De Beukelaer Herman

De Beukelaer Herman - Postdoctoral fellow @ Computational Regulomics

7. Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning

Helder Opdebeeck, Dajo Smet, Sander Thierens, Max Minne, Herman De Beukelaer, Jasper Zuallaert, Michiel Van Bel, Marc Van Montagu, Sven Degroeve, Bert De Rybel, Klaas Vandepoele

(2025) -

DOI
6. Modulating activity of the APC/C regulator SISAMBA improves the sugar and antioxidant content of tomato fruits

Perla Novais de Oliveira, Leonardo Perez de Souza, Pedro Boscariol Ferreira, Jean Phillippe Mauxion, Luis Felipe Correa da Silva, Ana Isabela Chang, Marina de Lyra Soriano Saleme, Sara Selma García, Herman De Beukelaer, Marina C. M. Martins, Lilian Ellen Pino, Norbert Bollier, Lázaro Eustáquio Pereira Peres, Klaas Vandepoele, Alain Goossens, Nathalie Gonzalez, Alisdair R. Fernie, Nubia Barbosa Eloy

(2024) -

DOI
5. Core Hunter 3: flexible core subset selection

Herman De Beukelaer, Guy F Davenport, Veerle Fack

(2018) - BMC Bioinformatics

DOI
4. JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

Herman De Beukelaer, Guy F. Davenport, Geert De Meyer, Veerle Fack

(2017) - Software: Practice and Experience

DOI
3. Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection

Herman De Beukelaer, Yvonne Badke, Veerle Fack, Geert De Meyer

(2017) - Genetics

DOI
2. Heuristic exploitation of genetic structure in marker-assisted gene pyramiding problems.

Beukelaer HD, Meyer GD, Fack V

(2015) -

DOI
1. Core Hunter II: fast core subset selection based on multiple genetic diversity measures using Mixed Replica search.

De Beukelaer H, Smýkal P, Davenport GF, Fack V

(2012) -

DOI

De Beukelaer Herman

Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning7. Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning

Modulating activity of the APC/C regulator SISAMBA improves the sugar and antioxidant content of tomato fruits6. Modulating activity of the APC/C regulator SISAMBA improves the sugar and antioxidant content of tomato fruits

Core Hunter 3: flexible core subset selection5. Core Hunter 3: flexible core subset selection

JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics4. JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection3. Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection

Heuristic exploitation of genetic structure in marker-assisted gene pyramiding problems.2. Heuristic exploitation of genetic structure in marker-assisted gene pyramiding problems.

Core Hunter II: fast core subset selection based on multiple genetic diversity measures using Mixed Replica search.1. Core Hunter II: fast core subset selection based on multiple genetic diversity measures using Mixed Replica search.

7. Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning

6. Modulating activity of the APC/C regulator SISAMBA improves the sugar and antioxidant content of tomato fruits

5. Core Hunter 3: flexible core subset selection

4. JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

3. Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection

2. Heuristic exploitation of genetic structure in marker-assisted gene pyramiding problems.

1. Core Hunter II: fast core subset selection based on multiple genetic diversity measures using Mixed Replica search.