H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology H-index 36 Citations 10,265 149 World Ranking 3188 National Ranking 141

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Gene
  • Machine learning

His primary scientific interests are in Memetic algorithm, Bioinformatics, Alzheimer's disease, Disease and Artificial intelligence. He performs integrative Memetic algorithm and Job shop scheduling research in his work. When carried out as part of a general Bioinformatics research project, his work on Biological data is frequently linked to work in Scalability, therefore connecting diverse disciplines of study.

His research on Alzheimer's disease also deals with topics like

  • Cognition together with Cognitive decline, Hippocampus, Recall and Gene expression profiling,
  • Biomarker that intertwine with fields like Metabolite, Metabolomics, Oncology and Area under the curve. His Disease research includes themes of Longitudinal study and Computational biology. His research integrates issues of Machine learning, Logistic regression and Fitness landscape in his study of Artificial intelligence.

His most cited work include:

  • New Ideas In Optimization (1303 citations)
  • On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms (1187 citations)
  • Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20 (440 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Memetic algorithm, Artificial intelligence, Bioinformatics, Data mining and Machine learning. His studies deal with areas such as Theoretical computer science and Metaheuristic as well as Memetic algorithm. His Artificial intelligence study frequently intersects with other fields, such as Pattern recognition.

His Bioinformatics research incorporates themes from Gene expression profiling, Biomarker, Internal medicine, Disease and Computational biology. His Disease study combines topics in areas such as Recall and Neuroscience. His work carried out in the field of Data mining brings together such families of science as Microarray analysis techniques, Quadratic assignment problem, Cluster analysis and Graph.

He most often published in these fields:

  • Memetic algorithm (29.52%)
  • Artificial intelligence (18.50%)
  • Bioinformatics (26.43%)

What were the highlights of his more recent work (between 2018-2021)?

  • Memetic algorithm (29.52%)
  • Analytics (3.52%)
  • Artificial intelligence (18.50%)

In recent papers he was focusing on the following fields of study:

Pablo Moscato spends much of his time researching Memetic algorithm, Analytics, Artificial intelligence, Data science and Cluster analysis. His study on Memetic algorithm is covered under Local search. He interconnects Tree and Problem domain in the investigation of issues within Local search.

As a part of the same scientific family, Pablo Moscato mostly works in the field of Analytics, focusing on Data analysis and, on occasion, Metaheuristic and Ensemble learning. His study in Metaheuristic is interdisciplinary in nature, drawing from both Predictive analytics, Feature selection and Curse of dimensionality. His Artificial intelligence study incorporates themes from Machine learning, Network alignment and Regression.

Between 2018 and 2021, his most popular works were:

  • An Accelerated Introduction to Memetic Algorithms (11 citations)
  • Memetic Algorithms for Business Analytics and Data Science: A Brief Survey. (6 citations)
  • M-Link: a link clustering memetic algorithm for overlapping community detection (5 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Gene
  • Machine learning

His scientific interests lie mostly in Memetic algorithm, Representation, Local search, Theoretical computer science and Data mining. His Memetic algorithm research is multidisciplinary, relying on both Partition and Cluster analysis. He combines subjects such as Label propagation, Mutual information, Complex system, Population structure and Community structure with his study of Cluster analysis.

His Representation study is concerned with the field of Artificial intelligence as a whole. The study incorporates disciplines such as Test, Data collection and Regression in addition to Artificial intelligence. Within one scientific family, Pablo Moscato focuses on topics pertaining to Problem domain under Local search, and may sometimes address concerns connected to Heuristics.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms

P. Moscato.
Caltech Concurrent Computation Program (1989)

2461 Citations

New ideas in optimization

David Corne;Marco Dorigo;Fred Glover;Dipankar Dasgupta.
(1999)

1280 Citations

Memetic algorithms: a short introduction

Pablo Moscato.
New ideas in optimization (1999)

779 Citations

A Gentle Introduction to Memetic Algorithms

Pablo Moscato;Carlos Cotta.
Handbook of Metaheuristics (2003)

578 Citations

Genome-wide analysis of long noncoding RNA stability

Michael B. Clark;Rebecca L. Johnston;Mario Inostroza-Ponta;Archa H. Fox.
Genome Research (2012)

466 Citations

Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20

Melanie Bahlo;David R Booth;Simon A Broadley;Matthew A Brown;Matthew A Brown.
Nature Genetics (2009)

456 Citations

On the Rank of Extreme Matrices in Semidefinite Programs and the Multiplicity of Optimal Eigenvalues

Pablo Moscato;Michael G. Norman;Gabor Pataki.
Mathematics of Operations Research (1998)

412 Citations

Handbook of Memetic Algorithms

Ferrante Neri;Carlos Cotta;Pablo Moscato.
Handbook of Memetic Algorithms (2011)

387 Citations

Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci

Nikolaos A. Patsopoulos;Federica Esposito;Joachim Reischl;Stephan Lehr.
Annals of Neurology (2011)

313 Citations

A memetic algorithm for the total tardiness single machine scheduling problem

Paulo M França;Alexandre Mendes;Pablo Moscato.
European Journal of Operational Research (2001)

249 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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