Polarimetric instrument Global Navigation Satellite System - Reflectometry airborne data.

In this paper, three datasets are described. The first dataset is a complete set of GNSS-R (GNSS-R: Global Navigation Satellite System - Reflectometry) airborne data. This dataset has been generated with the data acquired with the GLObal Navigation Satellite System Reflectometry Instrument (GLORI) developed at Centre d'Etudes Spatiales de la Biosphère (CESBIO), during the Land surface Interactions with the Atmosphere over the Iberian Semi-arid Environment (LIAISE) campaign in north-eastern Spain during the summer of 2021.

WellInverter: a web application for the analysis of fluorescent reporter gene data.

Background: Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation.

Analysis and Predictability of Drought In Northwest Africa Using Optical and Microwave Satellite Remote Sensing Products.

In a context of high stress on water resources and agricultural production at the global level, together with climate change marked by an increase in the frequency of these events, drought is considered to be a strong threat both socially and economically. The Mediterranean region is a hot spot of climate change; it is also characterized by a scarcity of water resources that places intense pressure on agricultural productivity. This article analyzes the potential for using multiple remote sensing tools in the quantification and predictability of drought in Northwest Africa.

Robust reconstruction of gene expression profiles from reporter gene data using linear inversion.

Motivation: Time-series observations from reporter gene experiments are commonly used for inferring and analyzing dynamical models of regulatory networks. The robust estimation of promoter activities and protein concentrations from primary data is a difficult problem due to measurement noise and the indirect relation between the measurements and quantities of biological interest.

Results: We propose a general approach based on regularized linear inversion to solve a range of estimation problems in the analysis of reporter gene data, notably the inference of growth rate, promoter activity, and protein concentration profiles.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

Background: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing.

Genetic network analyzer: a tool for the qualitative modeling and simulation of bacterial regulatory networks.

Genetic Network Analyzer (GNA) is a tool for the qualitative modeling and simulation of gene regulatory networks, based on so-called piecewise-linear differential equation models. We describe the use of this tool in the context of the modeling of bacterial regulatory networks, notably the network of global regulators controlling the adaptation of Escherichia coli to carbon starvation conditions. We show how the modeler, by means of GNA, can define a regulatory network, build a model of the network, determine the steady states of the system, perform a qualitative simulation of the network dynamics, and analyze the simulation results using model-checking tools.

Efficient parameter search for qualitative models of regulatory networks using symbolic model checking.

Motivation: Investigating the relation between the structure and behavior of complex biological networks often involves posing the question if the hypothesized structure of a regulatory network is consistent with the observed behavior, or if a proposed structure can generate a desired behavior.

Results: The above questions can be cast into a parameter search problem for qualitative models of regulatory networks. We develop a method based on symbolic model checking that avoids enumerating all possible parametrizations, and show that this method performs well on real biological problems, using the IRMA synthetic network and benchmark datasets.

A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks.

Background: The study of biological networks has led to the development of increasingly large and detailed models. Computer tools are essential for the simulation of the dynamical behavior of the networks from the model. However, as the size of the models grows, it becomes infeasible to manually verify the predictions against experimental data or identify interesting features in a large number of simulation traces.

Search for steady states of piecewise-linear differential equation models of genetic regulatory networks.

Analysis of the attractors of a genetic regulatory network gives a good indication of the possible functional modes of the system. In this paper we are concerned with the problem of finding all steady states of genetic regulatory networks described by piecewise-linear differential equation (PLDE) models. We show that the problem is NP-hard and translate it into a propositional satisfiability (SAT) problem.

Qualitative simulation of the carbon starvation response in Escherichia coli.

In case of nutritional stress, like carbon starvation, Escherichia coli cells abandon their exponential-growth state to enter a more resistant, non-growth state called stationary phase. This growth-phase transition is controlled by a genetic regulatory network integrating various environmental signals. Although E.

Validation of qualitative models of genetic regulatory networks by model checking: analysis of the nutritional stress response in Escherichia coli.

Motivation: The modeling and simulation of genetic regulatory networks have created the need for tools for model validation. The main challenges of model validation are the achievement of a match between the precision of model predictions and experimental data, as well as the efficient and reliable comparison of the predictions and observations.

Results: We present an approach towards the validation of models of genetic regulatory networks addressing the above challenges.

Potato flour viscosity improvement is associated with the expression of a wheat LMW-glutenin gene.

It has been previously shown that expression of a high-molecular-weight glutenin (HMW-GS) in transgenic wheat seeds resulted in the improvement of flour functional properties. In this study, potato flour viscosity was improved through a specific expression of a low-molecular-weight glutenin (LMW-GS-MB1) gene in tuber. The resulting construct was introduced into potato leaf explants (Solanum tuberosum cv Kennebec) through Agrobacterium tumefaciens-mediated gene transfer.

Paclitaxel antibody conjugates and trehalose for preserving the immunological activity after freeze-drying.

Antibodies and anticancer drug-antibody conjugates used in experimental cancer research or clinically must be freeze-dried for preserving the activity and storage at room temperature. This often results in some denaturation and loss of activity. We describe a recovery of the cytotoxic activity of a paclitaxel-mAb immunoconjugate after freeze-drying.

Qualitative simulation of genetic regulatory networks using piecewise-linear models.

In order to cope with the large amounts of data that have become available in genomics, mathematical tools for the analysis of networks of interactions between genes, proteins, and other molecules are indispensable. We present a method for the qualitative simulation of genetic regulatory networks, based on a class of piecewise-linear (PL) differential equations that has been well-studied in mathematical biology. The simulation method is well-adapted to state-of-the-art measurement techniques in genomics, which often provide qualitative and coarse-grained descriptions of genetic regulatory networks.

Qualitative simulation of the initiation of sporulation in Bacillus subtilis.

Under conditions of nutrient deprivation, the Gram positive soil bacterium Bacillus subtilis can abandon vegetative growth and form a dormant, environmentally-resistant spore instead. The decision to either divide or sporulate is controlled by a large and complex genetic regulatory network integrating various environmental, cell-cycle, and metabolic signals. Although sporulation in B.

Genetic Network Analyzer: qualitative simulation of genetic regulatory networks.

Motivation: The study of genetic regulatory networks has received a major impetus from the recent development of experimental techniques allowing the measurement of patterns of gene expression in a massively parallel way. This experimental progress calls for the development of appropriate computer tools for the modeling and simulation of gene regulation processes.

Results: We present Genetic Network Analyzer (GNA), a computer tool for the modeling and simulation of genetic regulatory networks.