3 citations · 4 across the 6 of their papers we have counts for
7 papers
Iterative AI-guided optimisation of selective triple-drug combinations for breast cancer
Oghenejokpeme Orhobor, Abbi Abdel-Rehim, Emma Tate +5
Personalised cancer therapy aims to tailor treatment to individual tumour profiles, yet tumour heterogeneity and adaptive resistance continue to limit clinical efficacy. Drug combi…
Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture
Abbi Abdel-Rehim, Oghenejokpeme Orhobor, Gareth Griffiths +2
The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for patients with tumours presenting…
Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment
Abbi Abdel-Rehim, Hector Zenil, Oghenejokpeme Orhobor +8
Large language models LLMs have transformed AI and achieved breakthrough performance on a wide range of tasks In science the most interesting application of LLMs is for hypothesis…
Extension of Transformational Machine Learning: Classification Problems
Adnan Mahmud, Oghenejokpeme Orhobor, Ross D. King
This study explores the application and performance of Transformational Machine Learning (TML) in drug discovery. TML, a meta learning algorithm, excels in exploiting common attrib…
Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction
Abbi Abdel-Rehim, Oghenejokpeme Orhobor, Hang Lou +2
The goal of Protein Structure Prediction (PSP) problem is to predict a protein's 3D structure (confirmation) from its amino acid sequence. The problem has been a 'holy grail' of sc…
Parallel Constraint-Driven Inductive Logic Programming
Andrew Cropper, Oghenejokpeme Orhobor, Cristian Dinu +1
Multi-core machines are ubiquitous. However, most inductive logic programming (ILP) approaches use only a single core, which severely limits their scalability. To address this limi…