Abdelhalim Larhlimi

Abdelhalim Larhlimi

Université de Nantes

H-index: 15

Europe-France

About Abdelhalim Larhlimi

Abdelhalim Larhlimi, With an exceptional h-index of 15 and a recent h-index of 11 (since 2020), a distinguished researcher at Université de Nantes, specializes in the field of Systems biology, Constraint-based modelling, metabolic networks.

Abdelhalim Larhlimi Information

University

Université de Nantes

Position

- LS2N - Combi

Citations(all)

1538

Citations(since 2020)

891

Cited By

1059

hIndex(all)

15

hIndex(since 2020)

11

i10Index(all)

19

i10Index(since 2020)

12

Email

University Profile Page

Université de Nantes

Abdelhalim Larhlimi Skills & Research Interests

Systems biology

Constraint-based modelling

metabolic networks

Top articles of Abdelhalim Larhlimi

Reconciliation and evolution of Penicillium rubens genome-scale metabolic networks–What about specialised metabolism?

In recent years, genome sequencing of filamentous fungi has revealed a high proportion of specialised metabolites with growing pharmaceutical interest. However, detecting such metabolites through in silico genome analysis does not necessarily guarantee their expression under laboratory conditions. However, one plausible strategy for enabling their production lies in modifying the growth conditions. Devising a comprehensive experimental design testing in different culture environments is time-consuming and expensive. Therefore, using in silico modelling as a preliminary step, such as Genome-Scale Metabolic Network (GSMN), represents a promising approach to predicting and understanding the observed specialised metabolite production in a given organism. To address these questions, we reconstructed a new high-quality GSMN for the Penicillium rubens Wisconsin 54–1255 strain, a commonly used model organism. Our reconstruction, iPrub22, adheres to current convention standards and quality criteria, incorporating updated functional annotations, orthology searches with different GSMN templates, data from previous reconstructions, and manual curation steps targeting primary and specialised metabolites. With a MEMOTE score of 74% and a metabolic coverage of 45%, iPrub22 includes 5,192 unique metabolites interconnected by 5,919 reactions, of which 5,033 are supported by at least one genomic sequence. Of the metabolites present in iPrub22, 13% are categorised as belonging to specialised metabolism. While our high-quality GSMN provides a valuable resource for investigating known phenotypes expressed in P. rubens …

Authors

Delphine Nègre,Abdelhalim Larhlimi,Samuel Bertrand

Journal

Plos one

Published Date

2023/8/30

Contribution of genome‐scale metabolic modelling to niche theory

Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome‐scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so‐called metabolic niche resumes well‐known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence–absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better …

Authors

Antoine Régimbeau,Marko Budinich,Abdelhalim Larhlimi,Juan José Pierella Karlusich,Olivier Aumont,Laurent Memery,Chris Bowler,Damien Eveillard

Journal

Ecology Letters

Published Date

2022/6

Seipin localizes at endoplasmic-reticulum-mitochondria contact sites to control mitochondrial calcium import and metabolism in adipocytes

Deficiency of the endoplasmic reticulum (ER) protein seipin results in generalized lipodystrophy by incompletely understood mechanisms. Here, we report mitochondrial abnormalities in seipin-deficient patient cells. A subset of seipin is enriched at ER-mitochondria contact sites (MAMs) in human and mouse cells and localizes in the vicinity of calcium regulators SERCA2, IP3R, and VDAC. Seipin association with MAM calcium regulators is stimulated by fasting-like stimuli, while seipin association with lipid droplets is promoted by lipid loading. Acute seipin removal does not alter ER calcium stores but leads to defective mitochondrial calcium import accompanied by a widespread reduction in Krebs cycle metabolites and ATP levels. In mice, inducible seipin deletion leads to mitochondrial dysfunctions preceding the development of metabolic complications. Together, these data suggest that seipin controls …

Authors

Yoann Combot,Veijo T Salo,Gilliane Chadeuf,Maarit Hölttä,Katharina Ven,Ilari Pulli,Simon Ducheix,Claire Pecqueur,Ophélie Renoult,Behnam Lak,Shiqian Li,Leena Karhinen,Ilya Belevich,Cedric Le May,Jennifer Rieusset,Soazig Le Lay,Mikael Croyal,Karim Si Tayeb,Helena Vihinen,Eija Jokitalo,Kid Törnquist,Corinne Vigouroux,Bertrand Cariou,Jocelyne Magré,Abdelhalim Larhlimi,Elina Ikonen,Xavier Prieur

Journal

Cell reports

Published Date

2022/1/11

MATHEMATICAL DESCRIPTIONS OF THE STEADY-STATE FLUX CONE.

The increasing amount of available molecular data has enabled the reconstruction of genome-scale metabolic networks of numerous living organisms. A thorough understanding of these complex networks requires the use of efficient computational and mathematical approaches. In this review, we present the key methods largely used to model and analyze metabolic networks. We make focus on constraint-based modeling which describes the solution space containing all the feasible metabolic behaviors of a living organism under steady-state conditions. The properties of this flux space can mainly be investigated either by optimization-based approaches or by pathway-based network analysis.

Authors

Abdelhalim Larhlimi

Published Date

2020/7/1

Bayesian integrative modeling of genome-scale metabolic and regulatory networks

The integration of high-throughput data to build predictive computational models of cellular metabolism is a major challenge of systems biology. These models are needed to predict cellular responses to genetic and environmental perturbations. Typically, this response involves both metabolic regulations related to the kinetic properties of enzymes and a genetic regulation affecting their concentrations. Thus, the integration of the transcriptional regulatory information is required to improve the accuracy and predictive ability of metabolic models. Integrative modeling is of primary importance to guide the search for various applications such as discovering novel potential drug targets to develop efficient therapeutic strategies for various diseases. In this paper, we propose an integrative predictive model based on techniques combining semantic web, probabilistic modeling, and constraint-based modeling methods. We applied our approach to human cancer metabolism to predict in silico the growth response of specific cancer cells under approved drug effects. Our method has proven successful in predicting the biomass rates of human liver cancer cells under drug-induced transcriptional perturbations.

Authors

Hanen Mhamdi,Jérémie Bourdon,Abdelhalim Larhlimi,Mourad Elloumi

Journal

Informatics

Published Date

2020/1/14

See List of Professors in Abdelhalim Larhlimi University(Université de Nantes)

Abdelhalim Larhlimi FAQs

What is Abdelhalim Larhlimi's h-index at Université de Nantes?

The h-index of Abdelhalim Larhlimi has been 11 since 2020 and 15 in total.

What are Abdelhalim Larhlimi's top articles?

The articles with the titles of

Reconciliation and evolution of Penicillium rubens genome-scale metabolic networks–What about specialised metabolism?

Contribution of genome‐scale metabolic modelling to niche theory

Seipin localizes at endoplasmic-reticulum-mitochondria contact sites to control mitochondrial calcium import and metabolism in adipocytes

MATHEMATICAL DESCRIPTIONS OF THE STEADY-STATE FLUX CONE.

Bayesian integrative modeling of genome-scale metabolic and regulatory networks

are the top articles of Abdelhalim Larhlimi at Université de Nantes.

What are Abdelhalim Larhlimi's research interests?

The research interests of Abdelhalim Larhlimi are: Systems biology, Constraint-based modelling, metabolic networks

What is Abdelhalim Larhlimi's total number of citations?

Abdelhalim Larhlimi has 1,538 citations in total.

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