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Research Interests: Flow Cytometry, Fluorescence Microscopy, Biology, Medicine, Multidisciplinary, and 15 moreCell Culture, HIV, Cell line, In Vitro, Hiv Infection, Green Fluorescent Protein, Pyridines, Microbial Sensitivity Tests, Reverse Transcriptase, Recombinant Proteins, Syncytium, Direct Method, Nevirapine, Infectivity, and reverse transcriptase inhibitors
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Research Interests: Mathematics, Computer Science, Algorithms, Artificial Intelligence, Machine Learning, and 14 moreComputational Biology, Biology, Medicine, Biological Sciences, Computer Simulation, Mathematical Sciences, Kernel Methods, BMC Bioinformatics, Peptides, String Kernel, Bioactive Peptides, In Silico, alleles, and binding sites
Research Interests: Computer Science, Algorithms, Machine Learning, Computational Biology, Biology, and 14 moreResearch, Medicine, Software, Humans, Text Categorization, Support vector machine, String Kernel, Clinical Sciences, Computer User Interface Design, Human immunodeficiency virus, Retrovirology, Internet, Multiple alignment, and HIV infections
Research Interests: Computer Science, Artificial Intelligence, Machine Learning, Heuristics, Graph Theory, and 15 moreBiology, Drug Discovery, Medicine, Algorithm, Biological Sciences, Model, Mathematical Sciences, Approach, Kernel Methods, Antimicrobial Cationic Peptides, Laboratory Experiments, Amino Acid Sequence, Bioactivity, Molecular Sequence Data, and Data Generation
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Research Interests: Algorithms, Artificial Intelligence, Immunology, Machine Learning, Computational Biology, and 15 moreVaccines, Biology, Medicine, Software, Humans, Mice, Animals, Epitope mapping, Antigen Presentation, Peptides, Major histocompatibility complex, Protein Binding, MHC class I, Human leukocyte antigen, and epitope
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Background Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication... more
Background Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada. Methods We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health...
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Motivation: Breakthroughs in high-throughput technologies and machine learning methods have enabled the shift towards multi-omics modeling as the preferred mean to understand the mechanisms underlying biological processes, and to improve... more
Motivation: Breakthroughs in high-throughput technologies and machine learning methods have enabled the shift towards multi-omics modeling as the preferred mean to understand the mechanisms underlying biological processes, and to improve complex disease prognosis in clinical settings. However, most multi-omic studies only use transcriptomics and epigenomics due to their over-representation in databases and their early technical maturity compared to others omics. For complex phenotypes and mechanisms, not leveraging all the omics despite their varying degree of availability can lead to a failure to understand the underlying biological mechanisms. Results: We proposed MOT (Multi-Omic Transformer), a deep learning based model using the transformer architecture, that discriminates complex phenotypes (herein cancers types) based on five omics data type regardless of their availability: transcriptomics (mRNA and miRNA), epigenomics (DNA methylation), copy number variations (CNVs), and pro...
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Background Deep learning methods are a proven commodity in many fields and endeavors. One of these endeavors is predicting the presence of adverse drug–drug interactions (DDIs). The models generated can predict, with reasonable accuracy,... more
Background Deep learning methods are a proven commodity in many fields and endeavors. One of these endeavors is predicting the presence of adverse drug–drug interactions (DDIs). The models generated can predict, with reasonable accuracy, the phenotypes arising from the drug interactions using their molecular structures. Nevertheless, this task requires improvement to be truly useful. Given the complexity of the predictive task, an extensive benchmarking on structure-based models for DDIs prediction was performed to evaluate their drawbacks and advantages. Results We rigorously tested various structure-based models that predict drug interactions using different splitting strategies to simulate different real-world scenarios. In addition to the effects of different training and testing setups on the robustness and generalizability of the models, we then explore the contribution of traditional approaches such as multitask learning and data augmentation. Conclusion Structure-based model...
