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Network medicine

Publications associées (22)

Unveiling gene perturbation effects through gene regulatory networks inference from single-cell transcriptomic data

Physiological and pathological processes are governed by networks of genes called gene regulatory networks (GRNs). By reconstructing GRNs, we can accurately model how cells behave in their natural state and predict how genetic changes will affect them. Transcriptomic data of single cells are now available for a wide range of cellular processes in multiple species. Thus, a method building predictive GRNs from single-cell RNA sequencing (scRNA-seq) data, without any additional prior knowledge, could have a gr

2026

Environmental selection constrains metabolic network architecture despite taxonomic turnover in anaerobic digestion communities

Microbial ecosystems often sustain stable metabolic functions despite pronounced taxonomic turnover, yet the mechanisms underlying such reproducible functional states remain poorly understood. Here, we investigated how physicochemical constraints shape functional convergence in anaerobic digestion communities using replicated serial enrichments seeded from four distinct inocula. Across three pH levels and six substrate regimes, replicate communities from different inocula consistently converged toward repro

Oxford University Press (OUP)2026

Unveiling functional-metabolic synergy in the healthy brain: multivariate integration of dynamic [ 18 F]FDG-PET and resting-state fMRI

Introduction Despite accounting for only 2% of body weight, the human brain requires significant amounts of glucose, even at rest, underscoring the importance of functional-metabolic relationships. Previous studies revealed moderate associations between resting-state fMRI functional connectivity (FC) and local metabolism via [ 18 F]FDG-PET, yet much remains to be understood, particularly regarding their coupling between functional and metabolic networks. Methods To this end, we employed multivariate Partial

bioRxiv2025

in silico analysis and comparison of the metabolic capabilities of different organisms by reducing metabolic complexity

Understanding how metabolic capabilities diverge across microbial species is fundamental for deciphering community function, ecological interactions, and for guiding synthetic microbiome design. Despite shared core pathways, microbial phenotypes can differ markedly due to evolutionary adaptations and metabolic specialization. Genome-scale metabolic models (GEMs) provide a systems-level framework to explore these differences; however, their complexity poses significant challenges to direct comparison. Here,

Cold Spring Harbor Laboratory2025

Multi-Head Attention: Collaborate Instead of Concatenate

Attention layers are widely used in natural language processing (NLP) and are beginning to influence computer vision architectures. Training very large transformer models allowed significant improvement in both fields, but once trained, these networks show symptoms of overparameterization. For instance, it is known that many attention heads can be pruned without impacting accuracy. This work aims to enhance current understanding on how multiple heads interact. Motivated by the observation that attention hea

arXiv2020

Brain networks and their relevance for stroke rehabilitation

Friedhelm Christoph Hummel, Philipp Johannes Koch

Stroke has long been regarded as focal disease with circumscribed damage leading to neurological deficits. However, advances in methods for assessing the human brain and in statistics have enabled new tools for the examination of the consequences of stroke ...

2019

Control Theory Concepts for Modeling Uncertainty in Enzyme Kinetics of Biochemical Networks

Vassily Hatzimanikatis, Ljubisa Miskovic, Georgios Savoglidis, Milenko Tokic

Analysis of the dynamic and steady-state properties of biochemical networks hinges on information about the parameters of enzyme kinetics. The lack of experimental data characterizing enzyme activities and kinetics along with the associated uncertainties i ...

2019

Investigating the deregulation of metabolic tasks via Minimum Network Enrichment Analysis (MiNEA) as applied to nonalcoholic fatty liver disease using mouse and human omics data

Vassily Hatzimanikatis, Vikash Kumar Pandey

Nonalcoholic fatty liver disease (NAFLD) is associated with metabolic syndromes spanning a wide spectrum of diseases, from simple steatosis to the more complex nonalcoholic steatohepatitis. To identify the deregulation that occurs in metabolic processes at ...

2019

Explore RdhK based regulatory network of organohalide respiration using a hybrid proteins strategy

Christof Holliger

Reductive dehalogenase (rdh) gene clusters are encoding proteins that enable organohalide respiring bacteria (OHRB) to couple the degradation of halogenated molecules to energy conservation. The transcription of rdh gene clusters is regulated by RdhK regulators belonging to the CRP/FNR-family. RdhK6 (previously called CprK1) in Desulfitobacterium hafniense was shown to activate the transcription of the chlorophenol rdh genes in presence of 3-hydroxy-4-chlorophenylacetate1,2. RdhK effector-binding domain bin

2019

Evaluating the similarity of biochemical reactions and its uses for mapping novel and orphan reactions to protein sequences

Recent advances in synthetic biochemistry have resulted in a wealth of de novo hypothetical enzymatic reactions that are not matched to protein-encoding genes, deeming them “orphan”. Nearly half of known metabolic enzymes are also orphan, leaving important gaps in metabolic network maps. Proposing genes for the catalysis of orphan reactions is critical for applications ranging from biotechnology to medicine. In this work, a novel computational method, BridgIT, assigned a potential enzyme sequence to orphan

2018

Mapping the diverse phenotypic states of yeast lipid metabolism to enzymes using mechanistic kinetic models

Lipids carry a very important role in cell structure and function, as well as in the physiopathology of many diseases. Maintenance of the lipid profiles should be tightly regulated as it is very important for preserving membrane permeability, cell integrity and several other functions. Large-scale kinetic models of metabolic networks are essential in order to accurately capture and predict such behaviors of cellular systems when subject to perturbations. To this end, we developed a detailed model of the lip

