Related papers: Automated generation of bacterial resource allocat…

The metabolic network plays a crucial role in regulating bacterial metabolism and growth, but it is subject to inherent molecular stochasticity. Previous studies have utilized flux balance analysis and the maximum entropy method to predict…

Collaborative Business Analysis (CBA) is a methodology that involves bringing together different stakeholders, including business users, analysts, and technical specialists, to collaboratively analyze data and gain insights into business…

Protein dynamics play a crucial role in protein biological functions and properties, and their traditional study typically relies on time-consuming molecular dynamics (MD) simulations conducted in silico. Recent advances in generative…

Many dynamic processes such as telecommunication and transport networks can be described through discrete time series of graphs. Modelling the dynamics of such time series enables prediction of graph structure at future time steps, which…

Metabolic fluxes in cells are governed by physical, physiological, and economic principles. Here I assume an optimal allocation of enzyme resources and postulate a general principle for metabolism: each enzyme must convert less valuable…

An automated resource analysis technique is introduced, targeting a Call-By-Push-Value abstract machine, with memory prediction as a practical goal. The machine has a polymorphic and linear type system enhanced with a first-order logical…

Organisms have evolved a variety of mechanisms to cope with the unpredictability of environmental conditions, and yet mainstream models of metabolic regulation are typically based on strict optimality principles that do not account for…

An extensive rewiring of cell metabolism supports enhanced proliferation in cancer cells. We propose a systems level approach to describe this phenomenon based on Flux Balance Analysis (FBA). The approach does not explicit a cell biomass…

Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data. Approximate Bayesian Computation (ABC) is devoted to these complex…

Dynamic flux balance analysis uses a quasi-steady state assumption to calculate an organism's metabolic activity at each time-step of a dynamic simulation, using the well-known technique of flux balance analysis. For microbial communities,…

We present RKappa, a framework for the development and analysis of rule-based models within a mature, statistically empowered R environment. The infrastructure allows model editing, modification, parameter sampling, simulation, statistical…

Probe-level models have led to improved performance in microarray studies but the various sources of probe-level contamination are still poorly understood. Data-driven analysis of probe performance can be used to quantify the uncertainty in…

This article describes lcpy, an open-source python package that allows for advanced parametric Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) analysis. The package is designed to allow the user to model a process with a flexible,…

We revise the procedure proposed by Balassa to infer comparative advantage, which is a standard tool, in Economics, to analyze specialization (of countries, regions, etc.). Balassa's approach compares the export of a product for each…

Modern biomedical data mining requires feature selection methods that can (1) be applied to large scale feature spaces (e.g. `omics' data), (2) function in noisy problems, (3) detect complex patterns of association (e.g. gene-gene…

Estimation by Analogy (EBA) is an increasingly active research method in the area of software engineering. The fundamental assumption of this method is that the similar projects in terms of attribute values will also be similar in terms of…

This paper introduces the shapr R package, a versatile tool for generating Shapley value-based prediction explanations for machine learning and statistical regression models. Moreover, the shaprpy Python library brings the core capabilities…

Prescriptive Performance Analysis (PPA) has shown to be more useful than traditional descriptive and diagnostic analyses for making sense of Big Data (BD) frameworks' performance. In practice, when processing large (RDF) graphs on top of…

Radiology report generation is crucial in medical imaging,but the manual annotation process by physicians is time-consuming and labor-intensive, necessitating the develop-ment of automatic report generation methods. Existingresearch…

The increasing need for causal analysis in large-scale industrial datasets necessitates the development of efficient and scalable causal algorithms for real-world applications. This paper addresses the challenge of scaling causal algorithms…