Predicting Rice Phenotypes with Meta-learning. - Oghenejokpeme I. Orhobor; Nickolai N. Alexandrov; Ross D. King (DS, 2018)

Large-Scale Assessment of Deep Relational Machines. - Tirtharaj Dash; Ashwin Srinivasan 001; Lovekesh Vig; Oghenejokpeme I. Orhobor; Ross D. King (ILP, 2018)

Transformative Machine Learning. - Iván Olier; Oghenejokpeme I. Orhobor; Joaquin Vanschoren; Ross D. King (CoRR, 2018)

A general framework for building accurate and understandable genomic models: a study in rice (Oryza sativa). - Oghenejokpeme I. Orhobor (2019)

Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology. - Oghenejokpeme I. Orhobor; Joseph French; Larisa N. Soldatova; Ross D. King (DS, 2020)

Federated Ensemble Regression Using Classification. - Oghenejokpeme I. Orhobor; Larisa N. Soldatova; Ross D. King (DS, 2020)

An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat. - Nastasiya F. Grinberg; Oghenejokpeme I. Orhobor; Ross D. King (Mach. Learn., 2020)

Predicting rice phenotypes with meta and multi-target learning. - Oghenejokpeme I. Orhobor; Nickolai N. Alexandrov; Ross D. King (Mach. Learn., 2020)

Parallel Constraint-Driven Inductive Logic Programming. - Andrew Cropper; Oghenejokpeme I. Orhobor; Cristian Dinu; Rolf Morel (CoRR, 2021)

Cross-validation is safe to use. - Ross D. King; Oghenejokpeme I. Orhobor; Charles C. Taylor (Nat. Mach. Intell., 2021)

Batched Bayesian Optimization for Drug Design in Noisy Environments. - Hugo Bellamy; Abbi Abdel-Rehim; Oghenejokpeme I. Orhobor; Ross D. King (J. Chem. Inf. Model., 2022)

Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction. - Abbi Abdel-Rehim; Oghenejokpeme I. Orhobor; Hang Lou; Hao Ni; Ross D. King (CoRR, 2023)

Extension of Transformational Machine Learning: Classification Problems. - Adnan Mahmud; Oghenejokpeme I. Orhobor; Ross D. King (CoRR, 2023)

Imbalanced regression using regressor-classifier ensembles. - Oghenejokpeme I. Orhobor; Nastasiya F. Grinberg; Larisa N. Soldatova; Ross D. King (Mach. Learn., 2023)

Protein-ligand binding affinity prediction exploiting sequence constituent homology. - Abbi Abdel-Rehim; Oghenejokpeme I. Orhobor; Hang Lou; Hao Ni; Ross D. King (Bioinform., 2023)

Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment. - Abbi Abdel-Rehim; Hector Zenil; Oghenejokpeme I. Orhobor; Marie Fisher; Ross J. Collins; Elizabeth Bourne; Gareth W. Fearnley; Emma Tate; Holly X. Smith; Larisa N. Soldatova; Ross D. King (CoRR, 2024)

Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture. - Abbi Abdel-Rehim; Oghenejokpeme I. Orhobor; Gareth Griffiths 006; Larisa N. Soldatova; Ross D. King (CoRR, 2024)