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Catherine Mooney

Showing results (21-30 of 68) with videos related to

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BMC Bioinformatics|June 16, 2007
Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure informationGianluca Pollastri, Alberto J M Martin, Catherine Mooney, et al.
Food Chemistry|June 18, 2013
Inhibition of dipeptidyl peptidase IV and xanthine oxidase by amino acids and dipeptidesAlice B Nongonierma, Catherine Mooney, Denis C Shields, et al.
Plos One|September 11, 2013
Predicting binding within disordered protein regions to structurally characterised peptide-binding domainsWaqasuddin Khan, Fergal Duffy, Gianluca Pollastri, et al.
IEEE Transactions on Bio-Medical Engineering|October 16, 2024
Classification System for Predicting Emergent Epilepsy Phenotype in the Intra-Amygdala Kainic Acid Mouse Model of EpilepsyMercy Edoho, Omar Mamad, David C Henshall, et al.
Journal of Personalized Medicine|September 23, 2022
Application of Artificial Intelligence Techniques to Predict Risk of Recurrence of Breast Cancer: A Systematic ReviewClaudia Mazo, Claudia Aura, Arman Rahman, et al.
Scientific Reports|June 11, 2021
Prediction of caregiver quality of life in amyotrophic lateral sclerosis using explainable machine learningAnna Markella Antoniadi, Miriam Galvin, Mark Heverin, et al.
BMJ Open|March 2, 2020
Prediction of caregiver burden in amyotrophic lateral sclerosis: a machine learning approach using random forests applied to a cohort studyAnna Markella Antoniadi, Miriam Galvin, Mark Heverin, et al.
Peptides|May 6, 2014
In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitorsAlice B Nongonierma, Catherine Mooney, Denis C Shields, et al.
Computer Methods and Programs in Biomedicine|February 27, 2026
A multimodal data-based model for breast cancer diagnosisHuina Wang, Lan Wei, Jianqiang Li, et al.
Scientific Reports|January 22, 2022
An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitusYuhan Du, Anthony R Rafferty, Fionnuala M McAuliffe, et al.
Pageof 7

Showing results (21-30 of 68) with videos related to

Sort By:
Pageof 7
BMC Bioinformatics|June 16, 2007
Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure informationGianluca Pollastri, Alberto J M Martin, Catherine Mooney, et al.
Food Chemistry|June 18, 2013
Inhibition of dipeptidyl peptidase IV and xanthine oxidase by amino acids and dipeptidesAlice B Nongonierma, Catherine Mooney, Denis C Shields, et al.
Plos One|September 11, 2013
Predicting binding within disordered protein regions to structurally characterised peptide-binding domainsWaqasuddin Khan, Fergal Duffy, Gianluca Pollastri, et al.
IEEE Transactions on Bio-Medical Engineering|October 16, 2024
Classification System for Predicting Emergent Epilepsy Phenotype in the Intra-Amygdala Kainic Acid Mouse Model of EpilepsyMercy Edoho, Omar Mamad, David C Henshall, et al.
Journal of Personalized Medicine|September 23, 2022
Application of Artificial Intelligence Techniques to Predict Risk of Recurrence of Breast Cancer: A Systematic ReviewClaudia Mazo, Claudia Aura, Arman Rahman, et al.
Scientific Reports|June 11, 2021
Prediction of caregiver quality of life in amyotrophic lateral sclerosis using explainable machine learningAnna Markella Antoniadi, Miriam Galvin, Mark Heverin, et al.
BMJ Open|March 2, 2020
Prediction of caregiver burden in amyotrophic lateral sclerosis: a machine learning approach using random forests applied to a cohort studyAnna Markella Antoniadi, Miriam Galvin, Mark Heverin, et al.
Peptides|May 6, 2014
In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitorsAlice B Nongonierma, Catherine Mooney, Denis C Shields, et al.
Computer Methods and Programs in Biomedicine|February 27, 2026
A multimodal data-based model for breast cancer diagnosisHuina Wang, Lan Wei, Jianqiang Li, et al.
Scientific Reports|January 22, 2022
An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitusYuhan Du, Anthony R Rafferty, Fionnuala M McAuliffe, et al.
Pageof 7