Jean-daniel Zucker

Jean-daniel Zucker
Institute of Research for Development | IRD · Mathematical and Computer Modelling of Dynamical Systems (UMMISCO) - UMI 209 SU/IRD

Senior Researcher (DRCE)

About

346
Publications
63,703
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13,149
Citations
Citations since 2016
70 Research Items
8146 Citations
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201620172018201920202021202202004006008001,0001,2001,400
201620172018201920202021202202004006008001,0001,2001,400
Introduction
My research focus is AI, Machine Learning, Multi-Scale Agent-based modelling of Complex Systems from Omics data integration to Environmental Decision system. I am a Former Engineer (Sup’Aéro,1985). In 1996 I got my Ph.D. in Machine Learning from Paris 6 Univ. where I became an associate professor. In 2002 I became Full Prof. at Paris 13 University. In 2008 I became a Senior Researcher at IRD. I am the director of the UMMISCO Lab. on Math. and Comput.Modeling of Complex Systems since 2014.
Additional affiliations
September 2015 - December 2019
Institute of Cardiometabolism and Nutrition
Position
  • Head of Department
Description
  • Personalized Omics-Based Medicine projects in the IHU ICAN
January 2014 - April 2021
Institute of Research for Development
Position
  • Managing Director
September 2010 - August 2015
Vietnam National University - Hanoi
Position
  • Associated Senior Researcher
Description
  • IFI/MSI@VNU 144 Xuan Thuy, Cau Giay, Ha Noi, Viet Nam.