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Triple negative breast cancer (TNBC) is one of the most aggressive form of breast cancer (BC) with the highest mortality due to high rate of relapse, resistance, and lack of an effective treatment. Various molecular approaches have been... more
Triple negative breast cancer (TNBC) is one of the most aggressive form of breast cancer (BC) with the highest mortality due to high rate of relapse, resistance, and lack of an effective treatment. Various molecular approaches have been used to target TNBC but with little success. Here, using machine learning algorithms, we analyzed the available BC data from the Cancer Genome Atlas Network (TCGA) and have identified two potential genes, TBC1D9 (TBC1 domain family member 9) and MFGE8 (Milk Fat Globule-EGF Factor 8 Protein), that could successfully differentiate TNBC from non-TNBC, irrespective of their heterogeneity. TBC1D9 is under-expressed in TNBC as compared to non-TNBC patients, while MFGE8 is over-expressed. Overexpression of TBC1D9 has a better prognosis whereas overexpression of MFGE8 correlates with a poor prognosis. Protein–protein interaction analysis by affinity purification mass spectrometry (AP-MS) and proximity biotinylation (BioID) experiments identified a role for T...
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... to KL Regularization}, author = {Pascal Germain and Alexandre Lacasse and Francois Laviolette and Mario Marchand and Sara Shanian}, booktitle ... Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced... more
... to KL Regularization}, author = {Pascal Germain and Alexandre Lacasse and Francois Laviolette and Mario Marchand and Sara Shanian}, booktitle ... Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data}}, author = {Hussain, Z. and ...
Mass spectrometry is a valued method to evaluate the metabolomics content of a biological sample. The recent advent of rapid ionization technologies such as Laser Diode Thermal Desorption (LDTD) and Direct Analysis in Real Time (DART) has... more
Mass spectrometry is a valued method to evaluate the metabolomics content of a biological sample. The recent advent of rapid ionization technologies such as Laser Diode Thermal Desorption (LDTD) and Direct Analysis in Real Time (DART) has rendered high-throughput mass spectrometry possible. It is used for large-scale comparative analysis of populations of samples. In practice, many factors resulting from the environment, the protocol, and even the instrument itself, can lead to minor discrepancies between spectra, rendering automated comparative analysis difficult. In this work, a sequence/pipeline of algorithms to correct variations between spectra is proposed. The algorithms correct multiple spectra by identifying peaks that are common to all and, from those, computes a spectrum-specific correction. We show that these algorithms increase comparability within large datasets of spectra, facilitating comparative analysis, such as machine learning.
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Antimicrobial resistance (AMR) is continuing to grow across the world. Though often thought of as a mostly public health issue, AMR is also a major agricultural and environmental problem. As such, many researchers refer to it as the... more
Antimicrobial resistance (AMR) is continuing to grow across the world. Though often thought of as a mostly public health issue, AMR is also a major agricultural and environmental problem. As such, many researchers refer to it as the preeminent One Health issue. Aerial transport of antimicrobial-resistant bacteria via bioaerosols is still poorly understood. Recent work has highlighted the presence of antibiotic resistance genes in bioaerosols. Emissions of AMR bacteria and genes have been detected from various sources, including wastewater treatment plants, hospitals, and agricultural practices; however, their impacts on the broader environment are poorly understood. Contextualizing the roles of bioaerosols in the dissemination of AMR necessitates a multidisciplinary approach. Environmental factors, industrial and medical practices, as well as ecological principles influence the aerial dissemination of resistant bacteria. This article introduces an ongoing project assessing the prese...
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The lactococcal virulent phage p2 is a model for studying the Skunavirus genus, the most prevalent group of phages causing milk fermentation failures in cheese factories worldwide. This siphophage infects Lactococcus lactis MG1363, a... more
The lactococcal virulent phage p2 is a model for studying the Skunavirus genus, the most prevalent group of phages causing milk fermentation failures in cheese factories worldwide. This siphophage infects Lactococcus lactis MG1363, a model strain used to study Gram-positive lactic acid bacteria. The structural proteins of phage p2 have been thoroughly described, while most of its non-structural proteins remain uncharacterized. Here, we developed an integrative approach, making use of structural biology, genomics, physiology, and proteomics to provide insights into the function of ORF47, the most conserved non-structural protein of unknown function among the Skunavirus genus. This small phage protein, which is composed of three α-helices, was found to have a major impact on the bacterial proteome during phage infection and to significantly reduce the emergence of bacteriophage-insensitive mutants.
