Search Results - "Orhobor, Oghenejokpeme"

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  1. 1

    An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat by Grinberg, Nastasiya F., Orhobor, Oghenejokpeme I., King, Ross D.

    Published in Machine learning (01-02-2020)
    “…In phenotype prediction the physical characteristics of an organism are predicted from knowledge of its genotype and environment. Such studies, often called…”
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    Journal Article
  2. 2

    Batched Bayesian Optimization for Drug Design in Noisy Environments by Bellamy, Hugo, Rehim, Abbi Abdel, Orhobor, Oghenejokpeme I., King, Ross

    “…The early stages of the drug design process involve identifying compounds with suitable bioactivities via noisy assays. As databases of possible drugs are…”
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    Journal Article
  3. 3

    Transformational machine learning: Learning how to learn from many related scientific problems by Olier, Ivan, Orhobor, Oghenejokpeme I., Dash, Tirtharaj, Davis, Andy M., Soldatova, Larisa N., Vanschoren, Joaquin, King, Ross D.

    “…Almost all machine learning (ML) is based on representing examples using intrinsic features. When there are multiple related ML problems (tasks), it is…”
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    Journal Article
  4. 4

    Imbalanced regression using regressor-classifier ensembles by Orhobor, Oghenejokpeme I., Grinberg, Nastasiya F., Soldatova, Larisa N., King, Ross D.

    Published in Machine learning (01-04-2023)
    “…We present an extension to the federated ensemble regression using classification algorithm, an ensemble learning algorithm for regression problems which…”
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    Journal Article
  5. 5

    Protein–ligand binding affinity prediction exploiting sequence constituent homology by Abdel-Rehim, Abbi, Orhobor, Oghenejokpeme, Hang, Lou, Ni, Hao, King, Ross D

    Published in Bioinformatics (Oxford, England) (01-08-2023)
    “…Abstract Motivation Molecular docking is a commonly used approach for estimating binding conformations and their resultant binding affinities. Machine learning…”
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    Journal Article
  6. 6

    Predicting rice phenotypes with meta and multi-target learning by Orhobor, Oghenejokpeme I., Alexandrov, Nickolai N., King, Ross D.

    Published in Machine learning (01-11-2020)
    “…The features in some machine learning datasets can naturally be divided into groups. This is the case with genomic data, where features can be grouped by…”
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    Journal Article
  7. 7
  8. 8

    A simple spatial extension to the extended connectivity interaction features for binding affinity prediction by Orhobor, Oghenejokpeme I, Rehim, Abbi Abdel, Lou, Hang, Ni, Hao, King, Ross D

    Published in Royal Society open science (01-05-2022)
    “…The representation of the protein-ligand complexes used in building machine learning models play an important role in the accuracy of binding affinity…”
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    Journal Article
  9. 9

    A General Framework for Building Accurate and Understandable Genomic Models: A Study in Rice (Oryza sativa) by Orhobor, Oghenejokpeme I

    Published 01-01-2019
    “…Rapid technological advances in genotyping and sequencing technologies are driving the generation of vast amounts of genomic data. These advancements present a…”
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    Dissertation
  10. 10

    Extension of Transformational Machine Learning: Classification Problems by Mahmud, Adnan, Orhobor, Oghenejokpeme, King, Ross D

    Published 07-08-2023
    “…This study explores the application and performance of Transformational Machine Learning (TML) in drug discovery. TML, a meta learning algorithm, excels in…”
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    Journal Article
  11. 11

    Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture by Abdel-Rehim, Abbi, Orhobor, Oghenejokpeme, Griffiths, Gareth, Soldatova, Larisa, King, Ross D

    Published 23-08-2024
    “…The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for patients…”
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    Journal Article
  12. 12

    Parallel Constraint-Driven Inductive Logic Programming by Cropper, Andrew, Orhobor, Oghenejokpeme, Dinu, Cristian, Morel, Rolf

    Published 15-09-2021
    “…Multi-core machines are ubiquitous. However, most inductive logic programming (ILP) approaches use only a single core, which severely limits their scalability…”
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    Journal Article
  13. 13

    Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction by Abdel-Rehim, Abbi, Orhobor, Oghenejokpeme, Lou, Hang, Ni, Hao, King, Ross D

    Published 18-01-2023
    “…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…”
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    Journal Article
  14. 14

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

    Published 20-05-2024
    “…Large language models (LLMs) have transformed AI and achieved breakthrough performance on a wide range of tasks that require human intelligence. In science,…”
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    Journal Article
  15. 15

    Transformative Machine Learning by Olier, Ivan, Orhobor, Oghenejokpeme I, Vanschoren, Joaquin, King, Ross D

    Published 08-11-2018
    “…The key to success in machine learning (ML) is the use of effective data representations. Traditionally, data representations were hand-crafted. Recently it…”
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    Journal Article