2018

Toward fully characterized knowledge gaps in metabolic networks: discovery of missing biochemistry in Escherichia coli

Advances in medicine and biotechnology rely on the further understanding of biological processes. Despite the technological advances and increasing available types and amounts of omics data, significant biochemical knowledge gaps remain uncharacterised. We necessitate methods that enable analysing the growing sets of data and identifying the knowledge gaps in a systematic way. In this study, we develop an approach to classify and characterise the knowledge gaps in metabolic networks. We use the recently dev

2017

Unlocking the full potential of kinetic metabolic models through characterization and reduction of uncertainty

Ljubisa Miskovic

Kinetic models are the most promising tool for comprehending the complex dynamic behavior of living cells. The primary goal of kinetic models is to capture the properties of the metabolic networks as a whole, and we need large-scale models for dependable in silico analyses of metabolism. However, the uncertainty in kinetic parameters is the main obstacle hindering the development of kinetic models, and the levels of uncertainty increase with the size of the models. Therefore, there is a need for tools that

2017

Facing The Unknown: Suggesting Alternative Novel Biochemistry in Escherichia coli and Saccharomyces cerevisiae

While advances in genome sequencing have greatly facilitated the inference of metabolic networks, the presence of unknown biochemistry in the organisms still challenges the analysis and understanding of metabolism. Even for one of the most known organism like Escherichia coli, there are around 10% of its open reading frames (ORFs) that remain to be annotated. The experimental identification of metabolic capabilities in an organism will benefit from the guidance from computational analysis. The study of geno

2017

A kinetic model of the lipid network in yeast

Lipids play a very important role in cell structure and function, as well as in the physiopathology of many diseases. Maintenance of the lipid profiles should be tightly regulated as it is very important for preserving membrane permeability, cell integrity and several other functions. Large-scale kinetic models of metabolic networks are essential in order to accurately capture and predict such behaviors of cellular systems when subject to perturbations. We have thus developed a detailed model of the lipid m

2017

Identifying patterns in kinetic parameters that determine the impact of rate-limiting enzymes

Ljubisa Miskovic

Kinetic models are essential for studying complex behavior and properties of metabolism. However, a persistent hurdle for constructing these models is uncertainty in the kinetic properties of enzymes. Currently available methods for building kinetic models cope in an indirect way with uncertainties by integrating data from different biological levels and origins into models. In this context, we have recently proposed iSCHRUNK1 a new approach for characterization and reduction of uncertainty that makes use o

2016

Discovery and Evaluation of Novel Pathways for Production of the Second Generation of Biofuels

Ljubisa Miskovic

In an effort of overcoming the limited availability of fossil energy resources the focus of the research and development in the area of biofuels has moved towards developing the second generation of fuels that should be produced via microbial fermentation. The idea is to use as a feedstock inexpensive and abundant waste materials such as lignocellulosic biomass. The second generation biofuels should satisfy several criteria such as lower emission, higher energy density and should be less corrosive to engine

2016

In Silico Atom Labeling for the Reconstruction of Atom-mapped Metabolic Networks

Field of atom mapping of metabolic networks is lacking an automated approach, which accounts for the information of reaction mechanism for atom mapping and is extendable from atom-mapped reactions to atom-mapped reaction networks. We developed “iAM.NICE” (in silico Atom Mapped Network Integrated Computational Explorer), for the atom-level reconstruction of metabolic networks from the in silico labeled substrates to elucidate the mass flow in a biochemical reaction network. “iAM.NICE” transfers the label(s)

2015

Walkability After the Car; looking into low-density urbanity

Taking the recent decline in ‘automobilities’ as a departure point, in this article, we reconstruct the constant opposition of pedestrian and car that marked the theoretical debates as well as the urban projects throughout the last century to better understand the implications and potentials of a possible inversion towards a post-car era, where gradually a mobility based on corporeal capacities takes primacy. We will trace the inversion through a historical path from car as an instrument of democracy –democ

Laboratory of Urbanism, EPFL2015

Developing a Reconciled Genome-Scale Model of the Malaria Parasite Plasmodium falciparum and its Thermodynamics-based Flux Balance Analysis

Understanding the metabolism of the malaria parasites is of high priority to identify novel enzymatic drug targets and face the rise in drug resistant parasites. Based on the knowledge of metabolic functions and molecular interactions, we can reconstruct genome-scale models (GEMs) to study the metabolic behavior of the organism as a whole. In this work, we have developed a reconciled GEM of Plasmodium falciparum, the deadliest of the malaria parasites. To accomplish this, we firstly reconstructed the metabo

2015

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Publications associées (22)

Unveiling gene perturbation effects through gene regulatory networks inference from single-cell transcriptomic data

2026

Environmental selection constrains metabolic network architecture despite taxonomic turnover in anaerobic digestion communities

Oxford University Press (OUP)2026

Unveiling functional-metabolic synergy in the healthy brain: multivariate integration of dynamic [ 18 F]FDG-PET and resting-state fMRI

bioRxiv2025

Investigating the deregulation of metabolic tasks via Minimum Network Enrichment Analysis (MiNEA) as applied to nonalcoholic fatty liver disease using mouse and human omics data

Vassily Hatzimanikatis, Vikash Kumar Pandey

2019

Explore RdhK based regulatory network of organohalide respiration using a hybrid proteins strategy

Christof Holliger

2019

Evaluating the similarity of biochemical reactions and its uses for mapping novel and orphan reactions to protein sequences

2018

Developing a Reconciled Genome-Scale Model of the Malaria Parasite Plasmodium falciparum and its Thermodynamics-based Flux Balance Analysis

2015