Marzia A. Cremona is an assistant professor in data science in the department of Operations and Decision Systems at Laval University, and a researcher at the CHU de Québec – Université Laval research center. She obtained a Ph.D. in Mathematical Models and Methods for Engineering from Politecnico di Milano (Italy), and she joined Université Laval after spending four years at the Pennsylvania State University (US). Her research interests focus on the development of statistical and computational methods for the analysis of large, high-dimensional and complex data, and the application of such methods in computational biology. Indeed, much of her work is at the interface between statistics and “Omics” sciences.
Functional data analysis in computational biology
“Omics” data generated by Next Generation Sequencing (NGS) techniques pose several challenges for reliable statistical analysis that are needed to unveil biological mechanisms and the consequences they have on genome function and evolution, as well as on diseases. Most of these data are suitable to be considered at high resolution and represented as curves over the genome. Functional Data Analysis (FDA), a subfield of statistics that aim at analyzing curves (mathematical functions), plays a critical role in exploiting the output of NGS assays. Indeed, considering curves as statistical units endowed with shapes increases our ability to extract both interpretable global patterns and relevant local information from these data, allowing sophisticated biological interpretation of shape information.
An important part of Dr. Cremona’s research program concerns the development of novel FDA techniques, with the aim of broaden the scope of FDA to many areas of computational biology. An important aspect of her research is its collaborative and multidisciplinary nature. Indeed, she is involved in multiple international collaborations involving the analysis of various types of “Omics” data, for example on molecular evolution, evolutionary genomics and human genetics.
1050, chemin Sainte-Foy
J0-08
Québec, QC
Canada G1S 4L8
2449
Québec, Quebec
Canada G1V 0A6
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- Doroshenko, LyubovPostdoctoral fellow
- Fathi, HedayatDoctoral student
- Hafezalseheh, HesamMaster studenthesam.hafezalseheh.1@ulaval.ca
Accurate sequencing of DNA motifs able to form alternative (non-B) structures
Journal ArticleGenome Res, 33 (6), 2023.
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Rescuing biologically relevant consensus regions across replicated samples
Journal ArticleBMC Bioinformatics, 24 (1), 2023.
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COVID-19 effects on the Canadian term structure of interest rates
Journal ArticleRev Econ Anal, 14 (2), 2022.
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Advanced age increases frequencies of de novo mitochondrial mutations in macaque oocytes and somatic tissues
Journal ArticleProc Natl Acad Sci U S A, 119 (15), 2022.
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Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy
Journal ArticleSci Rep, 11 (1), 2021.
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Non-B DNA: a major contributor to small- and large-scale variation in nucleotide substitution frequencies across the genome
Journal ArticleNucleic Acids Res, 49 (3), 2021.
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Age-related accumulation of de novo mitochondrial mutations in mammalian oocytes and somatic tissues
Journal ArticlePLoS Biol, 18 (7), 2020.
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Human L1 Transposition Dynamics Unraveled with Functional Data Analysis
Journal ArticleMol Biol Evol, 37 (12), 2020.
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On the bias of H-scores for comparing biclusters, and how to correct it
Journal ArticleBioinformatics, 36 (9), 2020.
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Functional data analysis for computational biology
Journal ArticleBioinformatics, 35 (17), 2019.
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Active projects
- Applications of variable selection methods for scalar-on-function regression, from 2023-05-01 to 2024-04-30
- Centre interuniversitaire de recherche sur les réseaux d'entreprise, la logistique et le transport (CIRRELT), from 2022-04-01 to 2028-03-31
- Exploitation de méthodes statistiques pour les données fonctionnelles dans les études "omiques", from 2023-07-01 to 2027-06-30
- Exploitation de méthodes statistiques pour les données fonctionnelles dans les études "omiques", longitudinales et épidémiologiques, from 2023-07-01 to 2027-06-30
- Fonds de démarrage - Nouveau chercheur, from 2023-09-14 to 2025-03-31
- Functional data analysis methods for genomics and financial data, from 2020-04-01 to 2025-03-31
- Prédiction de l'hypoglycémie induite par l'exercice chez les jeunes atteints de diabète de type 1, from 2023-04-01 to 2024-03-31
- Probabilistic K-means with local alignment for clustering and motif discovery in functional data, from 2023-05-01 to 2024-04-30
- Unsupervised learning methods to discover patterns in fuctional data, from 2019-12-05 to 2025-04-30
Recently finished projects
- Age-Related accumulation of de novo mitochondrial mutations in mammalian oocytes and somatic tissues, from 2021-05-01 to 2022-04-30
- Bubble detection in time series via functional motif discovery, from 2020-06-01 to 2022-05-31
- Centre interuniversitaire de recherche sur les réseaux d'entreprise, la logistique et le transport (CIRRELT), from 2015-04-01 to 2022-03-31
- Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy, from 2022-02-21 to 2023-04-30
- Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy, from 2022-06-01 to 2023-04-30
- On the bias of H-scores for comparing biclusters, and how to correct it, from 2021-05-01 to 2022-04-30
- Price pattern detection via functional biclustering, from 2022-09-01 to 2023-02-02
- Sélection de variables fonctionnelles pertinentes à l'aide d'espaces de Hilbert à noyau reproduisant, from 2022-02-02 to 2022-04-30