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Background: With the advent of metagenomics, many large studies have been conducted with the quest of better understanding gut microbiota changes in relation to varying health conditions. Significant findings have been made for diseases... more
Background: With the advent of metagenomics, many large studies have been conducted with the quest of better understanding gut microbiota changes in relation to varying health conditions. Significant findings have been made for diseases such as cirrhosis, colorectal cancers, inflammatory bowel diseases and others, yet one that stands out is obesity for which conflicting results have been reported in the literature. Methods: Here, we built and analyzed a cross-study dataset of healthy and obese individuals looking for major changes in the the taxonomic and functional composition of their metagenomes. Results: Our results suggest that the overweight and normal subjects have no strong dissimilarity in their metagenomes composition. Significant differences were observed when comparing the obese and the non-obese individuals in their functional and taxonomic profiles. Conclusion: In this study, we report the most significant changes that we observed and discuss their potential implicatio...
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Carbapenemase-producing Enterobacterales, including KPC-2 producers, have become a major clinical problem. During an outbreak in Quebec City, Canada, KPC-2-producing Klebsiella michiganensis and Citrobacter farmeri were isolated from a... more
Carbapenemase-producing Enterobacterales, including KPC-2 producers, have become a major clinical problem. During an outbreak in Quebec City, Canada, KPC-2-producing Klebsiella michiganensis and Citrobacter farmeri were isolated from a patient six weeks apart. We determined their complete genome sequences. Both isolates carried nearly identical IncN2 plasmids with blaKPC-2 on a Tn4401b element. Both strains also carried IncP1 plasmids, but that of C. farmeri did not carry a Beta-lactamase gene, whereas that of K. michiganensis carried a second copy of blaKPC-2 on Tn4401b. These results suggest recent plasmid transfer between the two species and a recent transposition event.
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The St. Lawrence hydrographic system includes freshwater, brackish, and marine habitats, and is the largest waterway in North America by volume. The food-webs in these habitats are ultimately dependent on phytoplankton. Viral lysis is... more
The St. Lawrence hydrographic system includes freshwater, brackish, and marine habitats, and is the largest waterway in North America by volume. The food-webs in these habitats are ultimately dependent on phytoplankton. Viral lysis is believed to be responsible for a major part of phytoplankton mortality. To better understand their role, we characterized the diversity and distribution of two viral taxa infecting phytoplankton: the picornaviruses and phycodnaviruses. Our study focused on the estuary transition zone, which is an important nursery for invertebrates and fishes. Both viral taxa were investigated by PCR amplification of conserved molecular markers and next-generation sequencing at six sites, ranging from freshwater to marine. Our results revealed few shared viral phylotypes between saltwater and freshwater sites. Salinity appeared to be the primary determinant of viral community composition. Moreover, our analysis indicated that the viruses identified in this region of th...
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Romboutsia weinsteinii sp. nov. CCRI-19649(T) belongs to the genus Romboutsia The strain was isolated from a water sample harvested in Québec City, Québec, Canada. The genome assembly comprised 4,134,593 bp with a 29.3% GC content. This... more
Romboutsia weinsteinii sp. nov. CCRI-19649(T) belongs to the genus Romboutsia The strain was isolated from a water sample harvested in Québec City, Québec, Canada. The genome assembly comprised 4,134,593 bp with a 29.3% GC content. This is the first documentation that reports the genome sequence of R. weinsteinii.
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Lachnotalea glycerini CCRI-19302 belongs to the genus Lachnotalea The strain was isolated from a water sample harvested in Québec City, Canada. The genome assembly comprised 4,694,231 bp, with 34.6% GC content. This is the first... more
Lachnotalea glycerini CCRI-19302 belongs to the genus Lachnotalea The strain was isolated from a water sample harvested in Québec City, Canada. The genome assembly comprised 4,694,231 bp, with 34.6% GC content. This is the first documentation to report the genome sequence of a sporulating and motile strain of L. glycerini.
