Ross D. King

Ross D. King

Chalmers tekniska högskola

H-index: 58

Europe-Sweden

About Ross D. King

Ross D. King, With an exceptional h-index of 58 and a recent h-index of 27 (since 2020), a distinguished researcher at Chalmers tekniska högskola, specializes in the field of Automation of Science, Drug Design, Artificial Intelligence, Machine Learning, Synthetic Biology.

His recent articles reflect a diverse array of research interests and contributions to the field:

Interpreting protein abundance in Saccharomyces cerevisiae through relational learning

A machine learning approach to predict gene expression levels based on stochastic simulation

AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting

Protein–ligand binding affinity prediction exploiting sequence constituent homology

Imbalanced regression using regressor-classifier ensembles

Robot scientists: From Adam to Eve to Genesis

The future of fundamental science led by generative closed-loop artificial intelligence

LGEM+: A First-Order Logic Framework for Automated Improvement of Metabolic Network Models Through Abduction

Ross D. King Information

University

Position

Professor of Machine Intelligence

Citations(all)

14344

Citations(since 2020)

3341

Cited By

12768

hIndex(all)

58

hIndex(since 2020)

27

i10Index(all)

124

i10Index(since 2020)

52

Email

University Profile Page

Chalmers tekniska högskola

Google Scholar

View Google Scholar Profile

Ross D. King Skills & Research Interests

Automation of Science

Drug Design

Artificial Intelligence

Machine Learning

Synthetic Biology

Top articles of Ross D. King

Title

Journal

Author(s)

Publication Date

Interpreting protein abundance in Saccharomyces cerevisiae through relational learning

Bioinformatics

Daniel Brunnsåker

Filip Kronström

Ievgeniia A Tiukova

Ross D King

2024/2/1

A machine learning approach to predict gene expression levels based on stochastic simulation

Ross King

2024/3/25

AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting

Journal of the American Society for Mass Spectrometry

Gabriel K Reder

Erik Y Bjurström

Daniel Brunnsåker

Filip Kronström

Praphapan Lasin

...

2024/2/4

Protein–ligand binding affinity prediction exploiting sequence constituent homology

Bioinformatics

Abbi Abdel-Rehim

Oghenejokpeme Orhobor

Lou Hang

Hao Ni

Ross D King

2023/8/1

Imbalanced regression using regressor-classifier ensembles

Machine Learning

Oghenejokpeme I Orhobor

Nastasiya F Grinberg

Larisa N Soldatova

Ross D King

2023/4

Robot scientists: From Adam to Eve to Genesis

Artificial Intelligence in Science Challenges, Opportunities and the Future of Research: Challenges, Opportunities and the Future of Research

Ross King

Oliver Peter

Patrick Courtney

2023/6/26

The future of fundamental science led by generative closed-loop artificial intelligence

arXiv preprint arXiv:2307.07522

Hector Zenil

Jesper Tegnér

Felipe S Abrahão

Alexander Lavin

Vipin Kumar

...

2023/7/9

LGEM+: A First-Order Logic Framework for Automated Improvement of Metabolic Network Models Through Abduction

Alexander H Gower

Konstantin Korovin

Daniel Brunnsåker

Ievgeniia A Tiukova

Ross D King

2023/10/8

Beating the best: improving on AlphaFold2 at protein structure prediction

arXiv preprint arXiv:2301.07568

Abbi Abdel-Rehim

Oghenejokpeme Orhobor

Hang Lou

Hao Ni

Ross D King

2023/1/18

Artificial intelligence in scientific discovery: Challenges and opportunities

Ross King

Hector Zenil

2023/6/26

Artificial Intelligence in Science: Robot scientists: From Adam to Eve to Genesis

Ross King

Oliver Peter

Patrick Courtney

2023/6/26

RIMBO-An Ontology for Model Revision Databases

Filip Kronström

Alexander H Gower

Ievgeniia A Tiukova

Ross D King

2023/10/8

An experimental target-based platform in yeast for screening Plasmodium vivax deoxyhypusine synthase inhibitors

AH Klippel

S Sigurdardottir

SJ Mahdizadeh

I Tiukova

C Bourgard

...

2023/11/24

LGEM: a first-order logic framework for automated improvement of metabolic network models through abduction

arXiv preprint arXiv:2306.06065

Alexander H Gower

Konstantin Korovin

Daniel Brunnsåker

Ievgeniia A Tiukova

Ross D King

2023/6/9

Artificial Intelligence in Science: Artificial intelligence in scientific discovery: Challenges and opportunities

Ross King

Hector Zenil

2023/6/26

Extrapolation is Not the Same as Interpolation

Yuxuan Wang

Ross D King

2023/10/8

Genesis-DB: a database for autonomous laboratory systems

Bioinformatics Advances

Gabriel K Reder

Alexander H Gower

Filip Kronström

Rushikesh Halle

Vinay Mahamuni

...

2023/1/1

Automated scientific discovery: from equation discovery to autonomous discovery systems

arXiv preprint arXiv:2305.02251

Stefan Kramer

Mattia Cerrato

Sašo Džeroski

Ross King

2023/5/3

Artificial Intelligence in Science: A framework for evaluating the AI-driven automation of science

Ross King

Hector Zenil

2023/6/26

Extension of Transformational Machine Learning: Classification Problems

arXiv preprint arXiv:2309.16693

Adnan Mahmud

Oghenejokpeme Orhobor

Ross D King

2023/8/7

See List of Professors in Ross D. King University(Chalmers tekniska högskola)

Co-Authors

H-index: 128
Douglas Kell

Douglas Kell

University of Liverpool

H-index: 119
Oliver Fiehn

Oliver Fiehn

University of California, Davis

H-index: 78
Stephen Muggleton

Stephen Muggleton

Imperial College London

H-index: 60
Hannu (TT) Toivonen

Hannu (TT) Toivonen

Helsingin yliopisto

H-index: 59
Pedro Mendes

Pedro Mendes

University of Connecticut

H-index: 52
Ivan Bratko

Ivan Bratko

Univerza v Ljubljani

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