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Roman Sarrazin-Gendron

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2020 – today

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2024
[j3]
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  - journals/bioinformatics/CholSLBW24
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  - https://dblp.org/rec/journals/bioinformatics/CholSLBW24
Arnaud Chol, Roman Sarrazin-Gendron, Eric Lécuyer, Mathieu Blanchette, Jérôme Waldispühl:
PERFUMES: pipeline to extract RNA functional motifs and exposed structures. Bioinform. 40(2) (2024)
[j2]
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  - journals/bmcbi/DrogarisZZNSWCMBW24
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Chrisostomos Drogaris, Yanlin Zhang, Eric Zhang, Elena Nazarova, Roman Sarrazin-Gendron, Sélik Wilhelm-Landry, Yan Cyr, Jacek Majewski, Mathieu Blanchette, Jérôme Waldispühl:
ARGV: 3D genome structure exploration using augmented reality. BMC Bioinform. 25(1): 277 (2024)
[c4]
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  - conf/fdg/CaiSMGBRC0BSW24
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Eddie Cai, Roman Sarrazin-Gendron, Renata Mutalova, Parham Ghasemloo Gheidari, Alexander Butyaev, Gabriel Richard, Sébastien Caisse, Rob Knight, Mathieu Blanchette, Attila Szantner, Jérôme Waldispühl:
Learning the Game: Decoding the Differences between Novice and Expert Players in a Citizen Science Game with Millions of Players. FDG 2024: 31
2023
[c3]
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  - conf/chi/MutalovaSCRGCKB23
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Renata Mutalova, Roman Sarrazin-Gendron, Eddie Cai, Gabriel Richard, Parham Ghasemloo Gheidari, Sébastien Caisse, Rob Knight, Mathieu Blanchette, Attila Szantner, Jérôme Waldispühl:
Playing the System: Can Puzzle Players Teach us How to Solve Hard Problems? CHI 2023: 679:1-679:15
[c2]
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Renata Mutalova, Roman Sarrazin-Gendron, Parham Ghasemloo Gheidari, Eddie Cai, Gabriel Richard, Sébastien Caisse, Rob Knight, Mathieu Blanchette, Attila Szantner, Jérôme Waldispühl:
Player-Guided AI outperforms standard AI in Sequence Alignment Puzzles. CI 2023: 53-62
2021
[j1]
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  - journals/ploscb/SouleRSDW21
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Antoine Soulé, Vladimir Reinharz, Roman Sarrazin-Gendron, Alain Denise, Jérôme Waldispühl:
Finding recurrent RNA structural networks with fast maximal common subgraphs of edge-colored graphs. PLoS Comput. Biol. 17(5) (2021)
2020
[c1]
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  - conf/recomb/Sarrazin-Gendron20
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Roman Sarrazin-Gendron, Hua-Ting Yao, Vladimir Reinharz, Carlos G. Oliver, Yann Ponty, Jérôme Waldispühl:
Stochastic Sampling of Structural Contexts Improves the Scalability and Accuracy of RNA 3D Module Identification. RECOMB 2020: 186-201

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