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It has been proposed that macrophages could serve as long-lived compartments for HIV-1 infection under in vivo situations because these cells are resistant to the virus-mediated cytopathic effect, produce progeny virus over extended... more
It has been proposed that macrophages could serve as long-lived compartments for HIV-1 infection under in vivo situations because these cells are resistant to the virus-mediated cytopathic effect, produce progeny virus over extended periods of time and are localized in tissues that are often less accessible by treatment. Comprehensive experimental studies are thus needed to characterize the HIV-1-induced modulation of host genes in these myeloid lineage cells. To shed light on this important issue, we performed comparative analyses of mRNA expression levels of host genes in uninfected bystander and HIV-1-infected human macrophages using an infectious reporter virus construct coupled with a large-scale RNA sequencing approach. We observed a rapid differential expression of several host factors in the productively infected macrophage population including genes regulating DNA replication factors and chromatin remodeling. A siRNA-mediated screening study to functionally identify host de...
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Research Interests: Conservation Biology, Conservation, Genome assembly, Fisheries, Biology, and 15 moreFish Biology, Fisheries Biology, Medicine, Functional Genomics, Biological Sciences, Biodiversity Conservation, Animals, Genome, Gene, Anguillid eels, American Eels, Anguilla, Freshwater Eel, Contig, and anguilla rostrata
Criibacterium bergeronii gen. nov., sp. nov., CCRI-22567 is the type strain of the new genus Criibacterium The strain was isolated from a woman with bacterial vaginosis. The genome assembly comprised 2,384,460 bp, with 34.4% G+C content.... more
Criibacterium bergeronii gen. nov., sp. nov., CCRI-22567 is the type strain of the new genus Criibacterium The strain was isolated from a woman with bacterial vaginosis. The genome assembly comprised 2,384,460 bp, with 34.4% G+C content. This is the first genome announcement of a strain belonging to the genus Criibacterium.
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ecent progress in DNA sequencing technology has yielded a new class of devices that allow for the analysis of genetic material with unprecedented speed and efficiency. These advances, styled under the name Next-Generation Sequencing... more
ecent progress in DNA sequencing technology has yielded a new class of devices that allow for the analysis of genetic material with unprecedented speed and efficiency. These advances, styled under the name Next-Generation Sequencing (NGS), increasingly shift the burden from chemistry done in a laboratory to a string manipulation problem, well suited to High-Performance Computing (HPC). By breaking up DNA into millions of small strands (20 to 1000 bases) and reading them in parallel, the rate at which genetic material can be acquired has increased by several orders of magnitude at the expense of a new distinction between raw and processed genetic data. The technology that generates raw genomic data is becoming increasingly fast and inexpensive when compared to the rate that this data can be analyzed. In general, assembling s mall reads into a useful form is done by either assembling individual reads (de novo) or mapping these pieces against a reference (mapping). In this paper, we pr...
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Bacteriophages are present in every environment that supports bacterial growth, including man made ecological niches. Virulent phages may even slow or, in more severe cases, interrupt bioprocesses driven by bacteria. Escherichia coli is... more
Bacteriophages are present in every environment that supports bacterial growth, including man made ecological niches. Virulent phages may even slow or, in more severe cases, interrupt bioprocesses driven by bacteria. Escherichia coli is one of the most widely used bacteria for large-scale bioprocesses; however, literature describing phage-host interactions in this industrial context is sparse. Here, we describe phage MED1 isolated from a failed industrial process. Phage MED1 (Microviridae family, with a single-stranded DNA [ssDNA] genome) is highly similar to the archetypal phage phiX174, sharing >95% identity between their genomic sequences. Whole-genome phylogenetic analysis of 52 microvirus genomes from public databases revealed three genotypes (alpha3, G4, and phiX174). Phage MED1 belongs to the phiX174 group. We analyzed the distribution of single nucleotide variants in MED1 and 18 other phiX174-like genomes and found that there are more missense mutations in genes G, B, and...
