Arlindo L. Oliveira links adjacent fields of study such as Heuristic and Minification in the subject of Mathematical optimization. His Mathematical optimization research extends to Heuristic, which is thematically connected. His Algorithm study frequently draws connections between adjacent fields such as Minimum description length, Binary decision diagram and Boolean function. His Minimum description length study frequently links to related topics such as Algorithm. Arlindo L. Oliveira combines topics linked to Discrete mathematics with his work on Boolean function. Borrowing concepts from Theoretical computer science, Arlindo L. Oliveira weaves in ideas under Discrete mathematics. His research ties Graph and Theoretical computer science together. His research on Graph often connects related areas such as Maximum cut. His study on Programming language is interrelated to topics such as Set (abstract data type), Binary decision diagram and Minification.
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Biclustering Algorithms for Biological Data Analysis: A Survey
Sara C. Madeira;Arlindo L. Oliveira.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2004)
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer.
arXiv: Computer Vision and Pattern Recognition (2018)
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer.
Unknown Journal (2018)
The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae
Miguel C. Teixeira;Pedro T. Monteiro;Pooja Jain;Sandra Tenreiro.
Nucleic Acids Research (2006)
Temporal Data Mining: an overview
Cláudia M. Antunes;Arlindo L. Oliveira.
(2001)
The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae
Miguel Cacho Teixeira;Pedro Tiago Monteiro;Joana Fernandes Guerreiro;Joana Pinho Gonçalves.
Nucleic Acids Research (2014)
YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface
Dário Abdulrehman;Pedro Tiago Monteiro;Miguel Cacho Teixeira;Nuno Pereira Mira.
Nucleic Acids Research (2011)
YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae
Pedro T. Monteiro;Nuno D. Mendes;Miguel C. Teixeira;Sofia d’Orey.
Nucleic Acids Research (2007)
Techniques for the creation of digital watermarks in sequential circuit designs
A.L. Oliveira.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2001)
Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm
Sara C. Madeira;Miguel C. Teixeira;Isabel Sa-Correia;Arlindo L. Oliveira.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2010)
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