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Mirko Torrisi
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Deep learning methods in protein structure prediction
M Torrisi, G Pollastri, Q Le
Computational and Structural Biotechnology Journal 18, 1301-1310, 2020
2522020
Deeper profiles and cascaded recurrent and convolutional neural networks for state-of-the-art protein secondary structure prediction
M Torrisi, M Kaleel, G Pollastri
Scientific reports 9 (1), 12374, 2019
792019
Porter 5: state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes
M Torrisi, M Kaleel, G Pollastri
BioRxiv, 289033, 2018
46*2018
PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning
M Kaleel, M Torrisi, C Mooney, G Pollastri
Amino acids 51, 1289-1296, 2019
282019
Protein structure annotations
M Torrisi, G Pollastri
Essentials of Bioinformatics, Volume I: Understanding Bioinformatics: Genes …, 2019
11*2019
Protein profiles: Biases and protocols
G Urban, M Torrisi, CN Magnan, G Pollastri, P Baldi
Computational and structural biotechnology journal 18, 2281-2289, 2020
102020
Brewery: deep learning and deeper profiles for the prediction of 1D protein structure annotations
M Torrisi, G Pollastri
Bioinformatics 36 (12), 3897-3898, 2020
7*2020
Improving the assessment of deep learning models in the context of drug-target interaction prediction
M Torrisi, AV de León, G Climent, R Loos, A Panjkovich
ICLR2022 Machine Learning for Drug Discovery, 2022
12022
Do chemical language models provide a better compound representation?
M Torrisi, S Asadollahi, A de la Vega de León, K Wang, W Copeland
bioRxiv, 2023.11. 07.566025, 2023
2023
Drug representation and scrambling experiments highlight issues with training and evaluation of drug-target interaction predictive models
de la Vega de Leon Antonio, M Torrisi, A Panjkovich
American Chemical Society SciMeetings 3 (2), 2022
2022
Predicting Protein Structural Annotations by Deep and Shallow Learning
M Torrisi
University College Dublin. School of Computer Science, 2020
2020
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Articles 1–11