output
20132026
most citedRoom-temperature superfluidity in a polariton condensate

380 citations

Showing q-bio.MNShow all

13 papers · 1 filter

q-bio.MN2021★ 12 cited

Relationship between fitness and heterogeneity in exponentially growing microbial populations

Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani +2

Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This re…

q-bio.MN2019★ 28 cited

Competing endogenous RNA crosstalk at system level

Mattia Miotto, Enzo Marinari, Andrea De Martino

microRNAs (miRNAs) regulate gene expression at post-transcriptional level by repressing target RNA molecules. Competition to bind miRNAs tends in turn to correlate their targets, e…

q-bio.MN2019★ 4 cited

Independent channels for miRNA biosynthesis ensure efficient static and dynamic control in the regulation of the early stages of myogenesis

Jonathan Fiorentino, Andrea De Martino

Motivated by recent experimental work, we define and study a deterministic model of the complex miRNA-based regulatory circuit that putatively controls the early stage of myogenesi…

q-bio.MN2017★ 6 cited

Statistics of optimal information flow in ensembles of regulatory motifs

Andrea Crisanti, Andrea De Martino, Jonathan Fiorentino

Genetic regulatory circuits universally cope with different sources of noise that limit their ability to coordinate input and output signals. In many cases, optimal regulatory perf…

q-bio.MN2017★ 2 cited

Constraint-based inverse modeling of metabolic networks: a proof of concept

Daniele De Martino, Andrea De Martino

We consider the problem of inferring the probability distribution of flux configurations in metabolic network models from empirical flux data. For the simple case in which experime…

q-bio.MN2017★ 28 cited

ceRNA crosstalk stabilizes protein expression and affects the correlation pattern of interacting proteins

Araks Martirosyan, Andrea De Martino, Andrea Pagnani +1

Gene expression is a noisy process and several mechanisms, both transcriptional and posttranscriptional, can stabilize protein levels in cells. Much work has focused on the role of…

q-bio.MN2017★ 7 cited

Translating ceRNA susceptibilities into correlation functions

Araks Martirosyan, Matteo Marsili, Andrea De Martino

Competition to bind microRNAs induces an effective positive crosstalk between their targets, therefore known as `competing endogenous RNAs' or ceRNAs. While such an effect is known…

q-bio.MN2017★ 8 cited

Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype

Jorge Fernandez-de-Cossio-Diaz, Andrea De Martino, Roberto Mulet

We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient…

q-bio.MN2016★ 193 cited

Constrained Allocation Flux Balance Analysis

Matteo Mori, Terence Hwa, Olivier C. Martin +2

New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement F…

q-bio.MN2016★ 14 cited

Noise Processing by MicroRNA-Mediated Circuits: the Incoherent Feed-Forward Loop, Revisited

Silvia Grigolon, Francesca Di Patti, Andrea De Martino +1

The intrinsic stochasticity of gene expression is usually mitigated in higher eukaryotes by post-transcriptional regulation channels that stabilise the output layer, most notably p…

q-bio.MN2016★ 31 cited

Probing the limits to microRNA-mediated control of gene expression

Araks Martirosyan, Matteo Figliuzzi, Enzo Marinari +1

According to the `ceRNA hypothesis', microRNAs (miRNAs) may act as mediators of an effective positive interaction between long coding or non-coding RNA molecules, carrying signific…

q-bio.MN2016★ 50 cited

Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli

Daniele De Martino, Fabrizio Capuani, Andrea De Martino

The solution space of genome-scale models of cellular metabolism provides a map between physically viable flux configurations and cellular metabolic phenotypes described, at the mo…

q-bio.MN2015★ 21 cited

Quantitative constraint-based computational model of tumor-to-stroma coupling via lactate shuttle

Fabrizio Capuani, Daniele De Martino, Enzo Marinari +1

Cancer cells utilize large amounts of ATP to sustain growth, relying primarily on non-oxidative, fermentative pathways for its production. In many types of cancers this leads, even…