Publications

Publications (346)
Book
Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences....
Article
Feature selection is an important step when building a classifier on high dimensional data. As the number of observations is small, the feature selection tends to be unstable. It is common that two feature subsets, obtained from different datasets but dealing with the same classification problem, do not overlap significantly. Although it is a cruci...
Article
Full-text available
We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previo...
Article
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Background Microbiome biomarker discovery for patient diagnosis, prognosis, and risk evaluation is attracting broad interest. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive models stemming from machine learning still behave as bl...
Conference Paper
Full-text available
Agent-based modeling is now widely used to investigate complex systems but still lacks integrated and generic tools to support the representation of features usually associated with real complex systems, namely rich, dynamic and realistic environments or multiple levels of agency. The GAMA platform has been developed to address such issues and allo...
Article
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Roux-en-Y gastric bypass (RYGB) is efficient at inducing drastic albeit variable weight loss and type-2 diabetes (T2D) improvements in patients with severe obesity and T2D. We hypothesized a causal implication of the gut microbiota (GM) in these metabolic benefits, as RYGB is known to deeply impact its composition. In a cohort of 100 patients with...
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At a time when the impacts of climate change and increasing urbanization are making risk management more complex, there is an urgent need for tools to better support risk managers. One approach increasingly used in crisis management is preventive mass evacuation. However, to implement and evaluate the effectiveness of such strategy can be complex,...
Preprint
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The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, contrary to the so-called conventional biostatistical methods where...
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Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and res...
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Objectives Gut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome’s functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the rol...
Article
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Background: Dietary intervention is a cornerstone of weight loss therapies. In obesity, a dysbiotic gut microbiota (GM) is characterized by high levels of Bacteroides lineages and low diversity. We examined the GM composition changes, including the Bacteroides 2 enterotype (Bact2), in a real-world weight loss study in subjects following a high-pro...
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During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1,2,3,4,5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the ex...
Article
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The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed for characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenge. To f...
Article
Aims Congenital long-QT syndromes (cLQTS) or drug-induced long-QT syndromes (diLQTS) can cause torsade de pointes (TdP), a life-threatening ventricular arrhythmia. The current strategy for the identification of drugs at the high risk of TdP relies on measuring the QT interval corrected for heart rate (QTc) on the electrocardiogram (ECG). However, Q...
Preprint
Full-text available
Background: The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challen...
Article
Full-text available
Interactions between diet and gut microbiota are critical regulators of energy metabolism. The effects of fibre intake have been deeply studied but little is known about the impact of proteins. Here, we investigated the effects of high protein supplementation (Investigational Product, IP) in a double blind, randomised placebo-controled intervention...
Chapter
Full-text available
According to recent studies, Vietnam is one of the twenty countries most affected by natural disasters in the world, and particularly by floods either on the low elevation coastal zones (risk of submersion) or along the Red River and the Mekong River (risk of flooding). In this context, dams are both means of mitigation but also threats given the p...
Conference Paper
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The need to adapt human resources to the activity workload is omnipresent in most sectors, especially when the activity variability depends on exogenous factors. Artificial intelligence seems to offer unprecedented opportunities for improving forecasting. However, its application to real-world business contexts still reveals critical breaches. In t...
Preprint
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Congenital or drug-induced long-QT syndromes can cause Torsade-de-Pointes (TdP), a life-threatening ventricular arrhythmia. The current strategy to identify individuals at high risk of TdP consists on measuring the QT duration on the electrocardiogram (ECG), shown to provide limited information. We propose an original method, including training dee...
Article
Full-text available
Like a hydra, fraudsters adapt and circumvent increasingly sophisticated barriers erected by public or private institutions. Among these institutions, banks must quickly take measures to avoid losses while guaranteeing the satisfaction of law-abiding customers. Facing an expanding flow of operations, effective banking relies on data analytics to su...
Chapter
Over the past decade, technological advances have made high-speed, high-resolution sequencing of genetic material possible at ever lower cost (from millions to one hundred dollars). In this context, the human microbiome has demonstrated its ability to support the stratification and the classification of various human diseases. Thus, the gut microbi...
Preprint
Full-text available
Background: The gut microbiome plays a major role in chronic diseases, several of which are characterized by an altered diversity and composition of bacterial communities. Large-scale sequencing projects allowed the characterization of these microbial community perturbations. However, a gap remains in how these discoveries can be translated into cl...
Article
Full-text available
Gut microbes are considered as major factors contributing to human health. Nowadays, the vast majority of the data available in the literature are mostly exhibiting negative or positive correlations between specific bacteria and metabolic parameters. From these observations, putative detrimental or beneficial effects are then inferred. Akkermansia...
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Addressing the heterogeneity of both the outcome of a disease and the treatment response to an intervention is a mandatory pathway for regulatory approval of medicines. In randomized clinical trials (RCTs), confirmatory subgroup analyses focus on the assessment of drugs in predefined subgroups, while exploratory ones allow a posteriori the identifi...
