Zobrazeno 1 - 10
of 135
pro vyhledávání: '"Wojtek, Michalowski"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-21 (2024)
Abstract Background Decision thresholds play important role in medical decision-making. Individual decision-making differences may be attributable to differences in subjective judgments or cognitive processes that are captured through the decision th
Externí odkaz:
https://doaj.org/article/4dccba8cdfc14c45b9d3270a8247593e
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1641-1653 (2024)
Protein generation has numerous applications in designing therapeutic antibodies and creating new drugs. Still, it is a demanding task due to the inherent complexities of protein structures and the limitations of current generative models. Proteins p
Externí odkaz:
https://doaj.org/article/01c4b28fa2e14dcabbbda16e97deee68
Autor:
Eric Paquet, Farzan Soleymani, Gabriel St-Pierre-Lemieux, Herna Lydia Viktor, Wojtek Michalowski
Publikováno v:
Artificial Intelligence Chemistry, Vol 2, Iss 1, Pp 100030- (2024)
This paper presents a new approach for protein generation based on one-shot learning and hybrid quantum neural networks. Given a single protein complex, the system learns how to predict the remaining unknown properties, without resorting to autoregre
Externí odkaz:
https://doaj.org/article/e9a9ee4dbf884e63950b4412b349f053
Publikováno v:
IEEE Access, Vol 12, Pp 74539-74557 (2024)
Lifelong machine learning concerns the development of systems that continuously learn from diverse tasks, incorporating new knowledge without forgetting the knowledge they have previously acquired. Multi-label classification is a supervised learning
Externí odkaz:
https://doaj.org/article/6c6bc1acf26743bf9df5e2700f40311e
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 2, Pp 2067-2082 (2023)
Abstract The design of binder proteins for specific target proteins using deep learning is a challenging task that has a wide range of applications in both designing therapeutic antibodies and creating new drugs. Machine learning-based solutions, as
Externí odkaz:
https://doaj.org/article/3c5ac7bf6942443fa2e95ed628eb80fe
Autor:
Shahin Basiratzadeh, Ramtin Hakimjavadi, Natalie Baddour, Wojtek Michalowski, Herna Viktor, Eugene Wai, Alexandra Stratton, Stephen Kingwell, Jean-Marc Mac-Thiong, Eve C. Tsai, Zhi Wang, Philippe Phan
Publikováno v:
Frontiers in Neurology, Vol 14 (2023)
BackgroundConducting clinical trials for traumatic spinal cord injury (tSCI) presents challenges due to patient heterogeneity. Identifying clinically similar subgroups using patient demographics and baseline injury characteristics could lead to bette
Externí odkaz:
https://doaj.org/article/d16a1efa1e2c4e1fa8cb179e4b07593d
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 1324-1348 (2023)
Proteins mainly perform their functions by interacting with other proteins. Protein–protein interactions underpin various biological activities such as metabolic cycles, signal transduction, and immune response. However, due to the sheer number of
Externí odkaz:
https://doaj.org/article/686268db195147ce8e154664ebca585c
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 5316-5341 (2022)
Most proteins perform their biological function by interacting with themselves or other molecules. Thus, one may obtain biological insights into protein functions, disease prevalence, and therapy development by identifying protein–protein interacti
Externí odkaz:
https://doaj.org/article/2b09ef369da742df89c75ba1d18f5974
Publikováno v:
IEEE Access, Vol 10, Pp 90045-90055 (2022)
This work introduces novel approaches, based on geometrical deep learning, for predicting protein–protein interactions. A dataset containing both interacting and non-interacting proteins is selected from the Negatome Database. Interactions are pred
Externí odkaz:
https://doaj.org/article/339ca760f1014f05be3c335866866057
Autor:
Toros C. Canturk, Daniel Czikk, Eugene K. Wai, Philippe Phan, Alexandra Stratton, Wojtek Michalowski, Stephen Kingwell
Publikováno v:
North American Spine Society Journal, Vol 11, Iss , Pp 100142- (2022)
Background: Predictive analytics are being used increasingly in the field of spinal surgery with the development of models to predict post-surgical complications. Predictive models should be valid, generalizable, and clinically useful. The purpose of
Externí odkaz:
https://doaj.org/article/0fcc5dd862dc4876951906652261a902