World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
8866
World Ranking
6201
National Ranking
373

Overview

Natalio Krasnogor is affiliated with Newcastle University in the United Kingdom. Their research primarily focuses on Biochemistry, Genetics, and Molecular Biology, with a significant contribution to the subfields of Molecular Biology, Biomedical Engineering, Ecology, Artificial Intelligence, and Genetics.

The scientist's work covers several key topics within biological sciences and biotechnology:

  • Advanced biosensing and bioanalysis techniques
  • CRISPR and Genetic Engineering
  • Bacteriophages and microbial interactions
  • Microbial Metabolic Engineering and Bioproduction
  • RNA Interference and Gene Delivery
  • Gene Regulatory Network Analysis
  • Bacterial Genetics and Biotechnology

Natalio Krasnogor has contributed to numerous scientific articles, with recent publications highlighting a diversity of research interests. Notable papers include:

  • For the sake of the Bioeconomy: define what a Synthetic Biology Chassis is!, 2020, New Biotechnology
  • Linking Engineered Cells to Their Digital Twins: A Version Control System for Strain Engineering, 2020, ACS Synthetic Biology
  • Toward Full-Stack In Silico Synthetic Biology: Integrating Model Specification, Simulation, Verification, and Biological Compilation, 2021, ACS Synthetic Biology
  • Transcriptomic Responses to Coaggregation between Streptococcus gordonii and Streptococcus oralis, 2021, Applied and Environmental Microbiology
  • Cotranscriptional Folding of a Bio-orthogonal Fluorescent Scaffolded RNA Origami, 2020, ACS Synthetic Biology

The scientist frequently publishes in several academic venues, including:

  • ACS Synthetic Biology
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Communications
  • New Biotechnology
  • Applied and Environmental Microbiology

Collaboration plays a notable role in Natalio Krasnogor's research, with frequent co-authors including:

  • Emanuela Torelli
  • Víctor de Lorenzo
  • Ben Shirt-Ediss
  • Jonathan Tellechea-Luzardo
  • Silvia Adriana Navarro

Best Publications

  • A tutorial for competent memetic algorithms: model, taxonomy, and design issues

    N. Krasnogor;J. Smith

  • Real-coded memetic algorithms with crossover hill-climbing

    Manuel Lozano;Francisco Herrera;Natalio Krasnogor;Daniel Molina

  • EnrichNet: network-based gene set enrichment analysis

    Enrico Glaab;Anaïs Baudot;Natalio Krasnogor;Reinhard Schneider

  • Recent advances in memetic algorithms

    William E. Hart;N. Krasnogor;J. E. Smith

  • Studies on the theory and design space of memetic algorithms.

    Krasnogor N

  • Nature‐inspired cooperative strategies for optimization

    Unknown

  • Multimeme Algorithms for Protein Structure Prediction

    Natalio Krasnogor;B. P. Blackburne;Edmund K. Burke;J. D. Hirst

  • A Memetic Algorithm with self-adaptive local search: TSP as a case study

    Natalio Krasnogor;Jim Smith

  • Measuring the similarity of protein structures by means of the universal similarity metric

    N. Krasnogor;D. A. Pelta

  • Protein structure prediction with evolutionary algorithms

    Natalio Krasnogor;William E. Hart;Jim Smith;David A. Pelta

  • Memetic Evolutionary Algorithms

    W. E. Hart;N. Krasnogor;J. E. Smith

  • The imitation game—a computational chemical approach to recognizing life

    Leroy Cronin;Natalio Krasnogor;Benjamin G Davis;Cameron Alexander

  • Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data

    Enrico Glaab;Jaume Bacardit;Jonathan M. Garibaldi;Natalio Krasnogor

  • A Study on the use of self-generation'' in memetic algorithms

    Natalio Krasnogor;Steven Gustafson

  • ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

    Enrico Glaab;Jonathan M Garibaldi;Natalio Krasnogor

  • Emergence of profitable search strategies based on a simple inheritance mechanism

    Natalio Krasnogor;Jim Smith

  • Prediction of human population responses to toxic compounds by a collaborative competition.

    Federica Eduati;Lara M Mangravite;Tao Wang;Hao Tang

  • Improving the scalability of rule-based evolutionary learning

    Jaume Bacardit;Edmund K. Burke;Natalio Krasnogor

  • A study on the design issues of Memetic Algorithm

    Q.H. Nguyen;Y.S. Ong;N. Krasnogor

  • Advanced Population Diversity Measures in Genetic Programming

    Edmund K. Burke;Steven M. Gustafson;Graham Kendall;Natalio Krasnogor

  • TopoGSA: network topological gene set analysis

    Enrico Glaab;Anaïs Baudot;Natalio Krasnogor;Alfonso Valencia

  • Bacteria clustering by polymers induces the expression of quorum-sensing-controlled phenotypes

    Leong T. Lui;Xuan Xue;Cheng Sui;Alan Brown

Frequent Co-Authors

Jaume Bacardit
Jaume Bacardit Newcastle University
Jonathan M. Garibaldi
Jonathan M. Garibaldi University of Nottingham
Edmund K. Burke
Edmund K. Burke Bangor University
Cameron Alexander
Cameron Alexander University of Nottingham
Marcus Kaiser
Marcus Kaiser University of Nottingham
Gabriela Ochoa
Gabriela Ochoa University of Stirling
Miguel Cámara
Miguel Cámara University of Nottingham
Jacek Blazewicz
Jacek Blazewicz Poznań University of Technology
Majlinda Lako
Majlinda Lako Newcastle University
Shengxiang Yang
Shengxiang Yang De Montfort University

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