and G.Pollastri BITS2018, University of Turin, Italy, June 27-29, 2018
“DeepSCLpred: protein subcellular localization prediction by Deep N-to-1 neural networks” M. Kaleel, A. Khalid, T. Kumar, Z. Yandan, C. Jialiang, F. Xuanming, G. Pollastri and C. Mooney ECCB 2018, Athens, Greece, Sep 8-12, 2018
“DeepSCLpred: protein subcellular localization prediction by Deep N-to-1 neural networks” M. Kaleel, A. Khalid, T. Kumar, Z. Yandan, C. Jialiang, F. Xuanming, G. Pollastri and C. Mooney UCD Molecular And Computational Biology Symposium 2018, Dublin, Ireland, Nov 29-30, 2018
“Brewery: state-of-the-art ab initio prediction of 1D protein structure annotations” M.Torrisi, M.Kaleel and G.Pollastri Critical Assessment of Techniques for Protein Structure Prediction (CASP) 2018, Riviera Maya, Mexico, December 3, 2018
“Protein subcellular localization prediction by N-to-1 neural networks” M. Kaleel, A. Khalid, T. Kumar, Z. Yandan, C. Jialiang, F. Xuanming, G. Pollastri and C. Mooney UCD The Virtual Institute of Bioinformatics and Evolution (VIBE), Dublin, Ireland, Mar 22, 2019