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Bioinformatics

RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data
RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data

Recent metabolomics measurement devices, such as mass spectrometers, produce extremely high-dimensional data. Together with small …

Intelligent Systems for Molecular Biology and European Conference on Computational Biology,  2021.
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Phylogenetic Manifold Regularization: a semi-supervised approach to predict transcription factor binding sites
Phylogenetic Manifold Regularization: a semi-supervised approach to predict transcription factor binding sites
The computational prediction of transcription factor binding sites remains a challenging problems in bioinformatics, despite …
International Conference on Bioinformatics and Biomedicine (BIBM),  2020.
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Mass spectra alignment using virtual lock-masses
Mass spectra alignment using virtual lock-masses
Mass spectrometry is a valued method to evaluate the metabolomics content of a biological sample. The recent advent of rapid ionization …
Nature Scientific Reports,  2019.
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Interpretable genotype-to-phenotype classifiers with performance guarantees
Interpretable genotype-to-phenotype classifiers with performance guarantees
Understanding the relationship between the genome of a cell and its phenotype is a central problem in precision medicine. Nonetheless, …
Nature Scientific Reports,  2018.
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