Oghenejokpeme I. Orhobor

According to our database, Oghenejokpeme I. Orhobor authored at least 17 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture.

Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Gareth Griffiths, Larisa N. Soldatova, Ross D. King

CoRR, 2024

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

2023

Protein-ligand binding affinity prediction exploiting sequence constituent homology.

Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Hang Lou, Hao Ni, Ross D. King

Bioinform., August, 2023

Imbalanced regression using regressor-classifier ensembles.

Oghenejokpeme I. Orhobor, Nastasiya F. Grinberg, Larisa N. Soldatova, Ross D. King

Mach. Learn., April, 2023

Extension of Transformational Machine Learning: Classification Problems.

Adnan Mahmud, Oghenejokpeme I. Orhobor, Ross D. King

CoRR, 2023

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

2022

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

2021

Cross-validation is safe to use.

Ross D. King, Oghenejokpeme I. Orhobor, Charles C. Taylor

Nat. Mach. Intell., 2021

Parallel Constraint-Driven Inductive Logic Programming.

Andrew Cropper, Oghenejokpeme I. Orhobor, Cristian Dinu, Rolf Morel

CoRR, 2021

2020

Predicting rice phenotypes with meta and multi-target learning.

Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King

Mach. Learn., 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

Federated Ensemble Regression Using Classification.

Oghenejokpeme I. Orhobor, Larisa N. Soldatova, Ross D. King

Proceedings of the Discovery Science - 23rd International Conference, 2020

Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology.

Oghenejokpeme I. Orhobor, Joseph French, Larisa N. Soldatova, Ross D. King

Proceedings of the Discovery Science - 23rd International Conference, 2020

2019

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

Oghenejokpeme I. Orhobor

PhD thesis, 2019

2018

Transformative Machine Learning.

Iván Olier, Oghenejokpeme I. Orhobor, Joaquin Vanschoren, Ross D. King

CoRR, 2018

Large-Scale Assessment of Deep Relational Machines.

Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King

Proceedings of the Inductive Logic Programming - 28th International Conference, 2018

Predicting Rice Phenotypes with Meta-learning.

Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King

Proceedings of the Discovery Science - 21st International Conference, 2018