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Research Interests: Microbiology, Biofilms, Nonparametric Statistics, Computational Biology, Biology, and 15 moreMedicine, Multidisciplinary, Quebec, Phylogeny, Disease Outbreaks, Humans, Legionella pneumophila, Cluster Analysis, PLoS one, Legionella, Base Sequence, Outbreak, Serotype, Molecular Sequence Data, and Legionnaires Disease
Staphylococcus xylosus is a bacterial species used in meat fermentation and a commensal microorganism found on animals. We present the first complete circular genome from this species. The genome is composed of 2,757,557 bp, with a G+C... more
Staphylococcus xylosus is a bacterial species used in meat fermentation and a commensal microorganism found on animals. We present the first complete circular genome from this species. The genome is composed of 2,757,557 bp, with a G+C content of 32.9%, and contains 2,514 genes and 79 structural RNAs.
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Research Interests: Microbiology, Medical Microbiology, Biology, Applied microbiology, Antimicrobials, and 15 moreMedicine, Multidisciplinary, Biological Sciences, Humans, Industrial microbiology, Meat, Microbial Genomics, Phages, Microbial Evolution, Fermentation, Improving, Microbial Pathogens, Microbial control, Multilocus sequence typing, and food handling
Research Interests: Algorithms, Artificial Intelligence, Immunology, Machine Learning, Computational Biology, and 15 moreVaccines, Biology, Medicine, Software, Humans, Mice, Animals, Epitope mapping, Antigen Presentation, Peptides, Major histocompatibility complex, Protein Binding, MHC class I, Human leukocyte antigen, and epitope
Research Interests: Flow Cytometry, Biology, Membrane Proteins, Cell Biology, Biological Chemistry, and 15 moreApoptosis, Medicine, HIV, Biological Sciences, Caspases, Humans, Animals, Cell Death, Biological, CHEMICAL SCIENCES, Cell free System, Interleukin, Cysteine Proteinase Inhibitors, Inhibitor of apoptosis proteins, and Medical and Health Sciences
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Identification of proteins is one of the most computationally intensive steps in genomics studies. It usually relies on aligners that don’t accommodate rich information on proteins and require additional pipelining steps for protein... more
Identification of proteins is one of the most computationally intensive steps in genomics studies. It usually relies on aligners that don’t accommodate rich information on proteins and require additional pipelining steps for protein identification. We introduce kAAmer, a protein database engine based on amino-acid k-mers, that supports fast identification of proteins with complementary annotations. Moreover, the databases can be hosted and queried remotely.
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We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalize eight kernels, such as the... more
We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalize eight kernels, such as the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it's approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of accurately predicting the binding affinity of any peptide to any protein. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. On all benchm...
Research Interests: Mathematics, Computer Science, Algorithms, Artificial Intelligence, Machine Learning, and 13 moreComputational Biology, Biology, Medicine, Biological Sciences, Computer Simulation, Mathematical Sciences, Kernel Methods, BMC Bioinformatics, Peptides, String Kernel, Bioactive Peptides, alleles, and binding sites
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... This would aid in the discovery of apoptosis inhibitors, which could boost the immune response to infection. ... Anticancer Res 2001: 21: 1771-1776. 15. Tackels-Horae D. Goodman MD, Williams AJ, Wilson DJ, Eskandari T. Vogt LM, et al.... more
... This would aid in the discovery of apoptosis inhibitors, which could boost the immune response to infection. ... Anticancer Res 2001: 21: 1771-1776. 15. Tackels-Horae D. Goodman MD, Williams AJ, Wilson DJ, Eskandari T. Vogt LM, et al. ...
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ABSTRACT The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes from whole genomes. We propose a general... more
ABSTRACT The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes from whole genomes. We propose a general approach that relies on the Set Covering Machine and a k-mer representation of the genomes. We show results for the problem of predicting the resistance of Pseudomonas Aeruginosa, an important human pathogen, against 4 antibiotics. Our results demonstrate that extremely sparse models which are biologically relevant can be learnt using this approach.