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Carlos H. A. Higa
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2020 – today
- 2023
- [j2]Eloi Araujo, Fábio Viduani Martinez, Carlos H. A. Higa, José Soares:
Matrices inducing generalized metric on sequences. Discret. Appl. Math. 332: 135-154 (2023) - [i1]Eloi Araujo, Fábio Viduani Martinez, Carlos H. A. Higa, José Soares:
Matrices inducing generalized metric on sequences. CoRR abs/2303.08725 (2023)
2010 – 2019
- 2018
- [c7]Jean C. W. K. Ma, Marco Aurelio Stefanes, Carlos H. A. Higa, Luiz C. S. Rozante:
Inferring Gene Regulatory Networks Using Hybrid Parallel Computing. ICCSA (1) 2018: 151-166 - [c6]Mariana Caravanti de Souza, Carlos H. A. Higa:
Reverse Engineering of Gene Regulatory Networks Combining Dynamic Bayesian Networks and Prior Biological Knowledge. ICCSA (1) 2018: 323-336 - 2016
- [c5]Camila Y. Koike, Carlos H. A. Higa:
Inference of Gene Regulatory Networks Using Coefficient of Determination, Tsallis Entropy and Biological Prior Knowledge. BIBE 2016: 64-70 - 2015
- [c4]Alex Z. Zaccaron, Said Sadique Adi, Carlos H. A. Higa, Eloi Araujo, Burton H. Bluhm:
The Maximum Similarity Partitioning Problem and its Application in the Transcriptome Reconstruction and Quantification Problem. ICCSA (1) 2015: 257-266 - 2013
- [j1]Carlos H. A. Higa, Tales P. Andrade, Ronaldo Fumio Hashimoto:
Growing Seed Genes from Time Series Data and Thresholded Boolean Networks with Perturbation. IEEE ACM Trans. Comput. Biol. Bioinform. 10(1): 37-49 (2013) - 2012
- [b1]Carlos Henrique Aguena Higa:
Inference of gene regulatory networks using the seed growing paradigm. University of São Paulo, Brazil, 2012 - 2010
- [c3]Carlos H. A. Higa, Vitor H. P. Louzada, Ronaldo Fumio Hashimoto:
Analysis of Gene Interactions Using Restricted Boolean Networks and Time-Series Data. ISBRA 2010: 61-76
2000 – 2009
- 2009
- [c2]Ronaldo Fumio Hashimoto, Henrique Stagni, Carlos H. A. Higa:
Budding yeast cell cycle modeled by context-sensitive probabilistic Boolean network. GENSiPS 2009: 1-4 - [c1]Carlos H. A. Higa, Ronaldo Fumio Hashimoto, Roberto Hirata Jr., Nina S. T. Hirata, Carlos S. Santos:
Inference of gene regulatory network using temporal coefficient of determination obtained from ergodic Markov chains. GENSiPS 2009: 1-4
Coauthor Index
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