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Microbiota-host-diet interactions contribute to the development of metabolic diseases. Imidazole propionate is a novel microbially produced metabolite from histidine, which impairs glucose metabolism. Here, we show that subjects with prediabetes and diabetes in the MetaCardis cohort from three European countries have elevated serum imidazole propio...
Preprint
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A bstract Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DN...
Article
Résumé L’intelligence artificielle (IA) fait de grand progrès au service de la médecine en général et des maladies métaboliques en particulier. L’apprentissage automatique, grâce notamment aux réseaux de neurones et la démultiplication des données massives de phénotypage, améliore considérablement l’aide au diagnostic médical. On peut ainsi augment...
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Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans1,2. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low micro...
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Gut microbiota composition is influenced by environmental factors and has been shown to impact body metabolism.OBJECTIVE: To assess the gut microbiota profile before and after Roux-en-Y gastric bypass (RYGB) and the correlation with food intake and postoperative type 2 diabetes remission (T2Dr).DESIGN: Gut microbiota profile from obese diabetic wom...
Article
Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low microbia...
Article
Full-text available
Introduction Low gut microbiome richness is associated with dyslipidemia and insulin resistance, and ceramides and other sphingolipids are implicated in the development of diabetes. Objectives Determine whether circulating sphingolipids, particularly ceramides, are associated with alterations in the gut microbiome among obese patients with increas...
Article
The gut bacterial species, Akkermansia muciniphila is associated with a healthier clinical profile. The purpose of this study was to determine the association between A. muciniphila and glucose homeostasis in patients undergoing bariatric surgery (BS): gastric banding (GB) or Roux-en-Y gastric bypass (RYGB). This non-randomized prospective study in...
Conference Paper
Full-text available
Partial or total horizontal evacuation of populations in urban areas is an important protection measure against a natural or technological risk. However, casualties during massive displacement in a context of stress and in a potentially degraded environment may be high due to non-compliance with instructions, accidents, traffic jams, incivilities,...
Article
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Purpose: DiaRem is a clinical scoring system designed to predict diabetes remission (DR) 1-year post-Roux-en-Y gastric bypass (RYGB). We examined long-term (2- and 5-year) postoperative DR prediction by DiaRem and an advanced-DiaRem (Ad-DiaRem) score following RYGB, sleeve gastrectomy (SG), and gastric banding (GB). Methods: We accessed data fro...
Article
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Background: The mechanisms responsible for calorie restriction (CR)-induced improvement in insulin sensitivity (IS) have not been fully elucidated. Greater insight can be achieved through deep biological phenotyping of subjects undergoing CR, and integration of big data. Materials and Methods: An integrative approach was applied to investigate ass...
Article
An important question in microbiology is whether treatment causes changes in gut flora, and whether it also affects metabolism. The reconstruction of causal relations purely from non-temporal observational data is challenging. We address the problem of causal inference in a bivariate case, where the joint distribution of two variables is observed....
Article
In a number of real life applications, scientists do not have access to temporal data, since budget for data acquisition is always limited. Here we challenge the problem of causal inference between groups of heterogeneous non-temporal observations obtained from multiple sources. We consider a family of probabilistic algorithms for causal inference...
Preprint
Full-text available
Biomarker discovery using metagenomic data is becoming more prevalent for patient diagnosis, prognosis and risk evaluation. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive models stemming from machine learning still behave as blac...
Article
Objective: Roux-en-Y gastric bypass (RYGB) induces type 2 diabetes remission (DR) in 60% of patients at 1 year, yet long-term relapse occurs in half of these patients. Scoring methods to predict DR outcomes 1 year after surgery that include only baseline parameters cannot accurately predict 5-year DR (5y-DR). We aimed to develop a new score to bet...
Chapter
An important question in microbiology is whether treatment causes changes in gut flora, and whether it also affects metabolism. The reconstruction of causal relations purely from non-temporal observational data is challenging. We address the problem of causal inference in a bivariate case, where the joint distribution of two variables is observed....
Chapter
A compact easily applicable and highly accurate classification model is of a big interest in decision making. A simple scoring system which stratifies patients efficiently can help a clinician in diagnostics or with the choice of treatment. Deep learning methods are becoming the preferred approach for various applications in artificial intelligence...
Preprint
Full-text available
Deep learning (DL) techniques have shown unprecedented success when applied to images, waveforms, and text. Generally, when the sample size ($N$) is much bigger than the number of features ($d$), DL often outperforms other machine learning (ML) techniques, often through the use of Convolutional Neural Networks (CNNs). However, in many bioinformatic...
Article
Full-text available
Objectives: Decreased gut microbial gene richness (MGR) and compositional changes are associated with adverse metabolism in overweight or moderate obesity, but lack characterisation in severe obesity. Bariatric surgery (BS) improves metabolism and inflammation in severe obesity and is associated with gut microbiota modifications. Here, we characte...
Article
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Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery‐driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We ar...
Article
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Statistical dependencies between two variables X and Y indicate that either X causes Y , or Y causes X, or there exists a latent variable Z which influences X and Y. In biology and medicine, an important problem is to find genetic or environmental unobserved causes of phenotypic difference between individuals. In this contribution, we introduce a n...
Article
Full-text available
Deep learning (DL) techniques have had unprecedented success when applied to images, waveforms, and texts to cite a few. In general, when the sample size (N) is much greater than the number of features (d), DL outperforms previous machine learning (ML) techniques, often through the use of convolution neural networks (CNNs). However, in many bioinfo...
Article
Given a classification task, an approach to improve accuracy relies on the use of abstaining classifiers. These classifiers are trained to reject observations for which predicted values are not reliable enough: these rejected observations belong to an abstaining area in the feature space. Two equivalent methods exist to theoretically compute the op...